bluuebunny/crossref_metadata_2025 huggingface dataset:
Rice mutants, selected under severe drought stress, show reduced stomatal density and improved water use efficiency under restricted water conditions
Authors: Phunthong Chutima , Pitaloka Mutiara K. , Chutteang Cattleya , Ruengphayak Siriphat , Arikit Siwaret , Vanavichit Apichart
Published: April 2024

Introduction

Rice is among the least water-use-efficient crops, and rice plants utilise most of their water uptake for transpirational cooling via stomata. To improve water-use efficiency (WUE) in rice, reducing stomatal density and size could help optimise transpiration and photosynthesis.

Methodology

In this study, we compared two series of purple rice stomata mutants: the Stomatal Model Mutant (SMM) identified by microscopic observation of flag-leaf stomata, and the Drought-selected Model Mutant (DMM) generated through screening under severe water stress. After undergoing two rounds of severe water stress between -60 to -80 Ym, right before the R1–2 reproductive stage, three DMMs were selected based on their rapid recovery rate and % filled-grain percentage.

Result

The three DMMs displayed 618–697 stomatal units per mm2, similar to the SMMs low-density stomata mutant (JHN 8756 (LD)). Furthermore, the four SMMs, three DMMs and the Jao Hom Nin wild type (JHN WT) were treated with two restricted water condition schemes from seedlings to harvest. The total amount of irrigation and precipitation during the experiment was 78.1 L/plant (69.1 mm/plant) for the less restricted water condition (LR) and 47.5 L/plant (42 mm/plant) for the more restricted water condition (MR). Water condition treatments had no effects on stomatal density and stomatal index. In contrast, genotypes and restricted water condition schemes affected plant height, tillers/plant, % filled grains and shoot dry weight (SDW). The three DMMs and the JHN 8756 (LD), the SMM's low-density stomata mutant, displayed greater resilience towards more restricted water conditions than the SMMs and the JHN wild type. Particularly, DMMs were tolerant to more restricted water condition treatments, showing no SDW penalties. Together, the DMMs and the JHN 8756 (LD) displayed higher WUE under these conditions of more restricted water conditions.

Conclusion

A rigorous screening process to distinguish tolerant mutants with a rapid drought recovery rate from severe water stress could pave the way to isolate more mutants with better stomatal functionality and resilience in preparation for imminent climate changes.
LFMNet: a lightweight model for identifying leaf diseases of maize with high similarity
Authors: Hu Jian , Jiang Xinhua , Gao Julin , Yu Xiaofang
Published: April 2024

Maize leaf diseases significantly impact yield and quality. However, recognizing these diseases from images taken in natural environments is challenging due to complex backgrounds and high similarity of disease spots between classes.This study proposes a lightweight multi-level attention fusion network (LFMNet) which can identify maize leaf diseases with high similarity in natural environment. The main components of LFMNet are PMFFM and MAttion blocks, with three key improvements relative to existing essential blocks. First, it improves the adaptability to the change of maize leaf disease scale through the dense connection of partial convolution with different expansion rates and reduces the parameters at the same time. The second improvement is that it replaces a adaptable pooling kernel according to the size of the input feature map on the original PPA, and the convolution layer to reshape to enhance the feature extraction of maize leaves under complex background. The third improvement is that it replaces different pooling kernels to obtain features of different scales based on GMDC and generate feature weighting matrix to enhance important regional features. Experimental results show that the accuracy of the LFMNet model on the test dataset reaches 94.12%, which is better than the existing heavyweight networks, such as ResNet50 and Inception v3, and lightweight networks such as DenseNet 121,MobileNet(V3-large) and ShuffleNet V2. The number of parameters is only 0.88m, which is better than the current mainstream lightweight network. It is also effective to identify the disease types with similar disease spots in leaves.
Advancing the understanding of children’s digital engagement: responsive methodologies and ethical considerations in psychological research
Authors: Kucirkova Natalia , Livingstone Sonia , Radesky Jenny
Published: April 2024

Children’s perspectives and experiences with digital media (digital engagement for short) are becoming difficult to observe and measure in today’s highly multi-faceted, personalized and dynamic media ecosystem. In response, psychologists are developing a host of innovative methods. These may be broadly divided into those which prioritize children’s active participation in research and those which develop techniques for passive observation. This article presents a state-of-the-art review of emerging methodologies to highlight the ethical issues that arise, by drawing on the Belmont principles for ethical research. We identify strengths and weaknesses of both participatory and non-participatory methods and recommend ways for future research to harness the potential of child-centered, responsive, and ethical methods.
Experiences using an online therapist-guided psychotherapy platform (OPTT) in correctional workers with depression, anxiety, and PTSD
Authors: Moghimi Elnaz , Gutierrez Gilmar , Stephenson Callum , Gizzarelli Tessa , Jagayat Jasleen , Holmes Christina , Patel Charmy , Omrani Mohsen , Simpson Alexander Ian Frederic , Alavi Nazanin
Published: April 2024

Introduction

Correctional workers (CWs) are frequently exposed to potentially traumatic events in the workplace, leading to an increased prevalence of mental health concerns. Online psychotherapy can address many of the barriers CWs face when seeking adequate mental health care. Despite their benefits, CWs’ experience using digital mental health interventions is relatively unknown. This information could be valuable in developing enhanced care delivery to improve recruitment, retention, satisfaction, and treatment outcomes.

Methods

This study investigated the experiences of a sample of CWs enrolled in a clinical trial evaluating the efficacy of the Online Psychotherapy Tool (OPTT) in this population. Participants were surveyed and interviewed to capture their opinions and feedback on the program. Survey analysis was conducted through Qualtrics statistical analysis software. The interview transcripts and open-ended survey questions were analyzed using thematic analysis methods in NVivo.

Results

Participants (n=14) were cis-gender, predominantly white, with an average age of 38 years. While most respondents preferred in-person therapy, they also reported the benefits of the online psychotherapy program. Specifically, they expressed positive perceptions of the platform, the quality and interaction of their care provider, and the homework assignments and skills learned. Lack of motivation to complete weekly homework assignments was a frequently cited challenge. Unhelpful aspects of the therapy noted issues with the online format and frustration with certain program elements.

Discussion

Participants expressed a positive outlook on the program, the platform, and treatment outcomes. A preference for in-person therapy was still indicated, demonstrating the need to focus on engagement in digital mental health interventions. In addition, the findings of this study shed light on the factors that can influence help-seeking in this population, including stigma in the work environment, demanding work schedules, workplace perceptions, and previous experiences accessing mental health services.
Differential effects of cannabis constituents on schizophrenia-related psychosis: a rationale for incorporating cannabidiol into a schizophrenia therapeutic regimen
Authors: Johnson Kennadi , Weldon Abby J. , Burmeister Melissa A.
Published: April 2024

Schizophrenia is a serious mental health disorder that confers one of the highest mortality rates of all psychiatric illnesses. Although the disorder’s psychotic symptoms are treatable with conventional antipsychotics, they remain incurable. Moreover, medication adherence is poor, and individuals with schizophrenia choose to self-medicate with illicit substances, including cannabis. It is well-established that the delta-9-tetrahydrocannabinol (delta-9-THC) component of cannabis elicits psychotomimetic effects at high doses; worsens schizophrenia-related psychosis; commonly develops into cannabis use disorder in individuals with schizophrenia; and increases the risk of earlier-onset schizophrenia symptoms in those harboring genetic susceptibility. However, individuals with schizophrenia commonly use cannabis and cannabis derivatives such as cannabidiol (CBD). These products seem to alleviate psychotic symptoms and relieve adverse side effects of antipsychotic medications. Therefore, one notion that has gained traction is the potential utility of cannabis-derived cannabidiol (CBD) as adjunct treatment to reduce schizophrenia-associated psychosis and other symptoms. Currently, preclinical and clinical data remain inconclusive. The present review distinguishes the mechanisms underlying schizophrenia-associated vs. cannabis-induced psychosis; reviews the evidence for delta-9-THC-mediated exacerbation vs. CBD-mediated amelioration of schizophrenia-associated psychosis; and describes potential approaches for incorporating CBD into schizophrenia therapeutic regimen in a safe and efficacious manner.
BERT-based language model for accurate drug adverse event extraction from social media: implementation, evaluation, and contributions to pharmacovigilance practices
Authors: Dong Fan , Guo Wenjing , Liu Jie , Patterson Tucker A. , Hong Huixiao
Published: April 2024

Introduction

Social media platforms serve as a valuable resource for users to share health-related information, aiding in the monitoring of adverse events linked to medications and treatments in drug safety surveillance. However, extracting drug-related adverse events accurately and efficiently from social media poses challenges in both natural language processing research and the pharmacovigilance domain.

Method

Recognizing the lack of detailed implementation and evaluation of Bidirectional Encoder Representations from Transformers (BERT)-based models for drug adverse event extraction on social media, we developed a BERT-based language model tailored to identifying drug adverse events in this context. Our model utilized publicly available labeled adverse event data from the ADE-Corpus-V2. Constructing the BERT-based model involved optimizing key hyperparameters, such as the number of training epochs, batch size, and learning rate. Through ten hold-out evaluations on ADE-Corpus-V2 data and external social media datasets, our model consistently demonstrated high accuracy in drug adverse event detection.

Result

The hold-out evaluations resulted in average F1 scores of 0.8575, 0.9049, and 0.9813 for detecting words of adverse events, words in adverse events, and words not in adverse events, respectively. External validation using human-labeled adverse event tweets data from SMM4H further substantiated the effectiveness of our model, yielding F1 scores 0.8127, 0.8068, and 0.9790 for detecting words of adverse events, words in adverse events, and words not in adverse events, respectively.

Discussion

This study not only showcases the effectiveness of BERT-based language models in accurately identifying drug-related adverse events in the dynamic landscape of social media data, but also addresses the need for the implementation of a comprehensive study design and evaluation. By doing so, we contribute to the advancement of pharmacovigilance practices and methodologies in the context of emerging information sources like social media.
Factors that facilitate consumer uptake of sustainable dietary patterns in Western countries: a scoping review
Authors: Srinivasan Soumya , Galvez Abby , Krieger Rebecca , Sebo Amy , Mckever Maya , Nestico Daniella , Carlsson Liesel , Wegener Jessica , Everitt Tracy
Published: April 2024

Objectives

This scoping review aims to describe factors that facilitate consumer-level transitions to more environmentally sustainable diets.

Methods

Using scoping review methods, four databases were searched for articles published in English examining facilitators to consuming an environmentally sustainable diet and focused on consumers, using data collected in Western countries, and were published between 2012 and 2022. Researchers extracted study characteristics and factors influencing adoption or uptake of sustainable foods or dietary patterns. Using this data, researchers conducted a thematic analysis to determine five main themes describing leverage points (modifiable) for dietary transitions.

Results

Results are reported per PRISMA guidelines: 21 studies were included with data from the U.K., U.S., Australia, and Europe. The results of this review indicate that values, knowledge, marketing, consumer-product relationships, and support networks, along with their respective subthemes, may be central drivers of consumer adoption of sustainable dietary patterns. Consumers are more likely to purchase and consume products which are familiar and appealing and align with their values. Cost, lack of knowledge, and lack of social support act as barriers to dietary change to more sustainable food choices. Income, education, ethnicity, sex, and employment were common individual-level characteristics identified as influential over likelihood of adopting environmentally sustainable dietary patterns. Individual-level characteristics create nuances in both likelihood to adopt, and the experience of barriers to adopting, sustainable dietary patterns.

Conclusion

Knowledge of leverage points and individual-level nuances is useful in informing strategies to facilitate transitions to more sustainable diets.
Improved Brain Storm Optimization Algorithm Based on Flock Decision Mutation Strategy
Authors: Zhao Yanchi , Cheng Jianhua , Cai Jing
Published: April 2024

To tackle the problem of the brain storm optimization (BSO) algorithm’s suboptimal capability for avoiding local optima, which contributes to its inadequate optimization precision, we developed a flock decision mutation approach that substantially enhances the efficacy of the BSO algorithm. Furthermore, to solve the problem of insufficient BSO algorithm population diversity, we introduced a strategy that utilizes the good point set to enhance the initial population’s quality. Simultaneously, we substituted the K-means clustering approach with spectral clustering to improve the clustering accuracy of the algorithm. This work introduced an enhanced version of the brain storm optimization algorithm founded on a flock decision mutation strategy (FDIBSO). The improved algorithm was compared against contemporary leading algorithms through the CEC2018. The experimental section additionally employs the AUV intelligence evaluation as an application case. It addresses the combined weight model under various dimensional settings to substantiate the efficacy of the FDIBSO algorithm further. The findings indicate that FDIBSO surpasses BSO and other enhanced algorithms for addressing intricate optimization challenges.
Research on the Calculation Method of Propeller 1P Loads Based on the Blade Element Momentum Theory
Authors: Yan Wenhui , Tian Xiao , Zhou Junwei , Zhang Kun
Published: April 2024

Aircraft propellers produce relatively large in-plane loads, called propeller 1P loads, during maneuvers such as turning, diving, and lifting, and these loads can negatively affect the flight and control of the aircraft. In order to study the change rule of 1P aerodynamic loads, in this paper, a mathematical model of the propeller 1P aerodynamic loads has been developed based on the blade element momentum theory. This mathematical model was then corrected using the Pitt–Peters incoming flow correction method, the Prandtl tip correction method, and the propeller root flow correction method. Based on this mathematical model, a calculation procedure for the propeller 1P aerodynamic loads was developed using MATLAB software, and the accuracy of the procedure was verified by comparing the results with CFD simulation results. Numerical simulations show that the results calculated based on the proposed mathematical model for the coefficients of thrust, power, bending moment, and the tangential force of the propeller have an error of less than ±6.00% compared to the CFD simulation results. For a small inflow angle, the coefficients of bending moment and tangential force of the whole propeller fluctuate in a small range. But, as the inflow angle increases, the fluctuation range of the aerodynamic characteristic parameters of the propeller increases and the fluctuation becomes more complicated. Through numerical calculations, it has been shown that the mathematical model presented herein is reliable and accurate. In addition, it greatly shortens the calculation time and improves the calculation efficiency. It is expected that the proposed model can provide a certain help for the strength design of the propeller structure and the study of the aerodynamic performance of the whole aircraft.
Bacterial Community Influences the Effects of Lactobacillus acidophilus on Lipid Metabolism, Immune Response, and Antioxidant Capacity in Dogs
Authors: Mao Aipeng , Chen Xiaoli , Zhao Weigang , Nan Weixiao , Huang Yao , Sun Yalong , Zhang Haihua , Xu Chao
Published: April 2024

Lactobacillus acidophilus (L. acidophilus), the most prevalent probiotic, has demonstrated the ability to improve the relative abundance of intestinal microorganisms and boost immunity. However, the underlying mechanisms of these effects remain unclear. This study evaluated body weight, nutrient apparent digestibility, serum indices, and bacterial communities in Chinese rural dogs from a L. acidophilus supplementation group (Lactobacillus acidophilus, n = 6) and a control group (CON, n = 6). The results indicated that L. acidophilus had no significant impact on the body weight and apparent nutrient digestibility of Chinese rural dogs. In comparison with the CON group, L. acidophilus significantly reduced the levels of cholesterol (CHO) and increased the levels of IgA, IFN-α, and T-AOC. Bacterial diversity indices were significantly reduced in the LAC group compared to the CON groups, and MetaStat analysis demonstrated notable distinctions in 14 bacterial genera between the groups. These bacterial genera exhibited correlations with physiological indices such as CHO, IgA, IFN-α, and T-AOC. In conclusion, L. acidophilus can modulate lipid metabolism, immunity, and antioxidant capacity by regulating the relative abundance of specific bacterial communities, which helps dogs to adapt to today’s lifestyle.
Seasonal Hair Glucocorticoid Fluctuations in Wild Mice (Phyllotis darwini) within a Semi-Arid Landscape in North-Central Chile
Authors: Veloso-Frías Joseline , Soto-Gamboa Mauricio , Mastromonaco Gabriela , Acosta-Jamett Gerardo
Published: April 2024

Mammals in drylands face environmental challenges exacerbated by climate change. Currently, human activity significantly impacts these environments, and its effects on the energy demands experienced by individuals have not yet been determined. Energy demand in organisms is managed through elevations in glucocorticoid levels, which also vary with developmental and health states. Here, we assessed how anthropization, individual characteristics, and seasonality influence hair glucocorticoid concentration in the Darwin’s leaf-eared mouse (Phyllotis darwini) inhabiting two areas with contrasting anthropogenic intervention in a semi-arid ecosystem of northern Chile. Hair samples were collected (n = 199) to quantify hair corticosterone concentration (HCC) using enzyme immunoassays; additionally, sex, body condition, and ectoparasite load were recorded. There were no differences in HCC between anthropized areas and areas protected from human disturbance; however, higher concentrations were recorded in females, and seasonal fluctuations were experienced by males. The results indicate that animals inhabiting semi-arid ecosystems are differentially stressed depending on their sex. Additionally, sex and season have a greater impact on corticosterone concentration than anthropogenic perturbation, possibly including temporal factors, precipitation, and primary production. The influence of sex and seasonality on HCC in P. darwini make it necessary to include these variables in future stress assessments of this species.
Effects of Parity and Somatic Cell Count Threshold on Udder Morphology, Milkability Traits, and Milk Quality in Canarian Goats
Authors: Salomone-Caballero Mario , Fresno María , Álvarez Sergio , Torres Alexandr
Published: April 2024

The effects of parity and somatic cell count in milk (SCC) threshold on the udder morphology, milkability traits, and milk composition was evaluated in 41 Canarian goats in mid-lactation. The animals were divided according to parity (1st, 2nd, and 3rd), and a SCC threshold of 2000 × 103 cells/mL in milk was set to evaluate the effect of this factor on the different measured parameters. Results showed that primiparous goats had the udder smaller and less distended than multiparous goats, but no differences were detected on milk flow parameters. Furthermore, SCC and total bacterial count (TBC) tended to be higher when the parity increased. On the other hand, goats with SCC ≤ 2000 × 103 had higher cistern-floor distance (CF) and lower TBC values compared with those goats with a count above the predetermined threshold. The results suggest that a reduction in SCC can be achieved by a selection of udder morphological traits. Moreover, milk flow parameters do not seem to be a tool to determine the udder health status in Canarian goats, but long-term studies are needed to verify it.
ProAKAP4 as Indicator of Long-Lasting Motility Marker in Post-Thaw Conditions in Stallions
Authors: Dordas-Perpinyà Marta , Yánez-Ortiz Iván , Sergeant Nicolas , Mevel Vincent , Catalán Jaime , Bruyas Jean-François , Miró Jordi , Briand-Amirat Lamia
Published: April 2024

ProAKAP4, a precursor of AKAP4 (A-kinase anchor protein) found in the flagellum of mammalian and non-mammalian spermatozoa, serves as a structural protein with established correlations to motility parameters across diverse species. This study aimed to determine the proAKAP4 level evolution in thawed stallion semen over a 3 h period, examining its correlation with motility descriptors and mitochondrial membrane potential. Utilizing sixteen ejaculates from four French warmblood stallions, this study involved maintaining thawed samples at 37 °C for 3 h, conducting proAKAP4 enzyme-linked immunosorbent assays (ELISA), computer-assisted sperm analysis (CASA), and mitochondrial membrane potential by JC-1 probe and flow cytometry at 0, 1, and 3 h post-thawing. The findings indicate significant positive correlations (p ≤ 0.05) between proAKAP4 levels and sperm total or progressive motility at all time points analyzed. Spermatozoa velocity descriptors (VAP, VCL, VSL) and spermatozoa lateral head displacement (ALH) display positive correlations (p ≤ 0.05) with ProAKAP4 at the 0 h post-thawing. ProAKAP4 concentration exhibits no discernible difference between batches with or without a cryoprotectant. Notably, proAKAP4 consumption remains insignificant within the initial hour after thawing but becomes significant (p ≤ 0.05) between 1 and 3 h post-thawing. In summary, proAKAP4 demonstrates positive correlations with total and progressive motility in stallion semen for up to 3 h after thawing, albeit showing a noticeable decrease starting from the first hour post-thawing, indicating a progressive consumption as a result of spermatozoa motile activity.
Tactile, Auditory, and Visual Stimulation as Sensory Enrichment for Dairy Cattle
Authors: Mota-Rojas Daniel , Whittaker Alexandra L. , Domínguez-Oliva Adriana , Strappini Ana C. , Álvarez-Macías Adolfo , Mora-Medina Patricia , Ghezzi Marcelo , Lendez Pamela , Lezama-García Karina , Grandin Temple
Published: April 2024

Several types of enrichment can be used to improve animal welfare. This review summarizes the literature on the use of mechanical brushes, tactile udder stimulation, music, and visual stimuli as enrichment methods for dairy cows. Mechanical brushes and tactile stimulation of the udder have been shown to have a positive effect on milk yield and overall behavioral repertoire, enhancing natural behavior. Classical music reduces stress levels and has similarly been associated with increased milk yield. A slow or moderate tempo (70 to 100 bpm) at frequencies below 70 dB is recommended to have this positive effect. Evidence on the impacts of other types of enrichment, such as visual stimulation through mirrors, pictures, and color lights, or the use of olfactory stimuli, is equivocal and requires further study.
Programmed Grooming after 30 Years of Study: A Review of Evidence and Future Prospects
Authors: Mooring Michael
Published: April 2024

In 1992, an evolutionary model for the endogenous regulation of parasite-defense grooming was first proposed for African antelope by Ben and Lynette Hart. Known as the programmed grooming model, it hypothesized that a central control mechanism periodically evokes grooming so as to remove ectoparasites before they blood feed. The programmed grooming model contrasts with a stimulus-driven mechanism, in which grooming is stimulated by direct peripheral irritation from ectoparasite bites. In the 30+ years since the seminal 1992 paper, 26 studies have provided robust support for the programmed grooming model in ungulate hosts and ticks. In addition, multiple studies from unaffiliated investigators have evaluated the predictions of the model in different host systems (including rodents and primates) and in a variety of other ectoparasites (fleas, lice, and keds). I conducted a tricennial review of these studies to assess the current evidence and arrived at the following three conclusions: (1) tests of the programmed grooming predictions should use a similar methodology to the well-established protocol, so that the results are comparable and can be properly assessed; (2) the predictions used to test the model should be tailored to the biology of the host taxa under investigation; and (3) the predictions should likewise be tailored to the biology of the ectoparasites involved, bearing in mind that grooming has varying degrees of effectiveness, depending on the parasite. Further research is warranted to enhance our understanding of the role of grooming in maintaining the health of wild animals in the face of parasite attacks.
Enhancing Deposit Exploitation Efficiency Utilizing Small-Diameter Radial Boreholes via Hydraulic Drilling Nozzles for Optimal Resource Recovery
Authors: Toczek Przemyslaw , Wisniowski Rafal
Published: April 2024

The exploration and development of new hydrocarbon deposits is facing increasing challenges as the global shift to renewable energy sources, such as shallow geothermal deposits, wind farms, and photovoltaics, reduces the dependence on hydrocarbons. To navigate this evolving landscape, it becomes crucial to find solutions that optimize the energy extraction efficiency while maximizing the use of hydrocarbon deposits. This requires exploring opportunities in existing fields and wells, including those slated for decommissioning. This article discusses the potential for extracting resources from seemingly depleted fields, where some 60–70% of the resources remain unrecoverable due to low reservoir energy. Meeting this challenge requires the implementation of secondary and tertiary EOR methods that involve the introduction of external energy to increase reservoir pressure and enhance resource recovery. One of the proposed innovative tertiary methods involves reaming the reservoir using multiple small-diameter radial boreholes generated by a hydraulic drilling nozzle. This strategy is designed to intensify the contact between the production hole and the reservoir layer, resulting in increased or commenced production in certain cases. The described method proves to be a practical application in hydrocarbon deposits, offering the dual benefits of mitigating environmental pollution by eliminating the need for drilling new boreholes and providing a cost-effective means of accessing resources in decommissioned deposits with insufficient reservoir energy for self-exploitation. Another article points out the design variation of a hydraulic drilling nozzle tailored specifically for reaming a reservoir layer. Taking the above into account, this article provides very practical information for future projects in which paths should be sought for the design and development of hydraulic wellheads, among other things, in order to intensify the production from hydrocarbon deposits.
All in How You Ask for It: Simple Black-Box Method for Jailbreak Attacks
Authors: Takemoto Kazuhiro
Published: April 2024

Large Language Models (LLMs), such as ChatGPT, encounter ‘jailbreak’ challenges, wherein safeguards are circumvented to generate ethically harmful prompts. This study introduces a straightforward black-box method for efficiently crafting jailbreak prompts that bypass LLM defenses. Our technique iteratively transforms harmful prompts into benign expressions directly utilizing the target LLM, predicated on the hypothesis that LLMs can autonomously generate expressions that evade safeguards. Through experiments conducted with ChatGPT (GPT-3.5 and GPT-4) and Gemini-Pro, our method consistently achieved an attack success rate exceeding 80% within an average of five iterations for forbidden questions and proved to be robust against model updates. The jailbreak prompts generated were not only naturally worded and succinct, but also challenging to defend against. These findings suggest that the creation of effective jailbreak prompts is less complex than previously believed, underscoring the heightened risk posed by black-box jailbreak attacks.
Cancerous and Non-Cancerous MRI Classification Using Dual DCNN Approach
Authors: Saeed Zubair , Bouhali Othmane , Ji Jim Xiuquan , Hammoud Rabih , Al-Hammadi Noora , Aouadi Souha , Torfeh Tarraf
Published: April 2024

Brain cancer is a life-threatening disease requiring close attention. Early and accurate diagnosis using non-invasive medical imaging is critical for successful treatment and patient survival. However, manual diagnosis by radiologist experts is time-consuming and has limitations in processing large datasets efficiently. Therefore, efficient systems capable of analyzing vast amounts of medical data for early tumor detection are urgently needed. Deep learning (DL) with deep convolutional neural networks (DCNNs) emerges as a promising tool for understanding diseases like brain cancer through medical imaging modalities, especially MRI, which provides detailed soft tissue contrast for visualizing tumors and organs. DL techniques have become more and more popular in current research on brain tumor detection. Unlike traditional machine learning methods requiring manual feature extraction, DL models are adept at handling complex data like MRIs and excel in classification tasks, making them well-suited for medical image analysis applications. This study presents a novel Dual DCNN model that can accurately classify cancerous and non-cancerous MRI samples. Our Dual DCNN model uses two well-performed DL models, i.e., inceptionV3 and denseNet121. Features are extracted from these models by appending a global max pooling layer. The extracted features are then utilized to train the model with the addition of five fully connected layers and finally accurately classify MRI samples as cancerous or non-cancerous. The fully connected layers are retrained to learn the extracted features for better accuracy. The technique achieves 99%, 99%, 98%, and 99% of accuracy, precision, recall, and f1-scores, respectively. Furthermore, this study compares the Dual DCNN’s performance against various well-known DL models, including DenseNet121, InceptionV3, ResNet architectures, EfficientNetB2, SqueezeNet, VGG16, AlexNet, and LeNet-5, with different learning rates. This study indicates that our proposed approach outperforms these established models in terms of performance.
Lower Extremity Joint Kinetics during Walk-to-Run and Run-to-Walk Transitions
Authors: Jin Li , Hahn Michael E.
Published: April 2024

Lower extremity joint kinetic factors are thought to modulate walk-to-run transition (WRT) and run-to-walk transition (RWT). This study aimed to investigate joint stiffness and energetic patterns during the WRT and RWT processes and identify whether gait transitions occur within a single step or not. Ten healthy subjects participated in treadmill WRT (1.8–2.4 m/s) and RWT (2.4–1.8 m/s) tests. We investigated two steps before transition (S–2, S–1), two steps after transition (S1, S2) and the transition step (S0). We found significant differences between S2 and S–2 for ankle joint stiffness during WRT and RWT (p < 0.001); for hip joint stiffness, we found significant differences between S1 and S–1 during WRT and RWT (p ≤ 0.001). Additionally, stance phase mechanical energy generation was observed to transfer from proximal to distal joints at S0 during WRT, and from distal to proximal at S0 during RWT. Transition step ankle kinematic and kinetic patterns were similar to the target locomotion task gait format in both WRT and RWT. Moreover, RWT required longer adaptation time compared with WRT. These findings indicate that WRT and RWT were modulated before and after the actual transitions, not within a single step. Redistribution of joint mechanical work generation was related to gait transition triggers, which modulate the WRT and RWT processes.
Cell-Free Nuclear and Mitochondrial DNA as Potential Biomarkers for Assessing Sepsis Severity
Authors: de Miranda Felipe Silva , Claudio Livia Maria A. M. , de Almeida Dayanne Silva M. , Nunes Juliana Braga , Barauna Valério Garrone , Luiz Wilson Barros , Vassallo Paula Frizzera , Campos Luciene Cristina Gastalho
Published: April 2024

Sepsis continues to be a significant public health challenge despite advances in understanding its pathophysiology and management strategies. Therefore, this study evaluated the value of cell-free nuclear DNA (cf-nDNA) and cell-free mitochondrial DNA (cf-mtDNA) for assessing the severity and prognosis of sepsis. Ninety-four patients were divided into three groups: infection (n = 32), sepsis (n = 30), and septic shock (n = 32). Plasma samples were collected at the time of diagnosis, and cfDNA concentrations were determined by qPCR assay. The results showed that plasma cfDNA levels increased with the severity of the disease. To distinguish between patients with infection and those with sepsis, the biomarker L1PA290 achieved the highest AUC of 0.817 (95% CI: 0.725–0.909), demonstrating a sensitivity of 77.0% and a specificity of 79.3%. When cf-nDNA was combined with the SOFA score, there was a significant improvement in the AUC (0.916 (0.853–0.979)), sensitivity (88.1%), and specificity (80.0%). Moreover, patients admitted to the ICU after being diagnosed with sepsis had significantly higher cf-nDNA concentrations. In patients admitted to the ICU, combining cf-nDNA with the SOFA score yielded an AUC of 0.753 (0.622–0.857), with a sensitivity of 95.2% and a specificity of 50.0%. cfDNA can differentiate between patients with infection and those with sepsis. It can also identify patients who are likely to be admitted to the ICU by predicting those with indications for intensive care, suggesting its potential as a biomarker for sepsis.
Shape Memory Alloys Patches to Mimic Rolling, Sliding, and Spinning Movements of the Knee
Authors: Seo Suyeon , Kang Minchae , Han Min-Woo
Published: April 2024

Every year, almost 4 million patients received medical care for knee osteoarthritis. Osteoarthritis involves progressive deterioration or degenerative changes in the cartilage, leading to inflammation and pain as the bones and ligaments are affected. To enhance treatment and surgical outcomes, various studies analyzing the biomechanics of the human skeletal system by fabricating simulated bones, particularly those reflecting the characteristics of patients with knee osteoarthritis, are underway. In this study, we fabricated replicated bones that mirror the bone characteristics of patients with knee osteoarthritis and developed a skeletal model that mimics the actual movement of the knee. To create patient-specific replicated bones, models were extracted from computerized tomography (CT) scans of knee osteoarthritis patients. Utilizing 3D printing technology, we replicated the femur and tibia, which bear the weight of the body and support movement, and manufactured cartilage capable of absorbing and dispersing the impact of knee joint loads using flexible polymers. Furthermore, to implement knee movement in the skeletal model, we developed artificial muscles based on shape memory alloys (SMAs) and used them to mimic the rolling, sliding, and spinning motions of knee flexion. The knee movement was investigated by changing the SMA spring’s position, the number of coils, and the applied voltage. Additionally, we developed a knee-joint-mimicking system to analyze the movement of the femur. The proposed artificial-skeletal-model-based knee-joint-mimicking system appears to be applicable for analyzing skeletal models of knee patients and developing surgical simulation equipment for artificial joint replacement surgery.
Efficient Feature Learning Model of Motor Imagery EEG Signals with L1-Norm and Weighted Fusion
Authors: Kong Xiangzeng , Wu Cailin , Chen Shimiao , Wu Tao , Han Junfeng
Published: April 2024

Brain–computer interface (BCI) for motor imagery is an advanced technology used in the field of medical rehabilitation. However, due to the poor accuracy of electroencephalogram feature classification, BCI systems often misrecognize user commands. Although many state-of-the-art feature selection methods aim to enhance classification accuracy, they usually overlook the interrelationships between individual features, indirectly impacting the accuracy of feature classification. To overcome this issue, we propose an adaptive feature learning model that employs a Riemannian geometric approach to generate a feature matrix from electroencephalogram signals, serving as the model’s input. By integrating the enhanced adaptive L1 penalty and weighted fusion penalty into the sparse learning model, we select the most informative features from the matrix. Specifically, we measure the importance of features using mutual information and introduce an adaptive weight construction strategy to penalize regression coefficients corresponding to each variable adaptively. Moreover, the weighted fusion penalty balances weight differences among correlated variables, reducing the model’s overreliance on specific variables and enhancing accuracy. The performance of the proposed method was validated on BCI Competition IV datasets IIa and IIb using the support vector machine. Experimental results demonstrate the effectiveness and superiority of the proposed model compared to the existing models.
Integrative Magnetic Resonance Imaging and Metabolomic Characterization of a Glioblastoma Rat Model
Authors: Arias-Ramos Nuria , Vieira Cecilia , Pérez-Carro Rocío , López-Larrubia Pilar
Published: April 2024

Glioblastoma (GBM) stands as the most prevalent and lethal malignant brain tumor, characterized by its highly infiltrative nature. This study aimed to identify additional MRI and metabolomic biomarkers of GBM and its impact on healthy tissue using an advanced-stage C6 glioma rat model. Wistar rats underwent a stereotactic injection of C6 cells (GBM group, n = 10) or cell medium (sham group, n = 4). A multiparametric MRI, including anatomical T2W and T1W images, relaxometry maps (T2, T2*, and T1), the magnetization transfer ratio (MTR), and diffusion tensor imaging (DTI), was performed. Additionally, ex vivo magnetic resonance spectroscopy (MRS) HRMAS spectra were acquired. The MRI analysis revealed significant differences in the T2 maps, T1 maps, MTR, and mean diffusivity parameters between the GBM tumor and the rest of the studied regions, which were the contralateral areas of the GBM rats and both regions of the sham rats (the ipsilateral and contralateral). The ex vivo spectra revealed markers of neuronal loss, apoptosis, and higher glucose uptake by the tumor. Notably, the myo-inositol and phosphocholine levels were elevated in both the tumor and the contralateral regions of the GBM rats compared to the sham rats, suggesting the effects of the tumor on the healthy tissue. The MRI parameters related to inflammation, cellularity, and tissue integrity, along with MRS-detected metabolites, serve as potential biomarkers for the tumor evolution, treatment response, and impact on healthy tissue. These techniques can be potent tools for evaluating new drugs and treatment targets.
Language Distance Moderates the Effect of a Mixed-Language Environment on New-Word Learning for 4-Year-Old Children
Authors: Niu Zhengkai , Li Zilong , Ma Yunxiao , Yu Keke , Wang Ruiming
Published: April 2024

As bilingual families increase, the phenomenon of language mixing among children in mixed-language environments has gradually attracted academic attention. This study aims to explore the impact of language mixing on vocabulary acquisition in bilingual children and whether language distance moderates this impact. We recruited two groups of bilingual children, Chinese–English bilinguals and Chinese–Japanese bilinguals, to learn two first-language new words in a monolingual environment and a mixed-language environment, respectively. The results showed that the participants could successfully recognize the novel words in the code-switching sentences. However, when we compared the performance of the two groups of bilingual children, we found that the gaze time proportion of the Chinese–English bilingual children under the code-switching condition was significantly higher than that of the Chinese–Japanese bilingual children, while there was no significant difference under the monolingual condition. This suggests that language mixing has an inhibitory effect on vocabulary acquisition in bilingual children and that this inhibitory effect is influenced by language distance, that is, the greater the language distance, the stronger the inhibitory effect. This study reveals the negative impact of language mixing on vocabulary acquisition in bilingual children and also implies that there may be some other influencing factors, so more research is needed on different types of bilingual children.
Pharmacodynamic and Toxicity Studies of 6-Isopropyldithio-2′-guanosine Analogs in Acute T-Lymphoblastic Leukemia
Authors: Song Tiantian , Yu Zheming , Shen Qitao , Xu Yu , Hu Haihong , Liu Junqing , Zeng Kui , Lei Jinxiu , Yu Lushan
Published: April 2024

(1) Background: The research group has developed a new small molecule, 6-Isopropyldithio-2′-deoxyguanosine analogs-YLS004, which has been shown to be the most sensitive in acute T-lymphoblastic leukemia cells. Moreover, it was found that the structure of Nelarabine, a drug used to treat acute T-lymphoblastic leukemia, is highly similar to that of YLS004. Consequently, the structure of YLS004 was altered to produce a new small molecule inhibitor for this study, named YLS010. (2) Results: YLS010 has exhibited potent anti-tumor effects by inducing cell apoptosis and ferroptosis. A dose gradient was designed for in vivo experiments based on tentative estimates of the toxicity dose using acute toxicity in mice and long-term toxicity in rats. The study found that YLS010 at a dose of 8 mg/kg prolonged the survival of late-stage acute T-lymphoblastic leukemia mice in the mouse model study. (3) Conclusions: YLS010 has demonstrated specific killing effects against acute T-lymphoblastic leukemia both in vivo and in vitro. Preclinical studies of YLS010 offer a new opportunity for the treatment of patients with acute T-lymphoblastic leukemia in clinical settings.
Short-Term Outcomes Analysis Comparing Open, Laparoscopic, Laparoscopic-Assisted, and Robotic Distal Gastrectomy for Locally Advanced Gastric Cancer: A Randomized Trials Network Analysis
Authors: Manara Michele , Aiolfi Alberto , Sozzi Andrea , Calì Matteo , Grasso Federica , Rausa Emanuele , Bonitta Gianluca , Bonavina Luigi , Bona Davide
Published: April 2024

Background. Minimally invasive surgery for the treatment of locally advanced gastric cancer (AGC) is debated. The aim of this study was to execute a comprehensive assessment of principal surgical treatments for resectable distal gastric cancer. Methods. Systematic review and randomized controlled trials (RCTs) network meta-analysis. Open (Op-DG), laparoscopic-assisted (LapAs-DG), totally laparoscopic (Lap-DG), and robotic distal gastrectomy (Rob-DG) were compared. Pooled effect-size measures were the risk ratio (RR), the weighted mean difference (WMD), and the 95% credible intervals (CrIs). Results. Ten RCTs (3823 patients) were included. Overall, 1012 (26.5%) underwent Lap-DG, 902 (23.6%) LapAs-DG, 1768 (46.2%) Op-DG, and 141 (3.7%) Rob-DG. Anastomotic leak, severe complications (Clavien–Dindo > 3), and in-hospital mortality were comparable. No differences were observed for reoperation rate, pulmonary complications, postoperative bleeding requiring transfusion, surgical-site infection, cardiovascular complications, number of harvested lymph nodes, and tumor-free resection margins. Compared to Op-DG, Lap-DG and LapAs-DG showed a significantly reduced intraoperative blood loss with a trend toward shorter time to first flatus and reduced length of stay. Conclusions. LapAs-DG, Lap-DG, and Rob-DG performed in referral centers by dedicated surgeons have comparable short-term outcomes to Op-DG for locally AGC.
Amino Terminal Acetylation of HOXB13 Regulates the DNA Damage Response in Prostate Cancer
Authors: Nguyen Duy T. , Mahajan Urvashi , Angappulige Duminduni Hewa , Doshi Aashna , Mahajan Nupam P. , Mahajan Kiran
Published: April 2024

Advanced localized prostate cancers (PC) recur despite chemotherapy, radiotherapy and/or androgen deprivation therapy. We recently reported HOXB13 lysine (K)13 acetylation as a gain-of-function modification that regulates interaction with the SWI/SNF chromatin remodeling complex and is critical for anti-androgen resistance. However, whether acetylated HOXB13 promotes PC cell survival following treatment with genotoxic agents is not known. Herein, we show that K13-acetylated HOXB13 is induced rapidly in PC cells in response to DNA damage induced by irradiation (IR). It colocalizes with the histone variant γH2AX at sites of double strand breaks (DSBs). Treatment of PCs with the Androgen Receptor (AR) antagonist Enzalutamide (ENZ) did not suppress DNA-damage-induced HOXB13 acetylation. In contrast, HOXB13 depletion or loss of acetylation overcame resistance of PC cells to ENZ and synergized with IR. HOXB13K13A mutants show diminished replication fork progression, impaired G2/M arrest with significant cell death following DNA damage. Mechanistically, we found that amino terminus regulates HOXB13 nuclear puncta formation that is essential for proper DNA damage response. Therefore, targeting HOXB13 acetylation with CBP/p300 inhibitors in combination with DNA damaging therapy may be an effective strategy to overcome anti-androgen resistance of PCs.