bluuebunny/crossref_metadata_2025 huggingface dataset:
Cysteine Rich Intestinal Protein 2 is a copper-responsive regulator of skeletal muscle differentiation and metal homeostasis
Authors: Verdejo-Torres Odette , Klein David C. , Novoa-Aponte Lorena , Carrazco-Carrillo Jaime , Bonilla-Pinto Denzel , Rivera Antonio , Bakhshian Arpie , Fitisemanu Fa’alataitaua M. , Jiménez-González Martha L. , Flinn Lyra , Pezacki Aidan T. , Lanzirotti Antonio , Ortiz Frade Luis Antonio , Chang Christopher J. , Navea Juan G. , Blaby-Haas Crysten E. , Hainer Sarah J. , Padilla-Benavides Teresita
Published: December 2024

Copper (Cu) is essential for respiration, neurotransmitter synthesis, oxidative stress response, and transcription regulation, with imbalances leading to neurological, cognitive, and muscular disorders. Here we show the role of a novel Cu-binding protein (Cu-BP) in mammalian transcriptional regulation, specifically on skeletal muscle differentiation using murine primary myoblasts. Utilizing synchrotron X-ray fluorescence-mass spectrometry, we identified murine cysteine-rich intestinal protein 2 (mCrip2) as a key Cu-BP abundant in both nuclear and cytosolic fractions. mCrip2 binds two to four Cu+ ions with high affinity and presents limited redox potential. CRISPR/Cas9-mediated deletion of mCrip2 impaired myogenesis, likely due to Cu accumulation in cells. CUT&RUN and transcriptome analyses revealed its association with gene promoters, including MyoD1 and metallothioneins, suggesting a novel Cu-responsive regulatory role for mCrip2. Our work describes the significance of mCrip2 in skeletal muscle differentiation and metal homeostasis, expanding understanding of the Cu-network in myoblasts.

Copper (Cu) is essential for various cellular processes, including respiration and stress response, but imbalances can cause serious health issues. This study reveals a new Cu-binding protein (Cu-BP) involved in muscle development in primary myoblasts. Using unbiased metalloproteomic techniques and high throughput sequencing, we identified mCrip2 as a key Cu-BP found in cell nuclei and cytoplasm. mCrip2 binds up to four Cu+ ions and has a limited redox potential. Deleting mCrip2 using CRISPR/Cas9 disrupted muscle formation due to Cu accumulation. Further analyses showed that mCrip2 regulates the expression of genes like MyoD1, essential for muscle differentiation, and metallothioneins in response to copper supplementation. This research highlights the importance of mCrip2 in muscle development and metal homeostasis, providing new insights into the Cu-network in cells.
Uptake of COVID-19 vaccine and associated factors among Health Care Workers at Queen Elizabeth Central Hospital in Malawi: A cross-section study
Authors: Chikhoza Angella Joseph , Ng’ambi Wingston , Nyondo-Mipando Alinane Linda
Published: December 2024

Globally, the introduction of the Coronavirus Disease of 2019 (COVID-19) vaccine within one year of the pandemic brought doubts to the general population including health professionals. Even though Health Care Workers (HCWs) are at a high risk of contracting and transmitting the coronavirus due to their work, their COVID-19 vaccine uptake is unknown. This study aimed to determine the uptake of the COVID-19 vaccine and identify factors associated with uptake among HCWs at Queen Elizabeth Central Hospital (QECH) in Blantyre, Malawi. We conducted a quantitative cross-sectional study at QECH. HCWs over 18 years, and with at least one year working experience at QECH were recruited using a simple random sampling technique between December 2021 and February 2022. Data were collected on sociodemographic characteristics, medical history, COVID-19 and COVID-19 vaccine perspectives. The study was informed by Behavioral and Social Drivers of COVID-19 Vaccination framework. We computed vaccine uptake as number of HCWs fully vaccinated divided by total number of participants recruited in the study. Bivariate and multivariable logistic regression models were used to identify factors associated with vaccine uptake. Of the 273 HCWs enrolled into the study 71% were fully vaccinated. Gender (Adjusted Odds Ratio (AOR) = 0.54, 95% CI: 0.30–0.96), ownership of medical insurance schemes (AOR = 2.90, 95% CI: 1.36–6.18) and history of vaccine refusal (AOR = 0.29, 95% CI: 0.12–0.70) were significantly related to vaccine uptake. Age and work experience were statistically significant. The level of education, the income of HCWs and occupation did not determine whether HCWs got vaccinated against COVID-19. There was high vaccine uptake among HCWs at QECH. Some risk factors for severe COVID-19 such as advancing in age and work experience are persuasive to COVID-19 vaccination. We recommend intensified COVID-19 vaccination campaigns for subgroups such as young adults and female HCWs.
Trends and drivers of hypoxic thickness and volume in the northern Gulf of Mexico: 1985–2018
Authors: Matli Venkata Rohith Reddy , Obenour Daniel
Published: December 2024

Hypoxia is a major environmental issue plaguing the commercially and ecologically important coastal waters of the northern Gulf of Mexico. Several modeling studies have explored this phenomenon, but primarily focus on the areal extent of the mid-summer hypoxic zone. Research into the variability and drivers of hypoxic volume and thickness is also important in evaluating the seasonal progression of hypoxia and its impact on coastal resources. In this study, we compile data from multiple monitoring programs and develop a geospatial model capable of estimating hypoxic thickness and volume across the summer season. We adopt a space-time geostatistical framework and introduce a rank-based inverse normal transformation to simulate more realistic distributions of hypoxic layer thickness. Our findings indicate that, on average, there is a seasonal lag in peak hypoxic volume and thickness compared to hypoxic area. We assess long-term trends in different hypoxia metrics (area, thickness, and volume), and while most metrics did not exhibit significant trends, mid-summer hypoxic thickness is found to have increased at a rate of 5.9 cm/year (p<0.05) over the past three decades. In addition, spring nitrogen load is found to be the major driver of all hypoxia metrics, when considered along with other riverine inputs and meteorological factors in multiple regression models. Hypoxic volume, which was also often influenced by east-west wind velocities, was found to be more predictable than hypoxic thickness.
How does company misconduct affect company survival risk?—evidence from China
Authors: Lu Ling
Published: December 2024

Based on the data of China’s listed companies from 2000 to 2022, this study investigates how company misconduct affect company survival risk through survival analysis. The research results show that company misconduct significantly increases company survival risk. After considering endogeneity issues and conducting robustness tests, this conclusion still holds. Mechanism analysis reveals that company misconduct significantly increases enterprise survival risk by reducing investor confidence and increasing corporate financing constraints. Further analysis considering company and regional heterogeneity, which shows that non-state-owned, small-scale, low equity concentration, and eastern region company face more severe survival risk after misconduct. The findings extend the research on the influencing factor of company survival, and provide new empirical evidence for revealing how corporate misconduct affect company survival risk.
An improved sample selection framework for learning with noisy labels
Authors: Zhang Qian , Zhu Yi , Yang Ming , Jin Ge , Zhu Yingwen , Lu Yanjun , Zou Yu , Chen Qiu
Published: December 2024

Deep neural networks have powerful memory capabilities, yet they frequently suffer from overfitting to noisy labels, leading to a decline in classification and generalization performance. To address this issue, sample selection methods that filter out potentially clean labels have been proposed. However, there is a significant gap in size between the filtered, possibly clean subset and the unlabeled subset, which becomes particularly pronounced at high-noise rates. Consequently, this results in underutilizing label-free samples in sample selection methods, leaving room for performance improvement. This study introduces an enhanced sample selection framework with an oversampling strategy (SOS) to overcome this limitation. This framework leverages the valuable information contained in label-free instances to enhance model performance by combining an SOS with state-of-the-art sample selection methods. We validate the effectiveness of SOS through extensive experiments conducted on both synthetic noisy datasets and real-world datasets such as CIFAR, WebVision, and Clothing1M. The source code for SOS will be made available at https://github.com/LanXiaoPang613/SOS.
The tradeoff of solitude? Restoration and relatedness across shades of solitude
Authors: Ross Morgan Quinn , Campbell Scott W.
Published: December 2024

Social interaction and solitude entail tradeoffs. Communicate Bond Belong (CBB) theory holds that social interaction can foster relatedness with others at the cost of social energy, whereas solitude can restore social energy at the cost of relatedness. The current study empirically tests this tradeoff of solitude and its implications for well-being by investigating different degrees of solitude. Less complete degrees of solitude (e.g., no interaction with others) were associated with more relatedness and restoration than more complete degrees of solitude (e.g., no interaction, no potential for it, and no engagement with media), speaking against a tradeoff. Solitude was less detrimental for well-being among individuals who perceived it to be associated with higher restoration and relatedness. Yet, this finding was independent of social energy expenditure, challenging CBB theory. Future work should consider motivations for solitude and longitudinal approaches.
SCRMshaw: Supervised cis-regulatory module prediction for insect genomes
Authors: Asma Hasiba , Liu Luna , Halfon Marc S.
Published: December 2024

As the number of sequenced insect genomes continues to grow, there is a pressing need for rapid and accurate annotation of their regulatory component. SCRMshaw is a computational tool designed to predict cis-regulatory modules (“enhancers”) in the genomes of various insect species. A key advantage of SCRMshaw is its accessibility. It requires minimal resources—just a genome sequence and training data from known Drosophila regulatory sequences, which are readily available for download. Even users with modest computational skills can run SCRMshaw on a desktop computer for basic applications, although a high-performance computing cluster is recommended for optimal results. SCRMshaw can be tailored to specific needs: users can employ a single set of training data to predict enhancers associated with a particular gene expression pattern, or utilize multiple sets to provide a first-pass regulatory annotation for a newly-sequenced genome. This protocol provides an extensive update to the previously published SCRMshaw protocol and aligns with the methods used in a recent annotation of over 30 insect regulatory genomes. It includes the most recent modifications to the SCRMshaw protocol and details an end-to-end pipeline that begins with a sequenced genome and ends with a fully-annotated regulatory genome. Relevant scripts are available via GitHub, and a living protocol that will be updated as necessary is linked to this article at protocols.io.
Design analysis and performance enhancement of a 2-element MIMO skin-implantable antenna for IoT-based health monitoring devices
Authors: Gupta Anupma , Aljaidi Mohammad , Bansal Shonak , Al Mamlook Rabia Emhamed , Kumar Vipan , Aljohani Abeer , Aljohani Saad , Singla Manish Kumar
Published: December 2024

Two two-element slotted patch multiple-input multiple-output (MIMO) antenna with coplanar waveguide (CPW) feed is proposed for deployment in implantable medical devices. Implantable devices are compact and demand high-gain antennae with unidirectional radiation patterns. Regarding compactness, the antenna has a size of 16 × 6×0.25 mm3 for the operating frequency of 2.45 GHz ISM band. Miniaturized antenna geometry is attained using the slots in the radiator and with the coplanar waveguide feed. An element MIMO configuration is used for establishing a reliable communication link. The two radiators maintain a connected ground topology with a minimum edge-to-edge spacing of 7.7 mm. Mutual coupling of -29 dB and operating frequency spectrum of 1300 MHz is attained at the center cut off frequency. Unidirectional power pattern and high gain of 2.3 dB is achieved. The proposed MIMO structure is suitable for mitigating multipath fading effect and realizing higher spectral efficiency in short range communication. The in-tissue measurement results for the scattering parameters and radiation characteristics are done by placing the antenna in a pork loin. Specific absorption rate (SAR) analysis is performed to confirm the user’s safety from nearfield EM waves. Antenna has safe SAR value of 0.798 W/kg for 1-g of average tissue for the power of 1-mW. The low envelope correlation coefficient of 0.035 depicts the excellent diversity performance for MIMO operation.
Do we still need a canary in the coal mine for laboratory animal facilities? A systematic review of environmental health monitoring versus soiled bedding sentinels
Authors: LaFollette Megan R. , Clement Caroline S. , Luchins Kerith R. , Manuel Christopher A. , Foley Patricia L. , Hanson Wai H. , Pettan-Brewer Christina , Winn Caroline B. , Garner Joseph P.
Published: December 2024

Introduction

Despite increasing evidence that Environmental Health Monitoring (EHM) is an effective method to perform rodent colony health surveillance, promotes the 3Rs as a Replacement, is comparable or reduces cost, and demonstrates labor benefits, many research institutions continue to use live Soiled Bedding Sentinels (SBS). Some veterinarians and others responsible for rodent colony health monitoring remain cautious of the evidence supporting this new technology. Therefore, our objective was to perform a formal systematic review to identify, summarize, and evaluate the research on the efficacy of EHM as compared to SBS. This information is essential to establishing recommendations for rodent health monitoring programs.

Methods

We systematically searched and evaluated all articles comparing EHM to SBS identified from PubMed, Web of Science, and CAB abstracts initially on November 12, 2021 with an update on Oct 15, 2023. Our inclusion criteria included publication in a peer-reviewed journal and collection of empirical data on rodent health monitoring alternatives to soiled bedding sentinels. Outcome data was extracted and analyzed via logistic regression and secondary descriptive statistics. Due to the nature of the included studies, no risk of bias assessment was performed. No specific funding was received for this review.

Results

Forty-two peer-reviewed articles passed inclusion criteria for analysis. The design of studies varied substantially but included publications investigating exhaust dust testing (n = 27), sentinel-free soiled bedding (n = 8), and direct colony sampling (n = 24). Based on both logistical regression and descriptive criteria, all types of EHM appear to be superior to soiled bedding sentinels at detecting pathogens, regardless of their taxonomic classification.

Conclusion

Based on these findings, we conclude there is a strong evidence base supporting the replacement of SBS with EHM. Looking forward, we encourage continued research on the detection of existing and emerging pathogens with these technologies and development of best practices for routine rodent health monitoring programs.
The burden of unexpected costs in medical school
Authors: Ball Madeleine , Lam LeAnn , Tigue Megan , Herzberg Simone , Finck Luke
Published: December 2024

Background

The cost of medical school continues to climb. What has yet to be well-understood are the so-called “unexpected costs” of medical school that, while not explicitly required, are considered paramount to success. This study aims to identify, quantify, and analyze the impacts of these costs of medical school and offer suggestions in alleviating these burdens.

Methods

Medical students across the United States were administered a questionnaire inquiring about the unexpected costs of medical school including test prep materials, clinical supplies, student fees, and the impact of these costs on mental and financial health. In this multi-institutional, cross-sectional survey study, outcomes included total cost, perception of expected vs. actual cost, and impact on well-being.

Results

From January to June 2022, 499 survey responses were collected. The average total additional costs were $4,937, with 83% of respondents stating they spent more during medical school than expected. 51% reported their institutions’ cost of attendance did not accurately predict expenses. These costs were a financial constraint for 68% of students, with a significant increase in constraint for first-generation college students (89% vs 65%, p = 0.02). Financial concerns impacted 65% of students’ mental health and well-being during their medical career, with a significantly increased impact on first-generation college students (85% vs 62%, p = 0.045).

Conclusions

Most students believed the total cost of medical school was significantly more than expected, serving as a source of stress and negatively impacting their mental health. The financial constraints and impact on mental health and well-being were most pronounced for first-generation college students. This study illuminates the importance of improving communication regarding costs outside of tuition and providing support and advocacy to alleviate those costs. Future investigation should further examine how other demographics are impacted by the burden of unexpected costs in medical school.
Effectiveness of interventions for preventing road traffic injuries: A systematic review in low-, middle- and high-income countries
Authors: Akbari Maryam , Heydari Seyed Taghi , Razzaghi Alireza , Vali Mohebat , Tabrizi Reza , Bagheri Lankarani Kamran
Published: December 2024

Background

Road traffic collisions (RTCs) are the primary cause of death, which usually occur during the most crucial years of life, resulting in significant damage to health, society, and the economy. A wide variety of strategies and policies have been implemented around the world to minimize injuries and fatalities resulting from RTCs. This study aimed to systematically evaluate the effectiveness of interventions to reduce road traffic injuries (RTIs) in low-, middle-, and high-income countries.

Methods

The researchers looked for articles in many databases (PubMed, Web of Science, Google Scholar, Scopus, Embase, PsycInfo, OpenGrey, EconLit, IMEMR, AIM, Cochrane Injuries Group’s specialized register, Transport Research International Documentation (TRID), Transportation Research Information Services (TRIS) Database and the OECD’s Joint Transport Research Centre’s International Transport Research Documentation (ITRD)) about ways to reduce RTIs and included articles published up to December 2023. The study area did not matter; only RTI reduction methods were considered. Two people checked the articles to ensure being relevant and qualified and summarized what they found in the articles.

Results

A total of 852 articles were included in this systematic review. Most interventions were related to legislation (26.4%) and enforcement (17.0%), and the minor interventions were related to social marketing (4.9%) and traffic user safety (2.2%). Regarding income level (based on the latest classification of the World Bank—2020), more than half of the interventions (83.7%) took place in developed and high-income countries. Regarding intervention types, legislative and road safety interventions effectively reduced road traffic crashes by 26% and 16.7%, respectively. The results indicated that interventions in high-income countries were more likely to minimize RTCs than other countries. However, this difference was not statistically significant (p-value = 0.982). Most effective interventions (36.1%) were reported during the Decade of Action for Road Safety (2011–2020).

Conclusion

Current road safety efforts prioritize changing how people behave on the roads (training, laws, enforcement) over making the roads safer. Focusing on fixing the entire system rather than blaming drivers ("system repair") is necessary for a complete picture.
Machine-learning-based identification of patients with IgA nephropathy using a computerized medical billing database
Authors: Tsunoda Ryoya , Kume Keitaro , Kagawa Rina , Sanuki Masaru , Kitagawa Hiroyuki , Mase Kaori , Yamagata Kunihiro
Published: December 2024

The billing database of the universal healthcare system in Japan potentially includes large-cohort data of patients with immunoglobulin A nephropathy, diagnosis codes aimed at billing should not be directly used for clinical research because of the risk of misdiagnosis. To solve this problem, we aimed to develop a novel method for identifying patients with immunoglobulin A nephropathy from billing data using machine learning. The medical records and bills of 3,743 patients who consulted nephrologists at a single center were extracted. Patients were labeled to have been diagnosed with immunoglobulin A nephropathy through a review of medical records. A manual analysis of the diagnostic accuracy and machine learning was performed. For machine learning, the datasets were preprocessed in three patterns and assigned to the XGBoost program using five-fold cross-validation. Of all the participants, 437 were labeled as having been diagnosed with immunoglobulin A nephropathy. Bill codes for immunoglobulin A nephropathy were provided to approximately half of them. The manually created criteria consisting of the recommended examinations and treatments in the Japanese guidelines for immunoglobulin A nephropathy showed both specificity and sensitivity < 0.8. In contrast, with the receiver operating characteristic curve analysis, the machine learning process yielded area under the curve values over 0.9 with preprocessing from the clinical viewpoint. Applying machine learning technology to a dataset preprocessed from a clinical viewpoint achieved a high performance in detecting patients with immunoglobulin A nephropathy. This methodology contributes to the construction of a disease-specific cohort using big bill data.
Study of shear resistance and anisotropy of layered shales
Authors: Gao Min , Gong Bin , Liang Zhengzhao , Jia Shanpo , Feng Xianhui
Published: December 2024

Characterizing anisotropy remains challenging in rock mechanics. Particularly, the strengths and failure patterns of layered shales under shear load are significantly anisotropic mainly because of the bedding planes. Meanwhile, understanding the creation and propagation of shear fractures is critical for drilling, mining, tunnelling, exploitation of shale gas, etc. In this study, the shear resistance of layered shales is comprehensively investigated based on the direct shear tests numerically. The results show that the shear parameters are greatly affected by the anisotropy induced by the normal stress and orientation of bedding planes; the shear strength, cohesion and internal friction angle generally increase with the growth of bedding plane orientation. Furthermore, three shear failure patterns are summarized, i.e., (1) the shear failure along bedding planes; (2) the shear failure crossing bedding planes; (3) the combination of tensile failure along bedding planes and shear failure crossing bedding planes. Besides, the empirical fitting formula characterizing the shear strength of layered rocks under triaxial compression is provided, and the modified Mohr-Coulomb criterion reflecting rock anisotropy is proposed.
Comparative study on corrosion characteristics of conductive concrete in red soil environment
Authors: Lin Shan , Tian Xu , Pei Feng , Yang Pinghao , Cheng Hongbo
Published: December 2024

In order to solve the corrosion problem of grounding materials in highly corrosive red soil environments, conductive concrete was proposed as a new type of grounding material. The corrosion resistance of conductive concrete was tested and compared to select a suitable preparation scheme with excellent corrosion resistance. A series of conductive concrete samples were made using different conductive materials such as graphite, stainless steel fiber (SSF), and ordinary silicate concrete. Common grounding metals include Q235 steel and galvanized steel, embedded in red soil, conventional concrete, and conductive concrete. The open circuit potential, dynamic potential polarization, and electrochemical impedance spectroscopy of these metals were measured and analyzed. The open-circuit potential of metal electrodes in red soil is lower than that in concrete, and the potential of specimens with conductive phase is higher than that of the ordinary concrete, show that the corrosion sensitivity of metals in conductive concrete is greatly reduced, the corrosion potential is the lowest and the corrosion current is the highest in red soil, the capacitance arc radius in red soil is very small, indicating poor corrosion resistance of grounding metals in a red soil environment. All these indexs indicate that using conductive concrete as grounding material can effectively slow down the corrosion of grounding materials in red soil. Compared with stainless steel based conductive concrete, graphite based conductive concrete provides better protection for the grounding metal wrapped around it. As the content of conductive phase materials increases, the corrosion tendency and corrosion rate of conductive concrete decrease. Compared with Q235 carbon steel, galvanized steel exhibits excellent corrosion resistance in conductive concrete. Therefore, it is recommended to use galvanized steel conductive concrete as the grounding material for power systems in red soil environments.
Association between quantitative flow ratio and clinical outcomes in multivessel disease STEMI patients with diabetes mellitus
Authors: Xian Huimin , Luo Xing , Liu Yanzong , Guo Bingchen , Wu JianJun , Yang Fan , Guo Yiyuan , Zhang Ruoxi
Published: December 2024

Background

Among patients with multivessel disease and ST-elevation myocardial infarction (MVD-STEMI), complete revascularization (CR) has been shown with improved outcomes. However, it is controversial whether diabetes mellitus (DM) status affects the outcomes. Quantitative flow ratio (QFR), as a newer non-invasive tool for identifying functional coronary stenosis and determining the presence of functional CR (FCR), may open up a new perspective for studying the above issues. The aim of this retrospective study was to investigate an association between QFR-based FCR and clinical outcomes in MVD-STEMI patients under DM status.

Methods

A total of 623 patients were included in the final analysis. The patients were divided into nonDM cohort and DM cohort. Within each cohort, patients were further stratified into functional CR (FCR) layer and functional incomplete revascularization (FIR) layer based on QFR assessment. The primary outcomes were 3-year major adverse cardiovascular events (MACEs), encompassing cardiac death, ischemia-driven revascularization (target vessel and non-target vessel), rehospitalization due to unstable angina pectoris, and non-fatal myocardial infarction.

Results

The incidence of MACEs was significantly lower in the FCR layer than in the FIR layer (12.6% vs 24.0%, log-rank P<0.001). In the nonDM cohort, the incidence of MACEs was also lower in the FCR layer than in the FIR layer (9.8% vs 18.5%, log-rank P = 0.032). Similar situations occurred in the DM cohort (16.1% vs 27.9%, log-rank P = 0.017). In addition, the multivariate Cox analysis showed that rSSQFR (QFR-derived residual SYNTAX score) was significantly associated with the increased risk of MACEs in the nonDM cohort (HR (95% CI) = 1.18 (1.10–1.26), P<0.001) and DM cohort (HR (95% CI) = 1.13 (1.09–1.18), P<0.001). ROC analysis showed adding rSSQFR into the model of clinical risk factors yielded a significant improvement in prediction of MACEs, especially in the DM cohort (AUC (95% CI) = 0.747 (0.675–0.819), P = 0.001) than in the nonDM cohort (AUC (95% CI) = 0.697 (0.602–0.791), P = 0.033). Furthermore, additional multivariate Cox analysis showed that rSSQFR was associated with the increased risk of MACEs in patients with moderate lesions (DS of 50%-89%) after procedure (HR (95% CI) = 1.16 (0.11–1.22), P<0.001).

Conclusions

In patients with MVD-STEMI, the incidence of MACEs was lower in FCR than in FIR, and the decrease was particularly significant in the DM cohort. The association between QFR-derived rSSQFR and MACEs was independent of baseline characteristic differences, and rSSQFR provided higher prognostic predictive ability in DM cohort than in nonDM cohort. Additionally, QFR had the additional utility of identifying moderate residual lesions that require revascularization.
Response of soybean root exudates and related metabolic pathways to low phosphorus stress
Authors: Yao Yubo , Yuan Hongmei , Liu Dandan , Cheng Lili
Published: December 2024

Phosphorus (P) is an essential elemental nutrient required in high abundance for robust soybean growth and development. Low P stress negatively impacts plant physiological and biochemical processes, such as photosynthesis, respiration, and energy transfer. Soybean roots play key roles in plant adaptive responses to P stress and other soil-related environmental stressors. Study the changes in soybean root exudates and differences in related metabolic pathways under low phosphorus stress, analyzing the response mechanism of soybean roots to phosphorus stress from the perspective of root exudates, which provide a theoretical basis for further analyzing the physiological mechanism of phosphorus stress on soybean. In this study, soybean roots were exposed to three phosphate levels: 1 mg/L (P stress), 11 mg/L (P stress) and 31 mg/L (Normal P) for 10 days and 20 days, then root exudates were analyzed via ultra-high-performance liquid chromatography-mass spectrometry to identify effects of P stress on root metabolite profiles and associated metabolic pathways. Our results revealed that with increasing P stress severity and/or duration, soybean roots produced altered types, quantities, and increased numbers of exudate metabolites (DMs in the P1 group were primarily upregulated, whereas those in the P11 group were predominately downregulated) caused by changes in regulation of activities of numerous metabolic pathways. These pathways had functions related to environmental adaptation, energy metabolism, and scavenging of reactive oxygen species and primarily included amino acid, flavonoid, and nicotinate and nicotinamide metabolic pathways and pathways related to isoquinoline alkaloid biosynthesis, sugar catabolism, and phospholipid metabolism. These metabolites and metabolic pathways lay a foundation to support further investigations of physiological mechanisms underlying the soybean root response to P deficiency.
Effects of triple semicircular canal plugging on hearing in patients with Meniere’s disease: A systematic review and meta-analysis
Authors: Zhu Jia quan , Kang Li li , Wen Xiao dong , Xiao Jing , Li Yu jie , Li Rong , Liu Hong jun , Wang Hong juan , Qiao Fu yu , Yang Dongbao , Xiang Bin
Published: December 2024

Introduction

Triple semicircular canal plugging is effective in controlling vertigo in patients with Meniere’s disease, however, whether the rate of causing hearing loss during treatment is still not uniform. This study aimed to evaluate the effects of Triple semicircular canal plugging (TSCP) on hearing in Meniere’s disease (MD) patients.

Methods

Databases Reviewed were PubMed, EMBASE, Scopus, Clinical Trials, Web of Science, Cochrane Library, CNKI, Wanfang, and VIP. The study reported on the duration, follow-up time, hearing loss, and vertigo control outcomes in MD patients evaluated by TSCP. Stata 17 software was used for data analysis and assessing the risk of bias.

Results

This meta-analysis included 367 MD patients from 7 studies. TSCP efficiently alleviated vertigo with a rate of 99% (95% CI: 0.97, 1.00) and had a hearing loss rate of 22% (95% CI: 0.16, 0.28). Subgroup analysis revealed that for hearing loss, the proportion of patients with disease duration more than or less than 12 months was 14% (95% CI: 0.05, 0.26) and 24% (95% CI: 0.19, 0.29), respectively. For vertigo control, the rates were 100% (95% CI: 0.96, 1.00) and 99% (95% CI: 0.97, 1.00), respectively. For hearing loss, the follow-up time of MD patients more than or less than 24 months was 20% (95% CI: 0.07, 0.38) and 23% (95% CI: 0.18, 0.29), respectively. For vertigo control, the rates were 99% (95% CI: 0.95, 1.00) and 99% (95% CI: 0.97, 1.00), respectively. The duration of the disease and follow-up time had no significant impact on hearing loss and vertigo control rates.

Conclusions

TSCP was efficient for vertigo control but with a risk of hearing loss. It could be used as a surgical method for hearing preservation in advanced MD patients.
Classifying forensically important flies using deep learning to support pathologists and rescue teams during forensic investigations
Authors: Gohe Anna Katharina , Kottek Marius Johann , Buettner Ricardo , Penava Pascal
Published: December 2024

Forensic entomology can help estimate the postmortem interval in criminal investigations. In particular, forensically important fly species that can be found on a body and in its environment at various times after death provide valuable information. However, the current method for identifying fly species is labor intensive, expensive, and may become more serious in view of a shortage of specialists. In this paper, we propose the use of computer vision and deep learning to classify adult flies according to three different families, Calliphoridae, Sarcophagidae, Rhiniidae, and their corresponding genera Chrysomya, Lucilia, Sarcophaga, Rhiniinae, and Stomorhina, which can lead to efficient and accurate estimation of time of death, for example, with the use of camera-equipped drones. The development of such a deep learning model for adult flies may be particularly useful in crisis situations, such as natural disasters and wars, when people disappear. In these cases drones can be used for searching large areas. In this study, two models were evaluated using transfer learning with MobileNetV3-Large and VGG19. Both models achieved a very high accuracy of 99.39% and 99.79%. In terms of inference time, the MobileNetV3-Large model was faster with an average time per step of 1.036 seconds than the VGG19 model, which took 2.066 seconds per step. Overall, the results highlight the potential of deep learning models for the classification of fly species in forensic entomology and search and rescue operations.
Investigating the relationship between insulin use and all-cause mortality, breast cancer mortality, and recurrence risk in diabetic patients with breast cancer: A comprehensive systematic review and meta-analysis
Authors: Loktionova Marina V. , Mohammadian Mahdi , Choopani Roya , Kheiri Soleiman , Mohammadian-Hafshejani Abdollah
Published: December 2024

Background

The co-occurrence of breast cancer and diabetes presents complex clinical challenges, as each condition may influence the progression and management of the other, potentially worsening patient outcomes. This study aims to examine the association between insulin use and the risks of all-cause mortality, breast cancer-specific mortality, and recurrence in diabetic patients with breast cancer.

Methods

A systematic review and meta-analysis were conducted using studies identified from multiple databases, including Web of Science, Scopus, PubMed, Cochrane, Google Scholar, and Embase. The meta-analysis approach was used to estimate the relative risk (RR) of the relationship between insulin use and the risks of all-cause mortality, breast cancer-specific mortality, and recurrence in diabetic patients with breast cancer. Heterogeneity among studies was assessed using statistical tests such as the Chi-square test, I2, and forest plots. Meta-regression and sensitivity analyses were performed to explore sources of heterogeneity. The quality of the included studies was assessed using the Newcastle-Ottawa Scale checklist. Data were analyzed using Stata version 17 (Stata Corp, College Station, Texas).

Results

Data from 22 studies conducted between 2002 and 2023, with a total of 159,674 participants, were analyzed. Nineteen studies were rated as high quality, and three as moderate quality. Diabetic patients with breast cancer who received insulin had a 1.65 (95% CI: 1.36–2.02; P < 0.001; I2 = 89.7%) times higher risk of overall mortality compared to those who did not use insulin. Meta-regression revealed that sample size and study quality were significant contributors to heterogeneity (P ≤ 0.10). Furthermore, insulin use was associated with a 1.22 (95% CI: 1.05–1.42; P = 0.009; I2 = 37.9%) times higher risk of breast cancer-specific mortality. For breast cancer recurrence, insulin use was associated with a 1.45 (95% CI: 1.19–1.77; P < 0.001; I2 = 3.4%) times higher risk. Sensitivity analysis confirmed the stability of the results across all outcomes.

Conclusion

This meta-analysis provides strong evidence that insulin use in diabetic patients with breast cancer is associated with increased risks of overall mortality, breast cancer-specific mortality, and recurrence. These findings underscore the need for careful consideration of insulin therapy in this patient population.
Social support and symptoms of antenatal depression among women screened for gestational diabetes mellitus: A cross-sectional study in Northern Vietnam (the VALID II study)
Authors: Nguyen Ai T. , Nguyen Kien Dang , Minh Le Hieu , Nguyen Thanh D. , W. Meyrowitsch Dan , C. Bygbjerg Ib , Søndergaard Jens , Nguyen Hanh T. T. , A. Vinter Christina , S. Linde Ditte , M. Gammeltoft Tine , Rasch Vibeke
Published: December 2024

Objectives

This study from Northern Vietnam aims to assess the association between social support and symptoms of depression among pregnant women screened for gestational diabetes mellitus (GDM).

Methods

A cross-sectional study was conducted among 823 pregnant women in Thai Binh, Vietnam. The women were screened for GDM and structured questionnaire were used to collect data on social support factors, GDM factors, and symptoms of depression. The diagnosis of GDM was based on the 2-hour 75-g OGTT according to WHO 2013 criteria. The Edinburg Postpartum Depression Scale (EPDS) with a cut-off of 10 and the Multidimensional Perceived Social Support Scale (MSPSS) were used to assess depression symptoms and perceived social support, respectively. Logistic regression analysis was conducted to measure the associations between social support, GDM-related factors, and symptoms of depression. The relationship between social support score and symptoms of depression was evaluated using Spearman’s correlation. The strength of the associations were measured by adjusted odds ratios (aOR) with 95% confidence intervals (CI).

Results

The prevalence rates of GDM and symptoms of depression were 22.2% (95%CI: 19.4–25.2) and 23.0% (95%CI: 20.1–26.0), respectively. Women who had moved away from their commune of birth and women who reported another person than their husband to be the primary person to confide in had increased odds of depression (aOR = 1.74; 95%CI:1.19–2.56 and aOR = 2.36; 95%CI:1.48–3.75, respectively). A reported lack of social support was strongly associated with increased odds of depression symptoms among both women with gestational diabetes mellitus (aOR = 6.16, 95% CI:2.35–16.12) and without gestational diabetes mellitus (aOR = 2.81; 95%CI: 1.67–4.75). When analysing the correlation between social support and depression symptoms, a negative correlation was found, with decreasing depression scores as the social support score increased.

Conclusion

The prevalence of symptoms of depression was high in our study, and women in Northern Vietnam who feel well-supported socially are less likely to report symptoms of depression. This finding applies both to women with and without GDM.
Fungal microbiome in gut of systemic lupus erythematosus (SLE)-prone mice (pristane and FCGRIIb deficiency), a possible impact of fungi in lupus
Authors: Cheibchalard Thanya , Leelahavanichkul Asada , Chatthanathon Piraya , Klankeo Piriya , Hirankarn Nattiya , Somboonna Naraporn
Published: December 2024

The gut mycobiota (fungal microbiota) plays a crucial role in the immune system, potentially impacting autoimmune diseases such as systemic lupus erythematosus (SLE). Despite growing interest, data on intestinal fungi in SLE remain limited. This study thereby investigated the human-mimicked (mice) gut mycobiome and quantitative gut mycobiome analyses using universal fungal internal transcribed spacer 2 (ITS2) DNA next generation sequencing and real-time PCR, tracking time-series dynamics from preclinical to established SLE conditions in two SLE-prone mouse models. These models included pristane -induced mice, representing an environmental cause of SLE, and Fc gamma receptor RIIb (FcgRIIb) deficiency mice, representing a genetic factor. Fecal samples and different intestinal sections from mice aged 2–10 months were analyzed, including samples from 4-month-old and 11-month-old mice, which represented preclinical lupus (negative for anti-dsDNA) and established SLE conditions (positive for anti-dsDNA with proteinuria), respectively, alongside age-matched healthy controls. Results showed increased fungal diversity, specific changes in gut fungal species (i.e. increased Candida spp.), and an elevated Basidiomycota-to-Ascomycota (Basidiomycota/Ascomycota) ratio, which correlated with lupus activity in both lupus models. Linear discriminant analysis Effect Size (LEfSe; a possible representative organism) helped identify specific fungal difference between the lupus models. Our findings revealed that active lupus states may elevate gut fungal populations and alter fungal components in both the pristane and genetically susceptible SLE-prone mice, as indicated by mycobiota and quantitative mycobiota analyses. These changes could, in turn, influence disease activity. This research is essential for a deeper understand of the SLE-gut microbiome association, as the gut microbiome comprises both bacterial and fungal symbiosis. Manipulating fungal communities could present a potential therapeutic avenue for influencing disease outcomes in lupus. Further studies are crucial to clarify the direct role of gut fungi in lupus disease progression.
Characteristics of the vertical variation in water quality indicators of aquatic landscapes in urban parks: A case study of Xinxiang, China
Authors: Zhang Yichuan , Qin Wenke , Qiao Lifang
Published: December 2024

The quality of landscape water directly impacts the recreational and leisure experiences of the public. Factors such as water clarity, color, and taste can influence public perception, while contaminants like heavy metals, algae, and microorganisms may pose health risks. Stratified monitoring can reveal variations in the physical, chemical, and biological properties of water at different depths, thereby providing a more comprehensive understanding of water quality and aiding in the identification of pollution sources. This study examined aquatic landscapes at five parks in Xinxiang, China, monitoring thirteen indicators including Water Temperature (WT), Chroma (Ch), Turbidity (Tu), Suspended Solids (SS), Electrical Conductivity (EC), pH, Dissolved Oxygen (DO), Total Nitrogen (TN), Total Phosphorus (TP), Chemical Oxygen Demand (COD), Fe, Zn, and Cu. Utilizing the single-factor evaluation method, the water quality level of each indicator was assessed in accordance with the Water Quality Standard for Scenery and Recreation Area of the People’s Republic of China (GB12941-91). The findings revealed significant vertical variations in the levels of TN, TP, COD, Fe, Zn and Cu of aquatic landscapes at parks, while WT, Ch, Tu, SS, EC, and DO showed no marked differences (P>0.05). The monthly dynamics of the water quality indicators indicated generally consistent trends for WT, Ch, Tu, SS, EC, DO, TN, TP, Zn, and Cu, albeit with varying degrees of fluctuation; however, the trends for EC, pH, COD, and Fe exhibited greater variability. These results offer valuable insights for the environmental protection and management of aquatic landscapes in urban parks. Stratified monitoring can capture the dynamic changes in water quality, assisting managers in developing more effective water quality management strategies.
Inducing programmed cell death trough MazEF system to combat Staphylococcus aureus: A non-antibiotic treatment candidate
Authors: Bakhti Shahriar , Ahmadi Mohammad Hossein , Owlia Parviz
Published: December 2024

The aim of the present study was to evaluate the role of extracellular death factor (EDF) derived from Escherichia coli in the induction of programmed cell death (PCD) in methicillin-resistant and -susceptible Staphylococcus aureus (MRSA and MSSA). The confirmation of bacterial strains as well as the minimum inhibitory concentration (MIC) test were performed according to CLSI, 2022. The extraction and efficacy determination of EDF as well as the CFU assessment were done. The expression of mazE and mazF gens in different conditions was evaluated by Real-time PCR. The likely formation of persister cells from MRSA and MSSA, and the possible synthesis of EDF in old cultures of these pathogens was evaluated, as well. The combination of EDF of two E. coli strains and sub-MIC rifampin reduced the CFUs of MRSA and MSSA strains in mid-logarithmic growth phase while increased the expression of mazF several times more than mazE gene. The expression of these genes in different conditions were unlike. EDF was produced in the old cultures of MRSA and MSSA. The supernatant of E. coli 25922 was more powerful than the clinical strain ones to decrease the CFUs of the MRSA and MSSA. The EDF derived from E. coli in combination with sub-MIC rifampin could induce PCD in MRSA and MSSA through activation of the MazEF system. This phenomenon could be exploited as a non-antibiotic treatment candidate to combat the infections caused by the antibiotic-resistant pathogens. However, more studies should be performed in this regard.
Do errors in the GHQ-12 response options matter?
Authors: Croak Bethany , Bhundia Rupa , Lamb Danielle , Greenberg Neil , Stevelink Sharon A. M. , Trompeter Nora , Wessely Simon , Rubin G. James
Published: December 2024

Background

The twelve item General Health Questionnaire (GHQ-12) is a widely used measure of psychological wellbeing. Because there are seven different sets of response options across the twelve items, there is scope for transcription errors to occur when researchers assemble their study materials. The impact of such errors might be more important if they occur in the first set of response options than if they occur later in the questionnaire, once participants have become aware that options to the right of the GHQ-12 response sets always indicate worse wellbeing.

Aims

To test the impact of introducing errors into the first and eighth set of response options for the GHQ-12 that render those response sets partially illogical.

Methods

We used a double-blind randomised controlled trial, pre-registered with Open Science Framework (osf.io/syhwf). Participants were recruited by a market research company from their existing panel of respondents in Great Britain. Participants were randomly allocated to receive one of three versions of the GHQ-12: a correct version (n = 500), a version with a mistake in the first item (n = 502), or a mistake in the eighth item (n = 502). Mistakes replaced ‘better than usual’ (item one) or ‘more so than usual’ (item eight) with ‘not at all.’

Results

We found no differences between the versions in terms of number of participants with possible poor psychological wellbeing (χ2 = 0.32, df = 2, p = 0.85) or in mean GHQ-12 scores for the three groups (F(2, 1501) = 0.26, p = 0.77).

Conclusions

Small deviations from the standard GHQ-12 wording do not have a substantive impact on results.