mdpi-ai/citelens huggingface dataset:
From immune equilibrium to tumor ecodynamics
Field: ONCOLOGY

Objectives There is no theory to quantitatively describe the complex tumor ecosystem. At the same time, cancer immunotherapy is considered a revolution in oncology, but the methods used to describe tumors and the criteria used to evaluate efficacy are not keeping pace. The purpose of this study is to establish a new theory for quantitatively describing the tumor ecosystem, innovating the methods of tumor characterization, and establishing new efficacy evaluation criteria for cancer immunotherapy. Methods Based on the mathematization of immune equilibrium theory and the establishment of immunodynamics in a previous study, the method of reverse immunodynamics was used, namely, the immune braking force was regarded as the tumor ecological force and the immune force was regarded as the tumor ecological braking force, and the concept of momentum in physics was applied to the tumor ecosystem to establish a series of tumor ecodynamic equations. These equations were used to solve the fundamental and applied problems of the complex tumor ecosystem. Results A series of tumor ecodynamic equations were established. The tumor ecological momentum equations and their component factors could be used to distinguish disease progression, pseudoprogression, and hyperprogression in cancer immunotherapy. On this basis, the adjusted tumor momentum equations were established to achieve the equivalence of tumor activity (including immunosuppressive activity and metabolic activity) and tumor volume, which could be used to calculate individual disease remission rate and establish new efficacy evaluation criteria (ieRECIST) for immunotherapy of solid tumor based on tumor ecodynamics. At the same time, the concept of moving cube-to-force square ratio and its expression were proposed to calculate the area under the curve of tumor ecological braking force of blood required to achieve an individual disease remission rate when the adjusted tumor ecological momentum was known. Conclusions A new theory termed tumor ecodynamics emphasizing both tumor activity and tumor volume is established to solve a series of basic and applied problems in the complex tumor ecosystem. It can be predicted that the future will be the era of cancer immune ecotherapy that targets the entire tumor ecosystem.
A Region-Selective Anti-compression Image Encryption Algorithm Based on Deep Networks
Field: AI

In recent years, related research has focused on how to safely transfer and protect the privacy of images in social network services while providing easy access by authorized users. To safeguard privacy, we suggest an image encryption scheme that combines data hiding and image encryption. The proposed scheme successfully decrypts images after JPEG compression attacks and preserves the privacy of secret regions through the use of block scrambling encryption based on region selection. Simultaneously, the scheme can handle nonuniform secret regions and obtain more sensitive secret keys because of the incorporation of a chaotic system. The enhanced deep learning-based data-hiding technology reduces algorithm complexity by enabling the encryption position to be determined in the decryption phase without the need for any information or equipment. However, this approach also increases algorithm security, because only when the right secret data are extracted can they be decrypted successfully. According to the experimental findings, the proposed scheme can correctly decrypt images via JPEG compression while maintaining visually acceptable quality. The proposed scheme can achieve greater robustness against image processing algorithms and a wider secret key space than traditional schemes.
The effects of mobile phone dependence on athletic performance and its mechanisms
Field: PSYCHOLOGY

Mobile phone dependence (also known as internet dependence, MPD), defined as a problematic behavior characterized by excessive use or intermittent craving to use a mobile phone, results in various social, behavioral, and affective problems in daily life. In sports, MPD is directly related to the physical and mental health and sports performance of athletes. The individual and environmental factors, neurobiological mechanisms and theoretical models of MPD affecting athletic performance were analyzed by reviewing previous studies, aiming to construct effective training and development protocols to prevent and control the occurrence of MPD in athletes. At present, athletic performance can be affected by MPD through individual factors and environmental factors. The neurobiological mechanisms between the two are based on the brain reward system and microwave radiation from mobile phones, with athletic performance being restricted by alterations in the corresponding brain regions. Relevant theoretical models mainly include the social cognitive model of self-regulation and the integrative model of self-control, which explain the interrelationship between MPD and athletic performance from the perspectives of athletes’ self-regulation and self-control, respectively. As an emerging phenomenon, the influence pathways and mechanisms by which MPD affects athletic performance need to be further investigated. A longitudinal perspective should be adopted to trace the dynamic impact relationship between the two, and developing relevant theoretical frameworks from an interdisciplinary research perspective should be valuable for providing theoretical support for coaches and sports administrators to formulate scientific training protocols and thus improve the mental health of athletes.
Attention-Focused Eye Gaze Analysis to Predict Autistic Traits Using Transfer Learning
Field: AI

Autism spectrum disorder (ASD) is a complex developmental issue that affects the behavior and communication abilities of children. It is extremely needed to perceive it at an early age. The research article focuses on attentiveness by considering eye positioning as a key feature and its implementation is completed in two phases. In the first phase, various transfer learning algorithms are implemented and evaluated to predict ASD traits on available open-source image datasets Kaggle and Zenodo. To reinforce the result, fivefold cross-validation is used on the dataset. Progressive pre-trained algorithms named VGG 16, VGG 19, InceptionV3, ResNet152V2, DenseNet201, ConNextBase, EfficientNetB1, NasNetMobile, and InceptionResNEtV2 implemented to establish the correctness of the result. The result is being compiled and analyzed that ConvNextBase model has the best diagnosing ability on both datasets. This model achieved a prediction accuracy of 80.4% on Kaggle with a batch size of 16, a learning rate of 0.00002, 10 epochs and 6 units, and a prediction accuracy of 80.71% on the Zenodo dataset with a batch size of 4, a learning rate of 0.00002, 10 epochs and 4 units. The accuracy of the model ConvNextBase is found challenging in nature as compared to an existing model. Attentiveness is a parameter that will accurately diagnose the visual behavior of the participant which helps in the automatic prediction of autistic traits. In the second phase of the proposed model, attentiveness is engrossed in identifying autistic traits. The model uses a dlib library that uses HOG and Linear SVM-based face detectors to identify a particular facial parameter called EAR and it is used to measure participants' attentiveness based on the eye gaze analysis. If the EAR value is less than 0.20 for more than 100 consecutive frames, the model concludes the participant is un-attentive. The model generated a special graph for a time period by continuously plotting the value of EAR based on the attention level. The average EAR value will depict the attentiveness of the participant.
Genome-wide investigation of lncRNAs revealed their tight association with gastric cancer
Field: ONCOLOGY

Background: Gastric cancer (GC) is a significant health issue globally, ranking as the fifth most common cancer with over 10,000 new cases reported annually. Long non-coding RNA (lncRNA) has emerged as a critical player in cellular functions, influencing GC's development, growth, metastasis, and prognosis. However, our understanding of lncRNA's role in the pathogenesis of GC remains limited. Therefore, it is particularly important to explore the relationship between lncRNA and gastric cancer. Methods: we conducted a comprehensive analysis of RNA sequencing data from the GEO database and stomach adenocarcinoma (STAD) data from the TCGA database to identify lncRNAs that exhibit altered expression levels in GC and the mechanisms underlying lncRNA-mediated transcription and post-transcriptional regulation were explored. Results: This study uncovered 94 lncRNAs with differential expression and, through co-expression analysis, linked these to 1508 differentially expressed genes (DEGs). GO functional enrichment analysis highlighted that these DEGs are involved in critical pathways, such as cell adhesion and the positive regulation of cell migration. By establishing a lncRNA-miRNA-mRNA regulatory network, we found that the ceRNA mechanism, particularly involving RP11-357H14.17 and CTD-2377D24.4, could play a role in GC progression. Experimental validation of selected differentially expressed lncRNAs and mRNAs (including RP11-357H14.17-CLDN1, BBOX1, TRPM2-AS, CLDN1, PLAU, HOXB7) confirmed the RNA-seq results. Conclusions: Overall, our findings highlight the critical role of the lncRNA-mRNA regulatory network in the development and progression of GC, offering potential biomarkers for diagnosis and targets for innovative treatment strategies.
A systematic literature review of the stereotype content model in the fields of psychology and marketing: main themes examined in the literature and an agenda for future research in marketing
Field: PSYCHOLOGY

The stereotypes content model indicates that two traits (i.e., warmth and competence) govern individuals’ impression formation. The great variety of research that has used this theory since the early 2000s leads to a need for a structured overview of prior findings. The goal of this study is to provide a concise map of research streams and present a research agenda. We conducted a systematic literature review of 955 articles. A bibliographic coupling analysis showed four clusters, i.e., (1) the general theoretical foundations of the SCM, (2) the societal impact of key stereotypes (with emphasis on gender), (3) research in clinical psychology and child development, and (4) marketing. Taking a closer look at research in marketing (using co-occurrence analysis), six research streams were identified, including research on branding, country-of-origin, front-line service providers, prosocial consumer behavior, perception of endorsers, and, more recently, on artificial intelligence (AI). The review presents key findings and research gaps across these topics. Finally, we reviewed the few articles that, although not falling into these streams, opened important research veins. This process provided the essential information to present a promising and complete research agenda, to continue building knowledge with impactful implications in different contexts.
A Hybrid CNN-TransXNet Approach for Advanced Glomerular Segmentation in Renal Histology Imaging
Field: AI

In the specialized field of renal histology, precise segmentation of glomeruli in microscopic images is crucial for accurate clinical diagnosis and pathological analysis. Facing the challenge of discerning complex visual features, such as shape, texture, and size within these images, we introduce a novel segmentation model that innovatively combines convolutional neural networks (CNNs) with the advanced TransXNet block, specifically tailored for glomerular segmentation. This innovative model is designed to capture the intricate details and broader contextual features within the images, ensuring a comprehensive and precise segmentation process. The model's architecture unfolds in two primary phases: the down-sampling phase, which utilizes CNNs structures within the TransXNet block for meticulous extraction of detailed features, and the up-sampling phase, which employs CNNs deconvolution techniques to restore spatial resolution and enhance macroscopic feature representation. A critical innovation in our model is the implementation of residual connections between these two phases, which facilitate the seamless integration of features and minimize loss of precision during image reconstruction. Experimental results demonstrate a significant improvement in our model’s performance compared to existing medical image segmentation methods. We report enhancements in mean Pixel Accuracy (mPA) and mean Intersection over Union (mIoU), with increases of approximately 3–5% and 3–8%, respectively. Additionally, the segmented outputs exhibit higher subjective visual quality with fewer noise artifacts. These findings suggest that our model offers promising applications in the segmentation of medical microscopic images, marking a significant contribution to the domain.
A family perspective for the mechanism of parent-child conflict on maternal anxiety in Chinese children with autism
Field: PSYCHOLOGY

Mothers of children with autism reported higher levels of anxiety than mothers of typical children. This study revealed the relationship between parent-child conflict, children’s problem behavior, parenting stress, and maternal anxiety from the perspective of the relationship within the family. The State-Trait Anxiety Inventory (STAI) and Caregiver Strain Questionnaire (CGSQ) were used to measure maternal anxiety and parenting stress respectively from 102 mothers of children with autism. We also collected information on parent-child relationships and children’s problem behaviors by using the Child-Parent Relationship Scale (CPRS) and Conners Parent Symptom Questionnaire (PSQ). Parent-child conflict positively predicted state and trait anxiety in mothers of children with autism. The severity of children’s psychosomatic disorders fully mediated the positive association between parent-child conflict and state-trait anxiety in mothers of children with autism. Parenting stress significantly moderated the impact of parent-child conflict on maternal state anxiety and trait anxiety. In the case of children with autism spectrum disorders, parent-child conflict can directly affect maternal anxiety levels, especially when mothers have low levels of parenting stress. Parent-child conflict can also affect children’s problem behaviors and thus indirectly affect maternal anxiety. Therefore, this study is of great significance for the alleviation of anxiety of mothers of autistic children and the family intervention for the early rehabilitation of autistic children.
The relationship between neonatal stress in preterm infants and developmental outcomes at the corrected age of 24–30 months
Field: PSYCHOLOGY

Aim The aim of research was to study the relationship between the stress experienced by preterm infants in the neonatal intensive care unit (NICU) and developmental status in the follow up, and to establish factors, associated with their neurodevelopment. Methods The first stage of research involved measuring stress markers (cortisol, melatonin) in infants (n = 56) during their NICU stay; the second phase assessed the developmental status at the corrected age of 24–30 months. Results The total ASQ-3 score, communication, problem solving, and personal-social skills scores at the corrected age of 24–30 months were positively correlated with melatonin level determined in the neonatal period (r = 0.31, p = 0.026; r = 0.36, p = 0.009; r = 0.30, p = 0.033, and r = 0.32; p = 0.022 respectively). In the same time, ASQ-3 communication and personal-social scores were negatively correlated with cortisol level (r = −0.31, p = 0.043; r = −0.35, p = 0.022). The ROC-curve analysis revealed that a decrease of melatonin below 3.44 ng/mL and 3.71 ng/mL during the neonatal period could predict communication and problem-solving delay, respectively. An increase in cortisol above 0.64 mcg/dl is predictive in personal-social delay. Negative correlation was identified between the NICU and total hospital stay duration and ASQ-3 communication scores in the follow-up (r = −0.27; p = 0.049 and r = −0.41; p = 0.002, respectively). The duration of mechanical ventilation was negatively correlated with gross motor scores (r = −0.46; p = 0.043). Apgar score was positively correlated with ASQ-3 communication (r = 0.29; p = 0.032) and personal-social scores (r = 0.28; p = 0.034); maternal age—with ASQ-3 total (r = 0.29; p = 0.034), communication (r = 0.37; p = 0.006), and personal-social scores (r = 0.29; p = 0.041). Positive correlations were observed between gestational age and communication scores (r = 0.28; p = 0.033). Infants who suffered neonatal sepsis had significantly often delay of communication (p = 0.014) and gross motor skills (p = 0.016). Children who required mechanical ventilation were more likely to have communication delay (p = 0.034). Conclusion Developmental outcomes in preterm infants at the corrected age of 24–30 months were associated with neonatal stress. Correlations between the communication, problem-solving and personal-social development in the follow up and cortisol and melatonin levels determined in the neonatal period supported this evidence. Factors as low gestational age, duration of hospital and NICU stay, mechanical ventilation, and sepsis were associated with more frequent delays in communication, gross motor and problems-solving skills.
A Multiple Environment Available Path Planning Based on an Improved A* Algorithm
Field: AI

The objective of the path planning for a mobile robot is to generate a collision-free path from a starting position to a target position, aiming to realize a higher quality of path planning, an improved A* algorithm and a hybrid approach incorporating the dynamic window algorithm have been proposed for robot path planning in various environments in this paper. In global path planning, first, a bidirectional search strategy was introduced into to improve the searching efficiency, and an adaptive heuristic function was designed to reduce redundant search nodes. In the meantime, a filtering function for key path nodes and an enhanced jump point optimization method help to remove redundant nodes in the path, reduce turning angles, greatly shorten the path length, and smooth the path using cubic B-spline curves. Furthermore, in local path planning, the combination of key path nodes and the dynamic window approach (DWA) algorithm is utilized to achieve obstacle avoidance in dynamic environments and adjust the heading angle of the section enables seamless locomotion of the robot. Finally, the simulation experiments and physical experiments on the robot were conducted to validate that the proposed improved algorithm significantly improves the speed of path planning while also reducing the length of the planned path and improve the reliability of the algorithm when compared with other algorithms.
The CABANA model 2017–2022: research and training synergy to facilitate bioinformatics applications in Latin America
Field: EDUCATION

The CABANA project (Capacity Building for Bioinformatics in Latin America) was funded by the UK’s Global Challenges Research Fund in 2017 with the aim to strengthen the bioinformatics capacity and extend its applications in Latin America focused on three challenge areas – communicable diseases, sustainable food production and protection of biodiversity. For 5 years, the project executed activities including data analysis workshops, train-the-trainer workshops, secondments, eLearning development, knowledge exchange meetings, and research projects in 10 countries. The project was successful in accomplishing all its goals with a major impact on the region. It became a model by which the research needs determined the training that was delivered. Multiple publications and over 800 trainees are part of the legacy of the project.
VISCERAL SENSITIVITY INDEX (VSI-IT): Italian Adaptation and Validation
Field: PSYCHOLOGY

The Visceral Sensitivity Index (VSI) represents a significant advancement in the assessment of gastrointestinal-specific anxiety among patients with irritable bowel syndrome (IBS) and chronic inflammatory bowel diseases (IBD)—such as ulcerative colitis and Crohn’s disease. However, an Italian version of the instrument is not yet available for the Italian-speaking population. This study utilized a national sample of 500 individuals divided into four groups: (a) patients with Crohn’s disease, (b) patients with ulcerative colitis, (c) patients with IBS, and (d) healthy controls (individuals without any diagnoses) to test the validity and reliability of the Italian VSI. Using back-translation methodology to ensure translation fidelity, this research applied a questionnaire and the VSI through an online format to 500 participants. Confirmatory Factor Analysis (CFA) revealed that the Italian VSI had excellent psychometric properties, demonstrating high internal consistency (Cronbach’s α = 0.949) and construct validity. The scale proved sensitive in detecting significant differences in visceral sensitivity among groups, highlighting its utility as a clinical and research assessment tool. Specifically, the Italian VSI exhibited a unidimensional factorial structure and maintained a strong correlation with interoceptive awareness, type of disease, and gastrointestinal symptom severity, confirming its role in enhancing the understanding and management of IBD and IBS in Italy.
Nasopharyngeal amyloidoma: report of three cases and review of the literature
Field: ONCOLOGY

Background: Nasopharyngeal amyloidoma is a rare, locally aggressive tumor that has been reported in the English literature in only 38 cases to date, most of which were in the form of case reports. The present study was aimed to summarize the characteristics of this rare tumor, with the goal of providing new insights for diagnosis and treatment. Materials and methods: We report three cases of nasopharyngeal amyloidoma diagnosed in our hospital following comprehensive medical examination and review the current literature on all cases of nasopharyngeal amyloidoma from PubMed. The journey of nasopharyngeal amyloidoma, including presentation, diagnostics, surgeries, and follow-up was outlined. Results: None of the three patients had systemic amyloidosis. CT and nasal endoscopy showed irregular masses obstructing the nasopharyngeal cavity. Congo red staining confirmed the deposition of amyloid, and immunohistochemical analysis showed that the amyloid deposition was the AL light chain type. Through literature review, we found that nasopharyngeal amyloidoma most commonly occurred in individuals over the age of 40, patients usually had a good prognosis after complete tumor resection; however, there were still cases of recurrence, and unresected patients were at risk of progression to systemic amyloidosis. The efficacy of radiotherapy and chemotherapy was currently uncertain. Conclusion: Early clinical and pathological diagnosis is crucial, and surgical intervention is the primary treatment option for this disease. Although patients usually have a favorable prognosis, long-term monitoring is necessary to detect potential relapses and initiate timely intervention.