Search Results (379)

The mitochondrial genomes of three species of Elmidae were sequenced. The sizes were 16,309 bp (C. jaechi), 16,291 bp (G. longiusculus), and 15,480 bp (S. punctulata). Each genome includes 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), two ribosomal RNA genes (rRNAs), and a control region (CR). All three mitogenomes show AT bias. Except for trnS1, lacking the dihydrouridine (DHU) arm, all tRNA genes had a typical cloverleaf structure. The codon usage preferences of the three species showed high similarity. The arrangement of the genes in the three mitogenomes was consistent among them but differed from that in the typical mitogenomes of Coleoptera. The Ka/Ks ratio indicated that COX1 and nad4L had a lower evolutionary rate, being relatively conserved genes among 13 PCGs. The phylogenetic analysis revealed that Elmidae belongs to the superfamily Dryopoidea within the suborder Polyphaga and is monophyletic. The results preliminarily indicate that the taxonomic groups at the subfamily, tribe, and genus levels within Elmidae are ambiguous, and further revisions may be required in the future. Full article

Background: Prostate cancer (PCa) diagnosis using MRI is often challenged by lesion variability. Methods: This study introduces Simplatab, an open-source automated machine learning (AutoML) framework designed for, but not limited to, automating the entire machine Learning pipeline to facilitate the detection of clinically significant prostate cancer (csPCa) using radiomics features. Unlike existing AutoML tools such as Auto-WEKA, Auto-Sklearn, ML-Plan, ATM, Google AutoML, and TPOT, Simplatab offers a comprehensive, user-friendly framework that integrates data bias detection, feature selection, model training with hyperparameter optimization, explainable AI (XAI) analysis, and post-training model vulnerabilities detection. Simplatab requires no coding expertise, provides detailed performance reports, and includes robust data bias detection, making it particularly suitable for clinical applications. Results: Evaluated on a large pan-European cohort of 4816 patients from 12 clinical centers, Simplatab supports multiple machine learning algorithms. The most notable features that differentiate Simplatab include ease of use, a user interface accessible to those with no coding experience, comprehensive reporting, XAI integration, and thorough bias assessment, all provided in a human-understandable format. Conclusions: Our findings indicate that Simplatab can significantly enhance the usability, accountability, and explainability of machine learning in clinical settings, thereby increasing trust and accessibility for AI non-experts. Full article

This study investigates the beliefs about multilingualism and the multilingual language use of multilingual children living in the Netherlands, a highly diverse and multilingual society. We interviewed 26 8- to 12-year-old primary school children with different home languages (i.e., English, German, Polish or Turkish). Children indicated how a multilingual alter-ego felt about multilingual language use scenarios and why. The scenarios comprised situations using their different languages with parents, friends or teachers in monolingual and multilingual modes. Children overwhelmingly associated neutral or positive feelings with using the societal and home language. These feelings were not consistently affected by the societal prestige of their home language (measured by English and German vs. Polish and Turkish as their home language). The content analysis indicated that, besides competence, accommodating the interlocutor, personal preference and normality were the most frequent explanations children provided for their emotional reactions. Our findings indicate that the participating children experience being multilingual as normal and are not (yet) negatively affected in their attitudes despite their experience with a monolingual bias at school. Although no effects of home language prestige emerged, differences between children from specific home language communities suggest that myths about multilingual competence and code-mixing persist. Full article

Background/Objectives: To assess the factors affecting the unconscious bias of healthcare professionals (HCPs) in obesity care. Methods: A cross-sectional, non-interventional, descriptive study collecting data via an online survey system was distributed via e-mail to 11,597 members of the Medical Chamber of Slovenia. Physicians were assigned into six HCP categories: (junior) resident physicians, primary care physicians (PCPs), internal medicine specialists, surgeons, dentists, and others. The online questionnaire was active for two weeks. Results: A total of 1248 physicians opened the survey link (10.8% response rate). Of the 898 physicians that engaged in the survey, 789 fully completed the questionnaire. Out of those physicians, 93.6% agreed that obesity is a disease, 83.7% were familiar with the definition, and 75.5% of HCPs were professionally interested in the subject. Overall, 39% of HCPs use the ICD obesity code, primarily primary care physicians and specialists in internal medicine. Notably, 82.0% of HCPs identified lifestyle change as the most effective intervention and believed that patients could lose weight with a serious attempt at a lifestyle change. This belief was particularly supported by male HCPs and HCPs under 40 years of age, who felt that patients were entirely responsible for their weight. The unconscious bias decreased with an increase in the HCPs’ body mass index (BMI), but at the same time, physicians with a higher BMI found obesity to be less important than other diseases (p = 0.036). Using composite answers, we found that the unconscious bias of HCPs toward obesity and effective obesity care was significantly related to gender (p = 0.017), age (p < 0.001), and BMI (p = 0.005), and was independent of an area of expertise. Conclusions: HCPs’ area of expertise impacted their professional standpoint (suggesting conscious bias), whereas male gender, a younger age, and a lower BMI affected unconscious bias toward obesity and its effective care. Despite their limitations, including the self-reported nature of the data, our findings can help to individualize educational strategies and create a more equitable environment in obesity healthcare. Full article

Background: The Ommastrephidae family of cephalopods is important in marine ecosystems as both predators and prey. Species such as Todarodes pacificus, Illex argentinus, and Dosidicus gigas are economically valuable but are threatened by overfishing and environmental changes. The genus Sthenoteuthis, especially S. oualaniensis, shows significant morphological and genetic variation, including medium-sized and dwarf forms found in the South China Sea. Methods: Specimens of S. oualaniensis were collected from the South China Sea, their genomic DNA sequenced, and phylogenetic relationships analyzed using mitochondrial genomes from various Ommastrephidae species. Results: The study presents the complete mitochondrial genome of the dwarf form of S. oualaniensis (20,320 bp) and compares it with the medium-sized form, revealing a typical vertebrate structure with 13 protein-coding genes, 21 tRNA genes, and 2 rRNA genes, along with a strong AT bias. Nucleotide composition analysis shows a 12% genetic divergence between the two forms, suggesting a recent common ancestor and potential cryptic speciation, with all protein-coding genes exhibiting purifying selection based on Ka/Ks ratios below 1. Conclusions: The mitochondrial genome of the dwarf form of S. oualaniensis shows a close evolutionary relationship with the medium-sized form and a 12% genetic divergence, suggesting potential cryptic speciation. These findings underscore the importance of mitochondrial analysis in understanding speciation and guiding future conservation efforts. Full article

Bryopsis hypnoides, a unicellular multinucleate green alga in the genus Bryopsis, plays vital ecological roles and represents a key evolutionary link between unicellular and multicellular algae. However, its weak genetic baseline data have constrained the progress of evolutionary research. In this study, we successfully assembled and annotated the complete circular chloroplast and mitochondrial genomes of B. hypnoides. The chloroplast genome has a total length of 139,745 bp and contains 59 protein-coding genes, 2 rRNA genes, and 11 tRNA genes, with 31 genes associated with photosynthesis. The mitochondrial genome has a total length of 408,555 bp and contains 41 protein-coding genes, 3 rRNA genes, and 18 tRNA genes, with 18 genes involved in oxidative phosphorylation. Based on the data, we conducted a genetic comparison involving repeat sequences, phylogenetic relationships, codon usage preferences, and gene transfer between the two organellar genomes. The major results highlighted that (1) the chloroplast genome favors A/T repeats, whereas the mitochondrial genome prefers C/G repeats; (2) codon usage preference analysis indicated that both organellar genomes prefer codons ending in A/T, with a stronger bias observed in the chloroplast genome; and (3) sixteen fragments with high sequence identity were identified between the two organellar genomes, indicating potential gene transfer. These findings provide critical insights into the organellar genome characteristics and evolution of B. hypnoides. Full article

As Large Language Models (LLMs) continue to advance, their capabilities in code clone detection have garnered significant attention. While much research has assessed LLM performance on human-generated code, the proliferation of LLM-generated code raises critical questions about their ability to detect clones across both human- and LLM-created codebases, as this capability remains largely unexplored. This paper addresses this gap by evaluating two versions of LLaMA3 on these distinct types of datasets. Additionally, we perform a deeper analysis beyond simple prompting, examining the nuanced relationship between code cloning and code similarity that LLMs infer. We further explore how fine-tuning impacts LLM performance in clone detection, offering new insights into the interplay between code clones and similarity in human versus AI-generated code. Our findings reveal that LLaMA models excel in detecting syntactic clones but face challenges with semantic clones. Notably, the models perform better on LLM-generated datasets for semantic clones, suggesting a potential bias. The fine-tuning technique enhances the ability of LLMs to comprehend code semantics, improving their performance in both code clone detection and code similarity assessment. Our results offer valuable insights into the effectiveness and characteristics of LLMs in clone detection and code similarity assessment, providing a foundation for future applications and guiding further research in this area. Full article

Tanypodinae, a highly diverse subfamily within Chironomidae (Diptera), has been poorly represented in mitochondrial genome (mitogenome) databases, with only a limited number of complete or partial sequences available. To address this gap, we present the first complete mitogenome sequences of 16 Tanypodinae species and 1 Podonominae species. By integrating these novel data with previously published chironomid mitogenomes, we conducted a comprehensive comparative mitogenomic analysis of 21 Tanypodinae species. Our results reveal that Tanypodinae mitogenomes maintain a conserved structural organization, preserving the ancestral insect gene arrangement. The nucleotide composition exhibits significant bias, with the control region demonstrating the highest A + T content among all genomic regions. Evolutionary analysis indicates that all protein-coding genes (PCGs) are subject to purifying selection, with ATP8 exhibiting the most rapid evolutionary rate. Phylogenetic reconstruction based on PCG amino acid sequences delineates seven well-supported clades within Tanypodinae, corresponding to the tribes Pentaneurini, Natarsiini, Procladiini, Tanypodini, Clinotanypodini, Macropelopiini, and Anatopyniini. These findings significantly advance our understanding of mitogenomic architecture and provide critical insights into the phylogenetic relationships within Tanypodinae. Full article

Background: Non-classical manifestations such as neuropsychiatric manifestations in primary hyperparathyroidism (PHPT) have long been documented as symptoms of PHPT and are commonly reported by these patients, despite this connection still being a matter of debate, and they (per se) do not represent an indication of parathyroidectomy. Objective: We aimed to overview the most recent findings regarding the link between depression and/or anxiety (D/A) in subjects confirmed with PHPT, including the impact of the surgery in improving their outcome. Methods: This was a comprehensive review of English-based original studies published between January 2020 and October 2024. Results: The studies (n = 16) included a total of 10,325 patients and an additional 152,525 patients with hypercalcemia (out of whom 13,136 had a PHPT diagnosis and 45,081 were at risk of PHPT diagnosis). Out of these subjects with PHPT, 10,068 underwent parathyroidectomy. Female prevalence was between 62.5 and 92%. Most individuals were over 50, with the youngest studied population having a mean age of 52.7 ± 13.8 years, and the oldest had a median of 71. Depression was documented based on ICD-10 codes (n = 3) and patients’ records (n = 2), Depression Anxiety Stress Scales (DASS) (n = 2), Beck Depression Inventory (BDI) (n = 3), BDI-II (n = 3), Symptom Check List 90-revised (SCL) (n = 1), Hamilton Depression Rating Scale (HAM-D) (n = 2), HADS (n = 2), Patient Health Questionnaire-9 (n = 1), and European Quality of Life 5 Dimensions 3-Level Version (EuroQOL-5D-3L) (n = 1). Patient records’ (n = 1) and ICD-10 codes (n = 2) were also used for anxiety. Most studies used questionnaires to identify anxiety in PHPT: DASS (n = 2), SCL90R (n = 1), Generalized Anxiety Disorder-7 (n = 1), HADS (n = 2), EuroQOL-5D-3L (n = 1), and State–Trait Anxiety Inventory (n = 1). Depression prevalence varied from 20–36.6% to 65.7% (scale-based assessment) and to 10.5% upon ICD-10. A rate of newly onset depression was reported of 10.7% and of 0.2% with concern to the prevalent suicidal ideation (an incidental rate of 0.4% after a median follow-up of 4.2 years). Most studies identified a moderate depression (when assessing its severity), affecting approximately one third of the surgery candidates. The prevalence of anxiety in PHPT varied between 10.4% and 38.6% (n = 8). Discordant results were generated when applying distinct questionnaires for the same population, and this might come as a potential bias. Other confounding factors are generated by the sub-population referred for surgery that typically displays a more severe parathyroid condition or non-endocrine overlapping conditions (e.g., related to the social or familial status). Conclusion: The modern approach of the patient with PHPT should be complex and go beyond the traditional frame. D/A had a high prevalence in the mentioned studies, associated with increased medication use. Yet, the underlying pathogenic mechanisms remain incompletely elucidated. No correlations between D/A and serum calcium levels were confirmed, while PTH had a slight positive correlation with depression. Parathyroid surgery appears to be beneficial for D/A as it improves the scores, prevalence, and severity. Cinacalcet might reduce depression scores, although more evidence is needed. Women are prone to both PHPT and D/A. The optimal method of D/A screening in PHPT remains to be determined, and the current scales need validation and perhaps adjustment for this specific population sub-group, while PHPT management should be refined upon D/A identification. Full article

Artificial intelligence (AI) affects many aspects of modern life, and most predictions are that the impact of AI on business and society will only increase. In the marketing function of today’s leading businesses, two main types of AI can be discerned. Traditional AI centres on supervised learning algorithms to support and enable the application of data rules, predictive functionality and other AI-based features. Generative AI, on the other hand, uses large language model (LLM) data sets and user prompts to generate new content. While AI-generated applications and content can boost efficiency, they also present challenges regarding transparency and authenticity, and the question of bias is central to these concerns. This article adopts a qualitative inductive approach to research this issue in the context of the marketing function of a global software supplier. Based on a systematic literature review and in-depth interviews with company marketeers, the perceived bias issues in coding, prompting and deployment of AI in digital marketing are identified. Then, based on a provisional conceptual framework derived from the extant literature, an analytical framework for revealing and mitigating bias in digital marketing is put forward, incorporating the perspectives of industry-based practitioners. The framework can be used as a checklist of marketing activities in which bias may exist in either traditional or generative AI across different stages of the customer journey. The article thus contributes to the development of theory and practice regarding the management of bias in AI-generated content and will be of interest to researchers and practitioners as an operational guide and point of departure for subsequent studies. Full article

(1) Background: The insect mitogenome encodes essential genetic components and serves as an effective marker for molecular identification and phylogenetic analysis in insects due to its small size, maternal inheritance, and rapid evolution. The morphological identification of Ablabesmyia is challenging, particularly for non-experts. Thus, there is an increasing need for molecular data to improve classification accuracy and phylogenetic analysis. (2) Methods: Our analysis encompassed eight species of Ablabesmyia, a single species of Conchapelopia, one species of Denopelopia, and one species of Thienemannimyia, all originating from China. We then performed a comprehensive analysis of the nucleotide composition, sequence length, and evolutionary rate. (3) Results: All newly assembled mitogenomes displayed a negative GC-skew, indicating a cytosine bias, while most exhibited a positive AT-skew, reflecting an adenine and thymine abundance. All thirteen protein-coding genes (PCGs) featured the conventional start codon ATN, aligning closely with the typical mitochondrial start codon observed in insects. The evolutionary rates of these PCGs can be ordered as follows: ND2 > ATP8 > ND6 > ND4 > ND5 > ND3 > ND4L > ND1 > CYTB > COIII > ATP6 > COII > COI. (4) Conclusions: These newly sequenced mitogenomes exhibit structural features and nucleotide compositions that closely align with those of previously reported Chironomidae species, marking a significant expansion of the chironomid mitogenome database. Full article

Background: Fatty acids (FAs) represent a ubiquitous class of nonpolar alkyl carboxylate metabolites with diverse biological functions. Nutrition, metabolism, and endogenous and exogenous stress influence the overall FA metabolic status and transport via the bloodstream. FAs esterified in lipids are of particular interest, as they represent promising biomarkers of pathological diseases and nutritional status. Methods: Here, we report a validated gas chromatographic-mass spectrometric (GC-MS) method for the quantitative analysis of 32 FAs exclusively bound in esterified lipids. The developed sample preparation protocol comprises three steps using only 5 µL of human serum for Folch extraction, sodium methoxide-catalyzed transesterification in tert-butyl methyl ether, and re-extraction in isooctane prior to a quantitative GC-MS analysis with positive ion chemical ionization (PICI) and selected ion monitoring (SIM). Results: The base-catalyzed transmethylation step was studied for 14 lipid classes and was found to be efficient under mild conditions for all major esterified lipids but not for free FAs, lipid amides, or sphingolipids. To minimize matrix effects and instrument bias, internal fatty acid trideuteromethyl esters (D3-FAME) standards were prepared through isotope-coded derivatization with D3-labeled methylchloroformate/methanol medium mixed with each transmethylated serum extract for the assay. The method was validated according to FDA guidelines and evaluated by analyzing NIST SRM 2378 Serum 1 and sera from three healthy donors. Conclusions: The measured quantitative FA values are consistent with the reference data of SRM 2378, and they demonstrate the application potential of the described method for general FA analysis in esterified lipids as a novel complementary tool for lipidomics, as well as for the analysis of membrane FAs in dry blood spots and red blood cells. Full article

Classroom dialogue analysis is crucial as it significantly impacts both knowledge transmission and teacher–student interactions. Since the inception of classroom analysis research, traditional methods such as manual transcription and coding have served as foundational tools for understanding these interactions. While precise and insightful, these methods are inherently time-consuming, labor-intensive, and susceptible to human bias. Moreover, they struggle to handle the scale and complexity of modern classroom data effectively. In contrast, many contemporary deep learning approaches focus primarily on dialogue classification, but often lack the capability to provide deeper interpretative insights. To address these challenges, this study introduces an automated dialogue analysis system that combines scalability, efficiency, and objectivity in evaluating teaching quality. We first collected a large dataset of classroom recordings from primary and secondary schools in China and manually annotated the dialogues using multiple encoding frameworks. Based on these data, we developed an automated analysis system featuring a novel dialogue classification algorithm that incorporates speaker role information for more accurate insights. Additionally, we implemented innovative visualization techniques to automatically generate comprehensive classroom analysis reports, effectively bridging the gap between traditional manual methods and modern automated approaches. Experimental results demonstrated the system’s high accuracy in distinguishing various types of classroom dialogue. Large-scale analysis revealed key patterns in classroom dynamics, showcasing the strong potential of our system to enhance teaching evaluation and provide valuable insights for improving education practices. Full article

Members of the genus Moelleriella (Hypocreales, Clavicipitaceae) are insect pathogens with specificity for scale insects and whiteflies. However, no mitochondrial genomes are available for these fungi. Here, we assembled seven mitogenomes from M. zhongdongii, M. libera, M. raciborskii, M. gracilispora, M. oxystoma, Moelleriella sp. CGMCC 3.18909, and Moelleriella sp. CGMCC 3.18913, which varied in size from 40.8 to 95.7 Kb. Synteny and codon usage bias was relatively conserved, with the mitochondrial gene arrangement being completely homologous to the gene order of 21 other species within the Hypocreales. Nevertheless, significant intron polymorphism was observed between Moelleriella species. Evolutionary analyses revealed that all 15 core protein–coding genes had ka/ks < 1, indicating purifying selection pressure. Sequence variation within the mitochondrial ATP synthase F0 subunit 6 (atp6) gene showed the largest genetic distance, with the ATP synthase F0 subunit 9 (atp9) gene showing the smallest. Comparative analyses of mitogenomes revealed that introns were the primary factor contributing to the size variation in Moelleriella and, more broadly, within Hypocreales mitogenomes. Phylogenetic analyses indicated that the seven Moelleriella species examined form a well–supported clade, most closely related to Metarhizium. These data present the first mitogenomes from Moelleriella and further advance research into the taxonomy, origin, evolution, and genomics of Moelleriella. Full article

An accurate estimation of Differential Code Bias (DCB) is essential for high-precision applications of the Global Navigation Satellite System (GNSS) and for the precise determination of GNSS-derived total electron content (TEC). This study leverages BeiDou Navigation Satellite System (BDS) and Global Positioning System (GPS) dual-frequency observations of the China Seismo-electromagnetic Satellite (CSES) from day of the year (DOY) 201 to DOY 232 in 2018, we evaluate the quality of CSES onboard GNSS observations, improve the data preprocessing method, and use the least-squares to estimate DCBs for both GNSS satellites and CSES receivers. A comprehensive analysis of the estimation accuracy is presented, revealing that DCBs for BDS satellites, derived from joint BDS and GPS observations, exhibit superior consistency compared to those from single BDS observations. Notably, the stability of DCBs for the CSES BDS receiver as well as for BDS GEO, IGSO, and MEO satellites has been significantly enhanced by 70%, 14%, 22%, and 23%, respectively. Conversely, the consistency of GPS satellite DCBs estimated from joint observations shows a decline when compared to the DCB products from the Center for Orbit Determination in Europe (CODE) and the Chinese Academy of Sciences (CAS). When fewer than nine satellites are tracked daily and nighttime observations are under 25%, estimation errors increase. The optimal DCB estimation is achieved with a cutoff elevation angle set at 10°, with monthly mean DCB values for CSES GPS and BDS receivers determined to be −2.193 ns and −1.099 ns, respectively, accompanied by root mean square errors (RMSEs) of 0.10 ns and 0.31 ns. The highest accuracy of DCBs estimated by the single-GPS scheme is corroborated by examining the occurrence of negative vertical total electron content (VTEC) percentages. Full article