bluuebunny/crossref_metadata_2025 huggingface dataset:
HOMA-beta independently predicts survival in patients with advanced cancer on treatment with immune checkpoint inhibitors
Authors: Watanabe Mayu , Eguchi Jun , Takamoto Atsushi , Kanzaki Hiromitsu , Noda Yohei , Kagawa Syunsuke , Wada Jun
Published: December 2024

Background

Although immune checkpoint inhibitors (ICIs) are effective cancer drugs, ICI-induced diabetes is a rare but a life-threatening adverse event for patients. The deleterious action of ICI on pancreatic beta-cell function is a concern. However, the influence of ICI on insulin synthesis and secretion in patients with cancer without diabetes remains unknown.

Methods

This study included 87 patients diagnosed with advanced cancer. Glucose metabolism markers (HbA1c, HOMA-IR) and indicators of insulin secretory capacity (HOMA-beta, C-peptide) were prospectively evaluated in patients with ICI-treated cancers to determine their association with cancer prognosis.

Results

Patients with overall survival (OS) ≥ 7 months had substantially higher HOMA-beta levels at baseline (p=0.008) and 1 month after ICI administration (p=0.006) compared to those with OS <7 months. The median OS was significantly longer in patients with HOMA-beta ≥ 64.24 (13 months, 95%CI: 5.849–20.151, 37 events) than in those with HOMA-beta < 64.24 (5 months, 95%CI: 3.280–6.720, 50 events) (p=0.013). Further, the median progression-free survival (PFS) was significantly longer in patients with HOMA-beta ≥ 66.43 (4 months, 95%CI: 3.073–4.927, 33 events) than in those with HOMA-beta < 66.43 (2 months, 95%CI: 1.410–2.590, 54 events) (p=0.025). Additionally, multivariable logistic regression analysis revealed that a HOMA-beta value ≥ 64.24 independently predicted longer OS in ICI-treated patients.

Conclusions

Pre-ICI HOMA-beta level is linked to longer OS in ICI-treated patients. This connection is significant and shows that insulin secretory capacity may predict ICI efficacy.
Cytokine screening identifies TNF to potentially enhance immunogenicity of pediatric sarcomas
Authors: Gassmann Hendrik , Thiede Melanie , Weiß Jennifer , Biele Emilie , Flohé Luisa , Lachermaier Helena , Prexler Carolin , Evdokimova Valentina , Radvanyi Laszlo , Akhtar Irfan , Morcos Mina N. F. , Auer Franziska , Schober Sebastian J. , Hauer Julia , Thiel Uwe , von Heyking Kristina
Published: December 2024

Introduction

Pediatric sarcomas, including osteosarcoma (OS), Ewing sarcoma (EwS) and rhabdomyosarcoma (RMS) carry low somatic mutational burden and low MHC-I expression, posing a challenge for T cell therapies. Our previous study showed that mediators of monocyte maturation sensitized the EwS cell line A673 to lysis by HLA-A*02:01/CHM1319-specific allorestricted T cell receptor (TCR) transgenic CD8+ T cells (CHM1319 CD8+ T cells).

Methods

In this study, we tested a panel of monocyte maturation cytokines for their ability to upregulate immunogenic cell surface markers on OS, EwS and RMS cell lines, using flow cytometry. xCELLigence, SRB and ELISpot assays were used to assess whether TNF pretreatment increases CD8+ T cell cytotoxicity.

Results

We observed that TNF and IL-1β upregulated MHC class I, ICAM-1 as well as CD83 and PD-L1 on the surface of pediatric sarcoma cell lines, while IL-4, GM-CSF, IL-6 and PGE2 failed to induce respective effects. Although pretreatment of pediatric sarcoma cell lines with TNF did not improve unspecific peripheral blood mononuclear cells (PBMCs) cytotoxicity, TNF enhanced specific lysis of 1/3 HLA-A2+ EwS cell lines by CHM1319 CD8+ T cells depending on MHC-I expression and ICAM-1 upregulation.

Discussion

Our study supports utilization of TNF or TNF-inducing regimens for upregulation of MHC-I and costimulatory surface molecules on pediatric sarcoma cells and for enhancing recognition of responsive HLA-A2+ EwS tumor cells by antigen-specific CD8+ T cells.
The mitochondrial function of peripheral blood cells in cognitive frailty patients
Authors: Qin Li , Huang Tingting , Zhang Danmei , Wei Liqin , Li Guochao , Zhu Qianqian , Tong Qiangwei , Ding Guoxian , Liu Juan
Published: December 2024

Background

Cognitive frailty (CF), characterized by the coexistence of physical frailty and cognitive impairment, is linked to increased morbidity and mortality in older adults. While CF has been linked to multiple physiological and lifestyle factors, the underlying biological mechanisms remain poorly understood. This study investigated the risk factors for CF and explored the relationship between mitochondrial function and CF in hospitalized patients.

Methods

A total of 279 hospitalized individuals were recruited from December 2020 to August 2022, conducted comprehensive clinical assessments, and collected peripheral blood samples. CF was evaluated using the Physical Frailty Phenotype and Montreal Cognitive Assessment scales. Nutritional status was assessed with the Mini Nutritional Assessment, and depression was measured using the Geriatric Depression Scale. DNA was obtained from the peripheral blood and interrogated for mitochondrial DNA copy number (mtDNAcn). Peripheral blood mononuclear cells isolated from peripheral blood were examined for respiratory function and reactive oxygen species (ROS) levels. Additionally, plasma samples were analyzed for inflammatory markers and Carnitine Palmitoyltransferase II (CPT2).

Results

Among the participants, 90 were classified as CF and 46 as non-CF. Logistic regression analysis revealed that increased age (OR 1.156, 95% CI 1.064–1.255), lower educational attainment (OR 0.115, 95% CI 0.024–0.550), malnutrition (OR 0.713, 95% CI 0.522–0.973), and higher depression scores (OR 1.345, 95% CI 1.065–1.699) were significantly associated with CF. The independent t tests and Mann–Whitney U tests showed the CF group exhibited impaired mitochondrial function, characterized by reduced mtDNAcn and respiratory activity, coupled with elevated ROS, interleukin-6, and CPT2 levels compared with the non-CF group. After adjusted for age, sex, and BMI, compared with non-CF group, the OR values for the CF group of mtDNAcn and ROS were 0.234 (95% CI = 0.065–0.849) (p = 0.027) and 1.203 (95% CI = 1.075–1.347) (p = 0.001), respectively. The Sensitive analysis showed that the area under curve values for mtDNAcn and ROS were 0.653 and 0.925.

Conclusion

Age, lower educational attainment, malnutrition, and depression are significant risk factors for CF. Moreover, mitochondrial dysfunction, characterized by decreased mtDNAcn, impaired respiratory function and increased ROS levels appears to be a critical phenotype of CF.
Case report: A successful live birth after in vitro fertilization and embryo transfer in a patient with endometrial cancer who was treated conservatively
Authors: Fan Yifan , Song Hui , Chen Xu , Zhang Pei , Si Jingwen , Dong Hui
Published: December 2024

Objective

To describe a patient conceiving with in vitro fertilization and embryo transfer(IVF-ET) after conservative treatment of early stage endometrial cancer.

Patient

A 31-year-old multiparous woman diagnosed with highly-differentiated (G1) endometrial adenocarcinoma (grade IA).

Intervention(s)

After four courses of conservative treatment each followed by hysteroscopic biopsy and endometrial curettage,assisted reproductive technology was performed.

Main outcome measure(s)

Successful pregnancy and delivery without residual endometrial cancer.

Results(s)

A healthy normal female infant with a birth weight of 3,690 g was born by cesarean section at 38 + 2 weeks’ gestation. No residual malignant cells was detected on a biopsy during cesarean section.

Conclusion(s)

Conservative fertility-sparing treatment are crucial for young patients with early stage endometrial cancer. Assisted reproductive technologies may be considered to assist such patients to conceive as soon as possible.
Global research trends and frontiers in ferroptosis in hepatocellular carcinoma: a bibliometric and visualization study
Authors: Ning Lin , Chen Di , Han Jie , Xie Guanyue , Sun Jianguang
Published: December 2024

Background

Since the emergence of the hot topic of “ferroptosis,” numerous studies have explored its role in hepatocellular carcinoma (HCC), revealing its significance in the disease’s pathogenesis, progression, and treatment. However, there remains a significant gap in the quantitative analysis of ferroptosis in HCC. Therefore, this study aims to comprehensively assess the research progress and evolution in this field through bibliometric and citation analysis.

Method

On June 27, 2024, the author conducted a literature search, extracting relevant publications from the Web of Science Core Collection (WOSCC) Science Citation Index Expanded (SCIE) spanning from January 2010 to December 2023. Subsequently, the compiled documents were subjected to bibliometric evaluation and analysis using visualization tools such as R package “bibliometrix”, CiteSpace and VOSviewer.

Result

The search yielded 576 papers by 3,925 authors, encompassing contributions from 34 countries and 685 institutions, published across 250 journals, including 25,889 co-cited references from 2,600 journals. Notably, China leads with a significant publication count of 481 articles (accounting for 83.5%) and demonstrates the strongest collaboration with the United States. The multifaceted role of ferroptosis in hepatocellular carcinoma (HCC) has garnered considerable attention. In recent years, research into disease prognosis, the tumor microenvironment, and targeted therapies involving immunology has become key themes and emerging frontiers in this field.

Conclusion

This study meticulously compiled and analyzed the current discourse and emerging perspectives on ferroptosis in HCC. Identifying research trends and hotspots offers valuable guidance for future investigations and provides a basis for the development of novel therapeutic strategies to improve HCC prognosis and treatment outcomes.
Ailanthone blocks mitophagy to promote mtDNA leakage through BAX-BAK1 pores and suppress hepatocellular carcinoma cell proliferation
Authors: Qin Yan , Gao Ying , Wu Dan , Liu Qing-Qing , Su Chang , Liu Guan , Yang Le , Zhao Ming-Gao , Yao Jing-Yue
Published: December 2024

Introduction

Hepatocellular carcinoma (HCC), the third leading cancer mortality worldwide, shows rising incidence. The mitochondria in HCC cells are prone to damage from metabolic stress and oxidative stress, necessitating heightened mitophagy for mitochondrial homeostasis and cell survival. Thus, mitophagy inhibition is a promising HCC therapy. The traditional Chinese medicinal herb ailanthone have proved promote mitochondrial dysfunction and inhibits HCC. However, the underlying mechanism remains unclear.

Methods

CCK8 assay was applied to detect the proliferation. JC-1, MitoTracker Red/Green and MitoSOX staining were applied to detect the mitochondrial homeostasis. Inflammatory factors were analysed via ELISA and WB assay. Mitochondria and cytoplasm separation, genome extraction and qPCR were used to detect mitochondrial DNA (mtDNA) leakage. Mitochondria ultrastructure was detected by transmission electron microscopy. WB and IHC experiments were applied to detect protein expression. Protein-protein interactions detected by immunoprecipitation and immunofluorescence imaging. The in vivo antitumor effect was validated by the xenograft mouse model.

Results

In this study, we demonstrated the potent anti-HCC properties of ailanthone and revealed its molecular mechanism. In vitro studies demonstrated that ailanthone effectively inhibited PINK1-PRKN mediated mitophagy and promoted BAX-BAK1 mitochondrial pores formation through PRKN inhibition. This process led to the mitochondrial mtDNA leakage into the cytoplasm, which subsequently triggered the induction of inflammatory factors. The inhibition of mitophagy and the activation of inflammatory response ultimately led to HCC proliferation inhibition. In vivo studies demonstrated that ailanthone exhibited stronger anti-HCC activity than 5-Fluorouracil (5-FU), with no significant adverse effects on animal body weight or the physiological functions of vital organs.

Conclusion

This study highlighted the efficacy of ailanthone against HCC and elucidated its underlying molecular mechanisms, suggesting the promising therapeutic potential of ailanthone for HCC.
Integrating drivers of pro-environmental behavior and physical activity to explore (in) compatibilities between an active and an environmentally sustainable lifestyle
Authors: Eriksson Louise , Linde Stefan
Published: December 2024

Introduction

Sport and outdoor activities have benefits on people’s health and well-being but may also increase the frequency of unsustainable behaviors. The present study explores drivers of travel mode choice and consumption of material (clothes and equipment) associated with physical activity to clarify the extent to which an active and sustainable lifestyle is compatible. The role of identity and varying levels of internalized motivation for pro-environmental behaviors (autonomous and controlled environmental motivation) and engagement in physical activity (autonomous and controlled activity motivation) was examined. In addition, socio-demographic, physical context, and life situation correlates of environmentally significant behaviors associated with physical activity were analyzed.

Methods

A survey of a random sample of the general public in Sweden (n = 1013) was conducted.

Results

After controlling for hours of physical activity, the study showed that environmental self-identity was related to a lower likelihood of using the car alone via autonomous environmental motivation and to a higher likelihood of buying and selling used material via controlled environmental motivation. Physical activity drivers displayed diverse impacts on environmentally significant behaviors, e.g., athlete identity was associated with a higher likelihood of using the car alone and buying new material, but also selling used material. Being a member of a sport or outdoor organization was related to a higher likelihood of using the car alone and buying new material, but also using active travel modes as well as buying and selling used material.

Discussion

With a better understanding of the drivers of environmentally significant behaviors in this domain, strategies to encourage sustainable transport and circular flows of material in sports and outdoors can be outlined.
Stress, mental symptoms and well-being in students: a gender analysis
Authors: del Pino María-José , Matud M. Pilar
Published: December 2024

Introduction

Stress is a major problem among students, threatening their health and well-being. The aim of the research is to analyze the sources of stress in students and to investigate whether there are gender differences and differences between university and non-university students in stress, coping styles, mental symptoms and well-being. A second aim is to know the relevance of age, education, stress, coping styles, self-esteem and social support on mental symptoms, psychological well-being and life satisfaction of boys and girls.

Methods

The study was cross-sectional. The sample consisted of 1,426 students between the ages of 16 and 26.

Results and discussion

The results of the ANOVAs showed that although there were some gender differences, being a university student or not explained more variance than gender. University students had more chronic stress than non-university students. However, they were more satisfied with their studies, had healthier coping styles, fewer mental symptoms, and greater well-being. For both genders, the main predictor of more mental symptoms was a higher emotional coping style. This was followed by lower self-esteem, a higher number of stressful life events, and higher chronic stress. Higher study dissatisfaction was associated with lower psychological well-being and lower life satisfaction. Higher chronic stress was associated with lower life satisfaction. It is concluded that stress and coping styles are relevant to students’ mental health. The results of this study are relevant to the design of policies, strategies, and programs to improve students’ mental health and well-being.
Development and validation of interpretable machine learning models for postoperative pneumonia prediction
Authors: Xiang Bingbing , Liu Yiran , Jiao Shulan , Zhang Wensheng , Wang Shun , Yi Mingliang
Published: December 2024

Background

Postoperative pneumonia, a prevalent form of hospital-acquired pneumonia, poses significant risks to patients’ prognosis and even their lives. This study aimed to develop and validate a predictive model for postoperative pneumonia in surgical patients using nine machine learning methods.

Objective

Our study aims to develop and validate a predictive model for POP in surgical patients using nine machine learning algorithms. By evaluating the performance differences among these machine learning models, this study aims to assist clinicians in early prediction and diagnosis of POP, providing optimal interventions and treatments.

Methods

Retrospective data from electronic medical records was collected for 264 patients diagnosed with postoperative pneumonia and 264 healthy control surgical patients. Through correlation screening, chi-square tests, and feature importance ranking, 47 variables were narrowed down to 5 potential predictive factors based on the main cohort of 528 patients. Nine machine learning models, including k-nearest neighbors, support vector machine, random forest, decision tree, gradient boosting machine, adaptive boosting, naive bayes, general linear model, and linear discriminant analysis, were developed and validated to predict postoperative pneumonia. Model performance was evaluated using the area under the receiver operating curve, sensitivity, specificity, accuracy, precision, recall, and F1 score. A distribution plot of feature importance and feature interaction was obtained to interpret the machine learning models.

Results

Among 17,190 surgical patients, 264 (1.54%) experienced postoperative pneumonia, which resulted in adverse outcomes such as prolonged hospital stay, increased ICU admission rates, and mortality. We successfully established nine machine learning models for predicting postoperative pneumonia in surgical patients, with the general linear model demonstrating the best overall performance. The AUC of the general linear model on the testing set was 0.877, with an accuracy of 0.82, specificity of 0.89, sensitivity of 0.74, precision of 0.88, and F1 score of 0.80. Our study revealed that the duration of bed rest, unplanned re-operation, end-tidal CO2, postoperative albumin, and chest X-ray film were significant predictors of postoperative pneumonia.

Conclusion

Our study firstly demonstrated that the general linear model based on 5 common variables might predict postoperative pneumonia in the general surgical population.
“Less is more?” The association between crop specialization and dietary diversity in China
Authors: Cao Shouhui , Sun Fei , Wang Lijun , Hong Weihua
Published: December 2024

Dietary diversity is an important indicator used to measure family dietary quality and food safety status. Against the backdrop of the transformation of China’s agricultural production model from a diversified, small-scale approach to specialization, this paper presents a comprehensive investigation into the complex interrelationship between crop specialization and dietary diversity. It employs a multi-method approach, integrating theoretical insights with empirical evidence. The analysis is based on a micro-survey of 866 rural households, utilizing mediation, moderation, and unconditional quantile regression model. The results indicated that crop specialization had a notable negative impact on dietary diversity, particularly among II part-time and mountainous households. Further analysis of the mechanisms involved reveals that income exerts a mediating effect, while education and market factors exert a moderating effect. Such factors may serve to mask or reduce the negative effects of crop specialization on dietary diversity. In the reality that the trend of production specialization is irreversible, government interventions to ensure dietary diversity and food security for rural households, particularly II part-time households and those in mountainous regions, can be implemented in three key areas: income support, education enhancement, and market access improvement.
Anchor-Based Method for Inter-Domain Mobility Management in Software-Defined Networking
Authors: Kanda Akichy Adon Jean Rodrigue , Atta Amanvon Ferdinand , Trey Zacrada Françoise Odile , Babri Michel , Kora Ahmed Dooguy
Published: December 2024

Recently, there has been an explosive growth in wireless devices capable of connecting to the Internet and utilizing various services anytime, anywhere, often while on the move. In the realm of the Internet, such devices are called mobile nodes. When these devices are in motion or traverse different domains while communicating, effective mobility management becomes essential to ensure the continuity of their services. Software-defined networking (SDN), a new paradigm in networking, offers numerous possibilities for addressing the challenges of mobility management. By decoupling the control and data planes, SDN enables greater flexibility and adaptability, making them a powerful framework for solving mobility-related issues. However, communication can still be momentarily disrupted due to frequent changes in IP addresses, a drop in radio signals, or configuration issues associated with gateways. Therefore, this paper introduces Routage Inter-domains in SDN (RI-SDN), a novel anchor-based routing method designed for inter-domain mobility in SDN architectures. The method identifies a suitable anchor domain, a critical intermediary domain that contributes to reducing delays during data transfer because it is the closest domain (i.e., node) to the destination. Once the anchor domain is identified, the best routing path is determined as the route with the smallest metric, incorporating elements such as bandwidth, flow operations, and the number of domain hops. Simulation results demonstrate significant improvements in data transfer delay and handover latency compared to existing methods. By leveraging SDN’s potential, RI-SDN presents a robust and innovative solution for real-world scenarios requiring reliable mobility management.
The Potential of Mustard Seed Meal to Alleviate LPS-Induced Microbial Shifts in Weaned Piglets
Authors: Grosu Iulian A. , Pistol Gina C. , Marin Daniela E. , Taranu Ionelia
Published: December 2024

Mustard seed meal, an oil industry by-product, shows promise as a dietary additive in animal feed due to its rich content of bioactive compounds and antioxidant potential. The present study examined its impact on the gut microbiota of post-weaning piglets exposed to bacterial lipopolysaccharides (LPSs). Twenty-four cross-bred TOPIGS-40 piglets were divided into four groups: C—control group on a basal diet; LPS—group on a basal diet later exposed to lipopolysaccharides; M—group on a basal diet with an 8% w/w mustard seed meal addition; and M+LPS—a combined mustard and LPS group. After 21 days, colonic content analysis using Illumina 16S rRNA sequencing revealed that while LPS challenge led to an increased abundance of Spirochaetota and Desulfobacterota in the LPS group, the presence of mustard seed meal kept these levels low in the M+LPS group. Notably, the Firmicutes to Bacteroidota (F/B) ratio decreased from 2.87 to 1.12 in the M+LPS group. Furthermore, Lactobacillus showed a 4.7-fold increase while Lachnospira decreased by 67.7% in the M+LPS group compared to the LPS group. These findings highlight mustard seed meal’s potential to prevent LPS-induced gut dysbiosis, enhancing gut health in weaning piglets.
Obesity Prevalence and Associated Factors in Captive Asian Elephants (Elephas maximus) in China: A Body Condition Assessment Study
Authors: Tang Yinpu , Jia Ting , Zhou Fangyi , Wang Liang , Chen Ziluo , Zhang Li
Published: December 2024

Obesity is a prevalent health issue among captive wildlife, but the obesity status of captive Asian elephants (Elephas maximus) in China has not been systematically investigated. This study assessed obesity in 204 captive Asian elephants across 43 facilities by recording seven potentially relevant variables: sex, age, daily feed supply, proportion of high-calorie feed, outdoor enclosure area, outdoor time, and foot disorders. Body condition was evaluated using visual scoring, revealing a high prevalence of overweight and obesity, particularly in zoo-kept elephants. Over 70% of captive Asian elephants in China were classified as overweight or obese. Statistical analysis indicated that insufficient outdoor time is likely a primary contributor to obesity among zoo elephants. We recommend extending outdoor time and regulating the supply of high-calorie feeds (e.g., fruits, vegetables, and pellets) to promote exercise and balance energy intake. Additionally, implementing positive reinforcement training for routine health checks, including foot exams and blood sampling, could improve data collection on elephant health and welfare, ultimately enhancing obesity management and overall animal well-being.
Investigation of Ki-67 and Clinical Outcome in Feline Nasal Adenocarcinoma Treated Using Hypofractionated Radiotherapy
Authors: Aonta Premkamon , Jaiyangyeun Piraya , Theerapan Wutthiwong , Srisampan Supreeya , Wongsali Charuwan , Kovitvadhi Attawit , Jaroensong Tassanee
Published: December 2024

Ki-67 has been reported as a prognostic marker in human cancers treated using RT. The current study investigated the prognostic significance of Ki-67 expression and its association with clinicopathological characteristics in 19 cats diagnosed with nasal adenocarcinoma and treated using hypofractionated RT. Data collected encompassed signalment, clinical signs, clinicopathological variables, treatment outcomes, and survival times. Median survival times (MST) were estimated using Kaplan–Meier curves and analyzed based on the log-rank test. Based on the results, white blood cell counts were significantly (p < 0.001) higher before treatment than after, although this was not associated with survival time. The overall MST was 550 days (range: 56–1118 days). Cats achieving a favorable response (complete or partial response) had significantly (p = 0.006) longer survival times (1055 days) than those with a poor response (stable or progressive disease; 369 days). Cats with high Ki-67 expression had significantly (p = 0.028) longer survival times (1055 days) than those with low Ki-67 expression (256 days). These results suggested that Ki-67 may be a potential prognostic factor for feline nasal adenocarcinoma.
Pseudomonas aeruginosa Isolation from Urine Culture in Hospitalised Patients: Incidence of Complicated Urinary Tract Infections and Asymptomatic Bacteriurias and Impact on Treatment of the EUCAST 2020 Update
Authors: Pallotto Carlo , Milani Paolo , Catalpi Caterina , Pietrella Donatella , Curcio Giuseppe , Allegrucci Filippo , Gidari Anna , Svizzeretto Elisabetta , Genga Giovanni , Tommasi Andrea , Mencacci Antonella , Francisci Daniela
Published: December 2024

Background. Urinary tract infections (UTIs) and asymptomatic bacteriurias (ABU) represent a large field of interest for antimicrobial stewardship programmes especially after 2020 EUCAST update in antimicrobial susceptibility testing interpretation and the possible related increase in carbapenems’ prescription rate. The aim of this study was to evaluate the impact of the 2020 EUCAST update on antibiotic prescription in UTI due to Pseudomonas aeruginosa organism and their characteristics. Methods. A retrospective observational study. We enrolled all the patients with P. aeruginosa isolation from urine, admitted to our hospital from 2018 to 2021. We compared demographic, clinical, and microbiological characteristics and treatment between cases before 2020 EUCAST update (period A, 2018–2019) and after it (period B, 2020–2021). Results. A total of 643 cases was analysed, 278 in period A and 365 in period B; 65% were ABU. Carbapenems’ prescription rate significantly increased in period B when considering ABU alone (21.4% vs. 41%, p = 0.016) and all the treated cases (treated ABU and UTI; 27.8% vs. 41.4%, p = 0.013); anti-Pseudomonas cephalosporins prescription significantly decreased in period B when considering ABU alone (15.7% vs. 3.6%, p = 0.021), UTI alone (20.7% vs. 5.9%, p = 0.009) and all the treated cases (18.5% vs. 5.9%, p = 0.001). Conclusions. The 2020 EUCAST update could have contributed to an increase in carbapenem prescriptions. UTI and ABU represent a large field of interest for stewardship interventions both from a diagnostic and therapeutic point of view.
Fusion Partner Facilitates Expression of Cell-Penetrating Peptide L2 in Pichia pastoris
Authors: Li Xuan , Yang Na , Fang Yuxin , Mao Ruoyu , Hao Ya , Teng Da , Dong Na , Shan Anshan , Wang Jianhua
Published: December 2024

Background: L2 is formed by combining the pheromone of Streptococcus agalactiae (S. agalactiae) and a cell-penetrating peptide (CPP) with cell-penetrating selectivity. L2 has more significant penetration and better specificity for killing S. agalactiae. However, the production of AMPs by chemical synthesis is always a challenge because of the production cost. Methods: This study was devoted to the heterologous expression of the cell-penetrating peptide L2 in Pichia pastoris using SUMO and a short acidic fusion tag as fusion partners, and the high-density expression of SUMO-L2 was achieved in a 5 L fermenter. Results: The results showed that SUMO-L2 expression in the 5 L fermenter reached 629 mg/L. The antibacterial activity of recombinant L2 was examined; the minimum inhibitory concentration (MICs) and minimum bactericidal concentration (MBCs) of purified L2 were 4–8 μg/mL and 8–16 μg/mL against S. agalactiae after 84 h of lysis with 50% formic acid. Conclusions: The findings suggest that SUMO is a suitable fusion tag to express cell-penetrating peptide L2.
Chitosan Nanoparticle-Mediated Delivery of Alstonia venenata R.Br. Root Methanolic Extract: A Promising Strategy for Breast Cancer Therapy in DMBA-Induced Breast Cancer in Sprague Dawley Rats
Authors: Jeganathan Aarthi , Arunachalam Karuppusamy , Byju Anju , Rani George Anju , Sajeev Sradha , Thangasamy Kavimani , Natesan Geetha
Published: December 2024

Alstonia venenata R.Br., a plant native to the Western Ghats, is recognized for its diverse medicinal properties. The plant’s extracts, particularly rich in alkaloids and other bioactive compounds, have shown potential anticancer activity. This study investigates the therapeutic potential of chitosan nanoparticles (CNPs) loaded with the root methanolic extract (RME) of A. venenata in combating breast cancer induced by dimethylbenz(a)anthracene (DMBA) in female Sprague Dawley rats. The RME-loaded chitosan nanoparticles (RME-EnCNPs) were synthesized and characterized, and their in vivo efficacy was evaluated. Treatment with RME-EnCNPs significantly inhibited tumor progression, which is evidenced by reduced tumor volume, burden, and incidence. Moreover, the nanoparticles demonstrated a sustained release of the active compounds, leading to marked improvements in various biochemical, enzymatic, and histopathological parameters. The study found that both RME and RME-EnCNPs effectively suppressed tumor growth, with RME-EnCNPs showing superior efficacy in modulating tumor progression. Antioxidant assays revealed that treatment with RME-EnCNPs (500 mg/kg) resulted in significant increases in total protein, superoxide dismutase (SOD), catalase, glutathione peroxidase (GPx), and glutathione (GSH) levels, alongside a marked reduction in lipid peroxidation (LPO) (p < 0.001). These findings suggest that RME-EnCNPs exert a potent antioxidant effect, mitigating oxidative stress within the tumor microenvironment. The root extract of A. venenata and its nanoparticle formulation hold promise as a potential therapeutic agent for breast cancer, warranting further investigation to isolate active bioactive compounds and elucidate their mechanisms of action.
Environmental Impacts of Orphaned and Abandoned Wells: Methane Emissions, and Implications for Carbon Storage
Authors: Alsubaih Ahmed , Sepehrnoori Kamy , Delshad Mojdeh
Published: December 2024

Orphaned and abandoned wells in the United States pose significant environmental risks, including methane emissions, groundwater contamination, and ecosystem degradation. These wells also threaten the integrity of carbon capture and storage (CCS) projects by providing potential leakage pathways for stored CO2, particularly if they lack proper plugging and well integrity. Although the exact number of orphaned and abandoned wells is uncertain due to poor historical documentation, recent estimates suggest there could be as many as 3.9 million such wells nationwide, emitting approximately 3.2 Teragram (Tg) of methane annually. This study investigates the distribution of orphaned and abandoned wells across the United States, presenting new estimates of documented wells and exploring their methane emissions. Through state-level data analysis, the number of documented orphan wells is estimated to be significantly higher than previously reported. A machine learning model, specifically a RandomForestRegressor, was employed to predict the locations of potential orphan wells, enhancing the ability to target monitoring and remediation efforts.
Qualitative and Quantitative Analysis of Volatile Molecular Biomarkers in Breath Using THz-IR Spectroscopy and Machine Learning
Authors: Tretyakov Akim , Vrazhnov Denis , Shkurinov Alexander , Zasedatel Viacheslav , Kistenev Yury
Published: December 2024

Exhaled air contains volatile molecular compounds of endogenous origin, being products of current metabolic pathways. It can be used for medical express diagnostics through control of these compounds in the patient’s breath using molecular absorption spectroscopy. The fundamental problem in this field is that the composition of exhaled air or other gas mixtures of natural origin is unknown, and content analysis of such spectra by conventional iterative methods is unpredictable. Machine learning methods enable the establishment of latent dependencies in spectral data and the conducting of their qualitative and quantitative analysis. This review is devoted to the most effective machine learning methods of exhaled air sample absorption spectra qualitative and content analysis. The focus is on interpretable machine learning methods, which are important for reliable medical diagnosis. Also, the steps additional to the standard machine learning pipeline and important for medical decision support are discussed.
Functional Near-Infrared Spectroscopy Analysis of Cerebral Physiological Changes in Response to Atmospheric Gas Concentrations
Authors: Park Chan-Sol , Kim Mu-Jin , Kim Dong-Hyun , Lee Yeong-Bae , Kang Chang-Ki
Published: December 2024

Compared with other organs in the body, the human brain is extremely sensitive to changes in O2 and CO2 levels. This study applied functional near-infrared spectroscopy (fNIRS) to analyze the changes in cerebral oxygen saturation (COS) and hemoglobin (Hb) concentrations in response to various atmospheric gas concentrations and investigate their effects on brain function. Twenty-nine adults were exposed to four gas conditions, namely atmospheric concentration (C1), high O2 concentration (C2), high CO2 concentration (C3), and high O2 and CO2 concentrations (C4). Changes in COS and Hb concentrations were measured using fNIRS, whereas heart rate (HR) and percutaneous oxygen saturation (SpO2) were measured using a patient monitor. COS, oxy-Hb (HbO), and total-Hb (HbT) increased progressively from C1 to C4, whereas deoxy-Hb (HbR) exhibited a decreasing trend. Moreover, the COS and Hb concentrations were more strongly influenced by high CO2 levels than by high O2 levels. High O2 concentrations increased the blood O2 saturation, whereas high CO2 concentrations increased blood flow as a physiological response, enhancing O2 delivery to the brain. Additionally, HR and SpO2 increased at high CO2 concentrations. However, at high O2 concentrations providing a sufficient O2 supply, SpO2 increased while HR decreased. Therefore, adjusting the concentrations of CO2 and O2 may improve cerebral blood flow and change brain function, supporting cerebrovascular health and preventing related diseases.
Rapid and Non-Invasive Determination of Iodine Value by Magnetic Resonance Relaxometry in Commercial Edible Oils
Authors: Remiro Víctor , Romero-de-Ávila María Dolores , Segura José , Cambero María Isabel , Fernández-Valle María Encarnación , Castejón David
Published: December 2024

This study presents a fast, non-invasive method to determine the iodine value (IV) of edible oils using Time Domain Nuclear Magnetic Resonance (TD-NMR) and Magnetic Resonance Imaging (MRI) techniques. The IV, which quantifies the degree of unsaturation in fats and oils, is a key parameter in assessing oil quality and detecting potential adulteration. Different edible oils were used in this study (sunflower, soy, olive, sesame, and linseed). Statistically significant regression models (R2 > 0.92) were established between the IV derived from NMR spectra and the longitudinal (T1) and transverse (T2) relaxation times of the oils, which were obtained from MRI and TD-NMR analyses. The regression models obtained allow for the prediction of the IV from the T1 and T2 relaxation times across a range that includes predominantly mono- and polyunsaturated edible vegetable oils. The TD-NMR approach stands out for its speed (<2 min), lack of sample preparation (including direct analysis within the commercial packaging), and reproducibility, with a variability of only 0.62%. Meanwhile, the MRI technique allows for the simultaneous evaluation of multiple samples in a single acquisition. Together, these features make TD-NMR and MRI effective tools for the rapid and reliable analysis of the IV in edible oils.
Localized Vector Optical Nondiffracting Subcycle Pulses
Authors: Laurinavičius Klemensas , Orlov Sergej
Published: December 2024

Structured light is essential in various fields such as imaging, communications, computing, laser microprocessing, and ultrafast and nonlinear optics. The structuring of light can occur in terms of space, amplitude, phase, polarization, time, frequency, and duration. One of the intriguing properties that can be obtained is resistance to the diffractive spread and dispersive broadening of the pulsed beams. This happens when temporal properties such as frequency are coupled with spatial properties like angles of propagation of plane-wave components. In this case, pulsed light beams exhibit characteristics similar to optical bullets, resisting both diffraction and material dispersion. This study questions whether free-space optical bullets that possess nondiffracting and nondispersive properties are possible with subcycle durations. We report on the possibility to create nondiffracting and nondispersing localized subcycle pulsed beams and their complex polarization topologies when controlling the group velocity of these light structures.
A Lifestyle-Based Perspective on the Mobility Choices and Preferences of Urban Travelers
Authors: Chatziathanasiou Maria , Botzoris George , Morfoulaki Maria , Kotoula Kornilia-Maria
Published: December 2024

This study investigates how lifestyle factors influence mobility choices within the metropolitan area of Thessaloniki, which is the second largest city in Greece. The primary objective is to understand the interplay between lifestyle attitudes and preferences for sustainable mobility options. This research utilizes data from a comprehensive survey conducted among Thessaloniki’s inhabitants, identifying four distinct attitudinal clusters shaped by lifestyle characteristics and general attitudes toward recycling, energy conservation, social distancing, and other factors. A two-step clustering approach combining hierarchical and k-means methods as well as Chi-square and Kruskal–Wallis tests were employed to investigate whether life attitudes are correlated with revealed and stated mode choices as well as beliefs, perceptions, and feelings related to the current and future public transport systems and micromobility options in the metropolitan area of Thessaloniki. The findings reveal significant variations in mobility choices across the identified lifestyle segments with environmentally conscious segments showing a higher propensity for sustainable modes of transport. Additionally, differences are observed in perceptions and intentions regarding micromobility and the future mass transit system within the region, suggesting that when introducing a new metro system that is expected to promote a shift toward public transport, segment-specific approaches are necessary for raising awareness and increasing trust to the new mode.
Hybrid Multi-Strategy Improved Butterfly Optimization Algorithm
Authors: Cao Panpan , Huang Qingjiu
Published: December 2024

To address the issues of poor population diversity, low accuracy, and susceptibility to local optima in the Butterfly Optimization Algorithm (BOA), an Improved Butterfly Optimization Algorithm with multiple strategies (IBOA) is proposed. The algorithm employs SPM mapping and reverse learning methods to initialize the population, enhancing its diversity; utilizes Lévy flight and trigonometric search strategies to update individual positions during global and local search phases, respectively, expanding the search scope of the algorithm and preventing it from falling into local optima; and finally, it introduces a simulated annealing mechanism to accept worse solutions with a certain probability, enriching the diversity of solutions during the optimization process. Simulation experimental results comparing the IBOA with Particle Swarm Optimization, BOA, and three other improved BOA algorithms on ten benchmark functions demonstrate that the IBOA has improved convergence speed and search accuracy.
VirtualFilter: A High-Performance Multimodal 3D Object Detection Method with Semantic Filtering
Authors: Qu Mingcheng , Deng Ganlin
Published: December 2024

Three-dimensional object detection is a key task in the field of autonomous driving that is aimed at identifying the position and category of objects in the scene. Due to the 3D nature of data generated by LiDAR, most models use it as input data for detection. However, the low scanning resolution of LiDAR for distant objects has inherent limitations to the method, and multimodal fusion 3D object detection methods have attracted widespread attention, mostly using both LiDAR and camera data as inputs for detection. Certainly, multimodal methods can also lead to many problems, the two main ones being the incomplete utilization of camera features and rough fusion methods. In this study, we proposed a novel multimodal 3D object detection method named VirtualFilter, which uses 3D point clouds and 2D images as inputs. In order to better utilize camera features, VirtualFilter utilizes the image semantic segmentation model to generate image semantic features and uses the semantic information to filter the virtual point cloud data during the virtual point cloud generation process to enhance the data accuracy of the virtual cloud. In addition, VirtualFilter utilizes a better RoI feature fusion strategy named 3D-DGAF (3D Distance-based Grid Attentional Fusion), which employs a attention mechanism based on distance gridding to better fuse the RoI features of the original and virtual point clouds. The experimental results on the authoritative autonomous driving dataset KITTI show that this multimodal 3D object detection method outperforms the baseline method in several evaluation metrics.
Research on Fault Diagnosis Method of Reciprocating Compressor Based on RSSD and Optimized Parameter RCMDE
Authors: Lyu Fengxia , Ding Xueping , Li Qianqian , Chen Suzhen , Zhang Siyi , Huang Xinyue , Huang Wenqing
Published: December 2024

As for the fault diagnosis process of a reciprocating compressor, vibration signals are often non-stationary, nonlinear, and multi-coupled, which makes it difficult to conduct effective fault information extraction. In this paper, a method based on optimized resonance-based sparse signal decomposition (RSSD) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The quality factors in RSSD are optimized by atom search optimization (ASO) primarily, then the optimal quality factors are applied to the RSSD of reciprocating compressor fault signals. The noise interference in the original vibration signal can be effectively distinguished from the low resonance component after decomposition. The genetic algorithm (GA) is employed to optimize the core parameters of RCMDE. Finally, the RCMDE of the low-resonance component is extracted as the eigenvalue for pattern recognition. The experimental study illustrates that the spring failure, valve wear, and normal valve conditions of reciprocating compressors can be effectively distinguished by the proposed method.
Two-Level Supervised Network for Small Ship Target Detection in Shallow Thin Cloud-Covered Optical Satellite Images
Authors: Liu Fangjian , Zhang Fengyi , Wang Mi , Xu Qizhi
Published: December 2024

Ship detection under cloudy and foggy conditions is a significant challenge in remote sensing satellite applications, as cloud cover often reduces contrast between targets and backgrounds. Additionally, ships are small and affected by noise, making them difficult to detect. This paper proposes a Cloud Removal and Target Detection (CRTD) network to detect small ships in images with thin cloud cover. The process begins with a Thin Cloud Removal (TCR) module for image preprocessing. The preprocessed data are then fed into a Small Target Detection (STD) module. To improve target–background contrast, we introduce a Target Enhancement module. The TCR and STD modules are integrated through a dual-stage supervision network, which hierarchically processes the detection task to enhance data quality, minimizing the impact of thin clouds. Experiments on the GaoFen-4 satellite dataset show that the proposed method outperforms existing detectors, achieving an average precision (AP) of 88.9%.
Generative Adversarial Network-Based Distortion Reduction Adapted to Peak Signal-to-Noise Ratio Parameters in VVC
Authors: Deng Weihao , Yang Zhenglong
Published: December 2024

In order to address the issues of image quality degradation and distortion that arise in the context of video transmission coding and decoding, a method based on an enhanced version of CycleGAN is put forth. The lightweight attention module is integrated into the residual block of the generator module structure, thereby facilitating the extraction of image details and motion compensation. Furthermore, the perceptual function LPIPS loss is increased to align the image restoration effect more closely with human perception. Additionally, the network training method is modified, and the original image is divided into 128 × 128 small blocks for training, thus enhancing the network’s accuracy in restoring details. The experimental results demonstrate that the algorithm attains an average PSNR value of 30.1147 on the publicly accessible YUV sequence dataset, YUV Trace Dataset, which is a 9.02% enhancement compared to the original network. Additionally, the LPIPS value reaches 0.2639, representing a 10.42% reduction, and effectively addresses the issue of image quality deterioration during transmission.