Conversational Patterns Research Articles

Organization of Female Turn Taking Pattern in Urdu Conversations

This article looks at the norms of turn-taking in Urdu discourse as an aspect of female communication tactics. A "turn-talking game" is what Tannen (1984) describes communication as being. This study aims to discover the structure of female turn-taking patterns in Urdu conversations and the distribution of turns within them. While the data does demonstrate that speakers switch and turn size and ordering might fluctuate, the majority of the time, just one side is speaking at a time. Different methods are employed to distribute turns, and those transitions are meticulously coordinated. The research also considers overlapping and pauses in Urdu conversation, but they do not distort the turn-taking pattern. Instead, these elements are ruled preserving.

Hydrothermal Treatment Effectively Inhibits the Conversion of Rutin to Quercetin in Flos Sophorae Immaturus Compared With Dry Heating: Based on Degrading Kinetic Analysis

ABSTRACTFlos sophorae immaturus (FSI) is rich in polyphenols and has been consumed as a health food. This study aimed to explore the impacts of dry heating (DH) and hydrothermal treatment (HT) on the phenolic content of FSI and their degrading kinetics, thereby elucidating the phenolic conversion patterns during processing at different temperatures. Results showed that DH led to a substantial decrease in total flavonoids and total phenols in FSI from 5 to 60 min at a maximum of 210°C. Conversely, FSI subjected to HT exhibited an opposing trend at a maximum of 90°C. Moreover, the highest rutin content (170.2 mg/g) was observed in HT‐FSI at 90°C for 120 min, whereas quercetin exhibited the lowest content (5.4 mg/g), indicating a potential termination of conversion. Correspondingly, the rutin‐degrading enzyme (RDE) activity of HT‐FSI (0.814 U) decreased beginning at 50°C for 120 min and reached the lowest level (0.015 U) when treated at 90°C for 60 min. In contrast, the RDE of DH‐FSI (0.463 U) was inactivated under the same processing conditions, yet its lowest level (0.041 U) remained significantly higher than that of HT‐FSI. Furthermore, the first‐order kinetics revealed that the activation energy of rutin extracted from the HT‐FSI (63.15 kJ/mol) was higher than that of the DH‐FSI (26.97 kJ/mol), suggesting that rutin conversion was much more difficult during HT. Overall, treating FSI with HT at 90°C for 60 min might be an effective method for rutin retention by inactivating RDE activity.

Ecological analysis and multi-scenario simulation of Yellow River Delta wetland under clearing of Spartina alterniflora

In 2022, China released the Special Action Plan for the Control of Spartina alterniflora (2022-2025) with the goal of completely clearing S. alterniflora from China's coastal wetlands. It is crucial to conduct a thorough analysis of wetlands under artificial intervention and obtain reliable future wetland simulation results. The Yellow River Delta wetland is one of China's important wetland reserves, has faced severe impacts from S. alterniflora invasion over the past decade. This study focuses on the Yellow River Delta wetland, utilizing Landsat imagery and a combined object-oriented and pixel-based approach to achieve wetland mapping from 2013 to 2023. Through wetland analysis, we designed scenarios for natural development, ecological priority, farmland protection, and combined development. The patch generating land use simulation model was used to simulate wetland scenarios for 2030 and analyze factors influencing wetland use cover change and future conversion patterns. The results indicate that between 2013 and 2022, native vegetation was impacted by the invasion of S. alterniflora, with Suaeda glauca being the most affected. In 2023, the removal of S. alterniflora was effective, reducing its area by 42.37km2 compared to pre-removal conditions. In all three scenarios, the area of Phragmites australis increased and is expected to dominate the wetlands, while the live space of other native salt marsh vegetation has also been restored. However, the predictions indicate that S. alterniflora still poses a potential threat of expansion in the future, necessitating continuous monitoring of its dynamics. We recommend implementing zoned management of the wetland, balancing ecological restoration in coastal areas with agricultural development in the western regions.

Wheat Tae-MIR1118 Constitutes a Functional Module With Calmodulin TaCaM2-1 and MYB Member TaMYB44 to Modulate Plant Low-N Stress Response.

Distinct target genes are modulated by microRNA members and affect various biological processes associated with abiotic stress responses in plants. In this study, we characterized a functional module comprising miRNA/target and a downstream MYB transcription factor partner, Tae-MIR1118/TaCaM2/TaMYB44, in Triticum aestivum to mediate the plant low-nitrogen (N) stress response. Dual luciferase (LUC) assay and expression analysis indicated that TaCaM2 is regulated by Tae-MIR1118 through a posttranscriptional cleavage mechanism. Reporter LUC activity in N. benthamiana leaves co-transformed with effector CaMV35S::Tae-MIR1118 and reporter TaCaM2::LUC was significantly reduced, and the transcripts of Tae-MIR1118 and TaCaM2 in tissues exhibited converse expression patterns under varying N levels. Specifically, the transcripts of Tae-MIR1118 decreased, whereas those of TaCaM2 increased under low-N stress in a temporal-dependent manner. Yeast two-hybrid, bimolecular fluorescence complementation (BiFC) and co-immunoprecipitation (Co-IP) assays indicated that TaCaM2 interacted with the MYB transcription factor TaMYB44. Transgene analysis revealed the negative roles of Tae-MIR1118 and the positive functions of TaCaM2 and TaMYB44 in regulating plants for low-N stress adaptation by modulating glutamine synthetase activity, N uptake capacity, and root morphology. Yeast one-hybrid, transcriptional activation, and chromatin immunoprecipitation-quantitative polymerase chain reaction (ChIP-PCR) assays indicated that TaMYB44 could bind to the promoters of genes TaGS2.2, TaNRT2.1, and TaPIN4 and induce transcription of these stress-defensive genes. Knockdown of these three genes reduced GS activity, N accumulation, and root growth traits in plants subjected to N starvation. The yield in the wheat variety panel was highly correlated with the transcripts of Tae-MIR1118, TaCaM2, and TaMYB44 in plants cultured under N-deprived field conditions. A major haplotype of Tae-MIR1118, TaMIR1118-Hap1, enhanced the low-N stress tolerance of plants. Our findings indicate that the Tae-MIR1118/TaCaM2/TaMYB44 pathway primarily affects the low-N response of plants by modulating associated physiological processes.

Children’s healthy and unhealthy food intake related to parental fear of COVID-19, family communication patterns, and parental controlling feeding practices

ABSTRACT Background The COVID-19 pandemic in 2020 changed the daily lives of families, including their food environments. We tested a conceptual model of potential influences on children’s dietary intake under these conditions. Methods 310 (51% fathers) parents with children ages 5–12 were recruited for an online study. Parents completed questionnaires to measure fear of COVID-19, family communication patterns, parental controlling feeding practices, and child’s healthy and unhealthy food intake. Structural equation modeling was conducted, including a path analysis and a multi-group analysis to compare mothers and fathers. Results Parental fear of COVID-19 was related to more conversation and conformity-oriented family communication patterns, which were associated with more parental controlling feeding practices. Conversation-oriented communication was related to less, while conformity-oriented communication was related to more unhealthy food intake by children. Conclusion Family communication patterns play an important role in children’s dietary intake. Therefore, it may be useful to help parents adopt positive parenting approaches to influence their children’s healthy development.

Conversational Agent Utilization Patterns of Individuals with Autism Spectrum Disorder

AbstractIndividuals with autism spectrum disorder (ASD) face unique challenges in their social interactions. The use of conversational agents (CA) can provide support and help reduce barriers to care. However, research on CA’s by individuals with ASD is limited. The present study sought to better understand CA utilization patterns by users with ASD. A subset of data was collected from users of Wysa, a mental health CA. Engagement with the CA, utilization of offered mental health interventions (CA tools), collection of energy scores, depression (PHQ-9), and anxiety (GAD-7) outcomes were gathered and analyzed. Users engaged with Wysa on average 8.59 days and had a median of 97 conversational exchanges. Almost half of the users utilized at least one of the 230 tools offered. The most frequently used interventions focused on mindfulness, thought recording, sleep, grounding, and social support. Energy scores were reported on average 10.59 times, and the mean energy score was 42.77 out of 100. Mean baseline PHQ-9 and GAD-7 scores were 10.34 and 8.81, respectively. Overall, the current findings show that users with ASD engaged regularly with a CA, despite its targeted design for other mental health concerns such as depression and anxiety, rather than ASD. If users with ASD engage with these types of resources, this could become a new avenue of support to a population facing multiple challenges to accessing treatment.

Treatment with mTOR Inhibitors as primary immunosuppression after combined heart and kidney transplantation

Abstract Background It has been hypothesized that combined heart and kidney transplantation (HKT) may lead to immune modulation and attenuation of cardiac allograft vasculopathy (CAV) progression. Sirolimus (SRL) has been shown to mitigate the progression of CAV and confer renal protection. With the increasing use of SRL as primary immunosuppression in heart transplant (HT) recipients, the effect of HKT on CAV progression compared to HT-only remains undetermined. Purpose We sought to investigate the patterns of conversion from calcineurin inhibitors (CNI) to SRL, and its impact on CAV progression and outcomes in HKT compared to HT-only in a cohort with frequent use of SRL as primary immunosuppression. Methods A cohort of 302 patients who underwent either HT only (n=262) or combined HKT (n=40) was analyzed. CAV progression was assessed by measuring the delta (Δ) annual change in plaque volume (PV) normalized to vessel length (PV/VL in mm3/mm) and plaque index (PI) (%) (calculated as the PV to VV ratio) between baseline and last follow-up coronary intravenous ultrasound (IVUS). Clinical adverse outcomes included all-cause death and CAV-associated events. Secondary outcomes included differences in renal function and incidence of SRL-associated proteinuria (defined as Δ urine protein ≥300 mg/24 h at 1 year after conversion to SRL) between HT-only and HKT recipients. Results Overall, 217 (72%) patients were converted from CNI to SRL as primary immunosuppression. HT recipients were more likely to be converted to SRL than combined HKT recipients (74% vs. 55%, P=0.01). HKT was associated with significantly higher ΔPV/VL (P=0.01) and a trend toward a higher ΔPI (P=0.06) than HT-only, but this association was markedly attenuated after adjustment to SRL conversion. HKT was associated with similar risk of death (adjusted hazard ratio [HR] 0.69, 95%CI: 0.28-1.71, P=0.43) and CAV-related events (adjusted HR 0.83, 95% CI: 0.30-2.31, P=0.72). Conversion to SRL was significantly associated with decreased risk of death and CAV-related events in the overall cohort. This association was not modified by the type of organ transplantation (Pinteraction=NS), and without a significant effect on estimated glomerular filtration rate (eGFR) or proteinuria. Conclusions HKT recipients compared to HT-only were less likely to be converted from CNI to SRL-based immunosuppression and had a greater CAV progression but without significant differences in all-cause mortality or CAV-related events. The clinical benefit and safety of conversion to SRL appeared similar in the HKT and isolated HT cohorts.

Reading Comprehension Instruction: Evaluating Our Progress Since Durkin’s Seminal Study

ABSTRACT Purpose: Nearly 50 years ago, Durkin (1978–1979) conducted a seminal observation study on reading comprehension teaching in Grades 3 through 6. She reported that teachers rarely taught reading comprehension (less than 1% of instructional time). Since then, we have gained substantial knowledge about teaching reading comprehension. We aimed to comprehensively review direct observation studies of reading instruction to understand the extent to which recommended comprehension practices are implemented in schools. Method: A systematic search of the extant literature identified 66 observation studies of reading comprehension instruction for children in K–12 schools, including a total of 1,784 teachers. We employed a mixed-method systematic review to address the research questions. Results: Integrated analyses revealed that reading comprehension instruction infrequently aligned with research-based practices. Findings revealed that, on average, 23% of instructional time during reading/language arts instruction was dedicated to reading comprehension. Like Durkin’s study (1978–1979), the results indicated that teachers spent much of this time engaging in initiation-response-evaluation conversation patterns rather engaging students in extensive discussion of text or teaching knowledge or practices (e.g. text structure, reading comprehension strategies) that support reading comprehension. However, analyses suggested that studies conducted after 2000 reported more research-based reading comprehension practices than earlier studies. Conclusions: These findings suggest a substantial gap persists between the reading comprehension practices identified as research-based and those observed in typical practice. There is a need for renewed efforts to prioritize reading comprehension instruction in policy and practice.

Qualitative Analysis of Responses in Estimating Older Adults Cognitive Functioning in Spontaneous Speech: Comparison of Questions Asked by AI Agents and Humans.

Artificial Intelligence (AI) technology is gaining attention for its potential in cognitive function assessment and intervention. AI robots and agents can offer continuous dialogue with the elderly, helping to prevent social isolation and support cognitive health. Speech-based evaluation methods are promising as they reduce the burden on elderly participants. AI agents could replace human questioners, offering efficient and consistent assessments. However, existing research lacks sufficient comparisons of elderly speech content when interacting with AI versus human partners, and detailed analyses of factors like cognitive function levels and dialogue partner effects on speech elements such as proper nouns and fillers. This study investigates how elderly individuals' cognitive functions influence their communication patterns with both human and AI conversational partners. A total of 34 older people (12 men and 22 women) living in the community were selected from a silver human resource centre and day service centre in Tokyo. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), and participants engaged in semi-structured daily conversations with both human and AI partners. The study examined the frequency of fillers, proper nouns, and "listen back" in conversations with AI and humans. Results showed that participants used more fillers in human conversations, especially those with lower cognitive function. In contrast, proper nouns were used more in AI conversations, particularly by those with higher cognitive function. Participants also asked for explanations more often in AI conversations, especially those with lower cognitive function. These findings highlight differences in conversation patterns based on cognitive function and the conversation partner being either AI or human. These results suggest that there are differences in conversation patterns depending on the cognitive function of the participants and whether the conversation partner is a human or an AI. This study aims to provide new insights into the effective use of AI agents in dialogue with the elderly, contributing to the improvement of elderly welfare.

X-raying Human Rights Violations by Government Agencies in Nigeria's Democratic System of Government

Respect for human rights is diminishing within Nigeria's democracy, with the political elite often acting with impunity and ignoring the rule of law. Gender discrimination and exclusion of marginalized citizens persist in politics. This study investigated human rights violations by government agencies in Nigeria, with the aim of enhancing understanding of the situation and proposing policy recommendations for promoting human rights. The study employed a descriptive survey research design, with 150 individuals randomly selected from government agencies in Lagos state. Data was collected through in-depth interviews, with the analysis focusing on patterns in conversations, text, and activities. The findings reveal the emotional and systemic impacts of government agencies' human rights violations, calling for sweeping reforms and enhanced accountability. Respondents also stress the complexity of accountability challenges and advocate for a collaborative approach. They offer valuable strategies, including government reforms, civil society involvement, education and awareness, learning from successful examples, and using media and digital platforms to promote human rights and accountability. The study concluded that the findings underscore the urgent need for comprehensive and collaborative efforts to address the multifaceted challenges of human rights violations in Nigeria. This requires the involvement of all stakeholders, including the government, civil society organizations, and the media. Sweeping reforms and enhanced accountability mechanisms are essential to ensure justice and the protection of human rights for all Nigerians. This study provides a valuable overview of human rights violations by government agencies in Nigeria's democratic system of government. The findings highlight the need for urgent action to address the root causes of these violations and to ensure accountability for perpetrators. The study's recommendations offer a roadmap for promoting human rights and strengthening democracy in Nigeria.

A knowledge-Aware NLP-Driven conversational model to detect deceptive contents on social media posts

The widespread dissemination of deceptive content on social media presents a substantial challenge to preserving authenticity and trust. The epidemic growth of false news is due to the greater use of social media to transmit news, rather than conventional mass media such as newspapers, magazines, radio, and television. Humans' incapacity to differentiate among true and false facts exposes fake news as a threat to logical truth, democracy, journalism, and government credibility. Using combination of advanced methodologies, Deep learning (DL) methods, and Natural Language Processing (NLP) approaches, researchers and technology developers attempt to make robust systems proficient in discerning the subtle nuances that betray deceptive intent. Analysing conversational linguistic patterns of misleading data, these techniques’ purpose to progress the resilience of social platforms against the spread of deceptive content, eventually contributing to an additional informed and trustworthy online platform. This paper proposed a Knowledge-Aware NLP-Driven AlBiruni Earth Radius Optimization Algorithm with Deep Learning Tool for Enhanced Deceptive Content Detection (BER-DLEDCD) algorithm on Social Media. The purpose of the BER-DLEDCD system is to identify and classify the existence of deceptive content utilizing NLP with optimal DL model. In the BER-DLEDCD technique, data pre-processing takes place to change the input data into compatible format. Furthermore, the BER-DLEDCD approach applies hybrid DL technique encompassing Convolutional Neural Network with Long Short-Term Memory (CNN-LSTM) methodology for deceptive content detection. Moreover, the BER approach has been deployed to boost hyperparameter choice of the CNN-LSTM technique which leads to enhanced detection performance. The simulation outcome of the BER-DLEDCD system has been examined employing benchmark database. The extensive outcomes stated the BER-DLEDCD system achieved excellent performance with the accuracy of 94 %, 94.83 % precision, 94.30 % F-score with other recent approaches.

Surviving is just the beginning: Exposing unmet needs of cancer survivors through a patient-informed lens.

214 Background: Despite advancements in survivorship care over the past two decades, cancer survivors continue to grapple with unmet needs that impact their quality of life. While survivorship care plans and clinical interventions have made progress in addressing physical health concerns, a substantial gap remains in delivering comprehensive biopsychosocial support. For the growing population of cancer survivors, varied degrees of toxicity and trauma persist. Research shows only 40% of survivors feel their healthcare providers adequately support their transition to post-treatment care (1). Methods: We conducted a qualitative study among survivors of varying Dx, grouped into 3 cohorts, with a two-pronged approach: semi-structured focus groups using “Experience Group” methodology identified domains of care gaps; followed by in-person, human-design workshops mapping perceived gaps in care based on lived experiences. We held 4 Experience Groups; posing open-ended questions (i.e., “what was a good day like w/ cancer?”) to 21 participants. A trained facilitator guided discussion based on emerging patterns in conversation. We utilized an inductive approach: data gathered from groups was used to define & develop codes to categorize responses from in-person workshops into domains & subdomains for care gaps. We held 3, 3-hour workshops in 9 months. Survivors were asked to explore “challenges or unmet needs in extended and long term survivorship.” We collected 628 qualitative data points from 24 total participants. Results: Participants identified 66 discreet unmet needs across 7 predominant domains: psychological/emotional, physical health and safety, social/relational, practical, education/information, financial, and existential/spiritual. Most common themes among cohorts included: 1) Mental health concerns: managing anxiety, depression, and existential dread. 2) Physical health: managing long-term effects, daily functioning, and quality of life. 3) Social health: building and maintaining support networks, caregiver support and healthy relationships. Second most common themes included: practical day-to-day concerns, financial and sexual health.Notably, young adult survivors expressed heightened financial and existential concerns. Conclusions: While these data exemplify common themes in current literature, they also point to the deep gap between clinical survivorship care plans and real-life support. These findings, while specific to Central Texas, hold implications for survivorship care nationally: increasing awareness and timely use of interdisciplinary interventions delivered outside the clinical setting are needed to comprehensively address the diverse needs of survivors. 1. NCCS, 2022.

Seasonal variation of serum potassium and related prescription pattern: an ecological time series

AimsTo assess if ambient temperature-related effects on serum potassium levels impact clinical decision-making.MethodsThis study is an ecological time series consisiting of 1 218 453 adult patients with at least one...

Alternative double strand break repair pathways shape the evolution of high recombination in the honey bee, Apis mellifera.

Social insects, particularly honey bees, have exceptionally high genomic frequencies of genetic recombination. This phenomenon and underlying mechanisms are poorly understood. To characterise the patterns of crossovers and gene conversion in the honey bee genome, a recombination map of 187 honey bee brothers was generated by whole-genome resequencing. Recombination events were heterogeneously distributed without many true hotspots. The tract lengths between phase shifts were bimodally distributed, indicating distinct crossover and gene conversion events. While crossovers predominantly occurred in G/C-rich regions and seemed to cause G/C enrichment, the gene conversions were found predominantly in A/T-rich regions. The nucleotide composition of sequences involved in gene conversions that were associated with or distant from crossovers corresponded to the differences between crossovers and gene conversions. These combined results suggest two types of DNA double-strand break repair during honey bee meiosis: non-canonical homologous recombination, leading to gene conversion and A/T enrichment of the genome, and the canonical homologous recombination based on completed double Holliday Junctions, which can result in gene conversion or crossover and is associated with G/C bias. This G/C bias may be selected for to balance the A/T-rich base composition of eusocial hymenopteran genomes. The lack of evidence for a preference of the canonical homologous recombination for double-strand break repair suggests that the high genomic recombination rate of honey bees is mainly the consequence of a high rate of double-strand breaks, which could in turn result from the life history of honey bees and their A/T-rich genome.

On reversal of wave-generated longshore currents at tidal frequencies on dissipative beaches contiguous to a mesotidal estuary, S.E coast of Nigeria

Reversals in wave-generated longshore currents in surf zones occur at different temporal and spatial scales. Along coastlines with tidal channel openings with well-developed mouth bars or ebb-tidal deltas, the reversal mechanism is often attributed to the mouth bar – induced refraction of the shoaling waves. This reversal mechanism is characterized by convergence of longshore currents from the adjoining surf zones at the mouth of the tidal channel. Simultaneous half-hourly monitoring of wave-generated longshore currents over 50 successive (daylight) semi-diurnal tidal cycles in beach surf zones adjoining the Qua Iboe River estuary, S.E coast of Nigeria showed the above reversal pattern during flooding stage only. The converse pattern, where the surf zone longshore currents diverged away from the mouth of the estuary, was observed during ebbing stage. Both surf zones showed flow direction inversion with respect to each other, with velocity vector correlation coefficient r > − 0.8 in over 80 % of the data set. Instances of comparable flow direction (<10 %) were also recorded. Tidal processes are implicated in the documented results. Direction-averaged longshore current velocities, typically in the 15–60 cm/s range, attained highest values in both surf zones at about spring tide phase. Also, tidal cycle-residual longshore current maximum and minimum velocities occurred close to spring and neap tide, respectively. Only 30 % of the residual velocities were eastward directed in the up-drift surf zone as against 80 % in the down-drift counterpart. Given the prevailing southwesterly waves, the present results negate the assertion that reversal in longshore current direction in this offset shoreline setting is exclusively a consequence of wave refraction by mouth bar morphology. The reversing pattern of the longshore currents over a tidal cycle is well explained by incorporating interacting effects of shoaling waves with tide-induced oscillations in water level as well as the estuarine flow.

AI-Driven Patient Education in Chronic Kidney Disease: Evaluating Chatbot Responses against Clinical Guidelines.

Chronic kidney disease (CKD) patients can benefit from personalized education on lifestyle and nutrition management strategies to enhance healthcare outcomes. The potential use of chatbots, introduced in 2022, as a tool for educating CKD patients has been explored. A set of 15 questions on lifestyle modification and nutrition, derived from a thorough review of three specific KDIGO guidelines, were developed and posed in various formats, including original, paraphrased with different adverbs, incomplete sentences, and misspellings. Four versions of AI were used to answer these questions: ChatGPT 3.5 (March and September 2023 versions), ChatGPT 4, and Bard AI. Additionally, 20 questions on lifestyle modification and nutrition were derived from the NKF KDOQI guidelines for nutrition in CKD (2020 Update) and answered by four versions of chatbots. Nephrologists reviewed all answers for accuracy. ChatGPT 3.5 produced largely accurate responses across the different question complexities, with occasional misleading statements from the March version. The September 2023 version frequently cited its last update as September 2021 and did not provide specific references, while the November 2023 version did not provide any misleading information. ChatGPT 4 presented answers similar to 3.5 but with improved reference citations, though not always directly relevant. Bard AI, while largely accurate with pictorial representation at times, occasionally produced misleading statements and had inconsistent reference quality, although an improvement was noted over time. Bing AI from November 2023 had short answers without detailed elaboration and sometimes just answered "YES". Chatbots demonstrate potential as personalized educational tools for CKD that utilize layman's terms, deliver timely and rapid responses in multiple languages, and offer a conversational pattern advantageous for patient engagement. Despite improvements observed from March to November 2023, some answers remained potentially misleading. ChatGPT 4 offers some advantages over 3.5, although the differences are limited. Collaboration between healthcare professionals and AI developers is essential to improve healthcare delivery and ensure the safe incorporation of chatbots into patient care.

Little evidence for homoeologous gene conversion and homoeologous exchange events in Gossypium allopolyploids.

A complicating factor in analyzing allopolyploid genomes is the possibility of physical interactions between homoeologous chromosomes during meiosis, resulting in either crossover (homoeologous exchanges) or non-crossover products (homoeologous gene conversion). Homoeologous gene conversion was first described in cotton by comparing SNP patterns in sequences from two diploid progenitors with those from the allopolyploid subgenomes. These analyses, however, did not explicitly consider other evolutionary scenarios that may give rise to similar SNP patterns as homoeologous gene conversion, creating uncertainties about the reality of the inferred gene conversion events. Here, we use an expanded phylogenetic sampling of high-quality genome assemblies from seven allopolyploid Gossypium species (all derived from the same polyploidy event), four diploid species (two closely related to each subgenome), and a diploid outgroup to derive a robust method for identifying potential genomic regions of gene conversion and homoeologous exchange. We found little evidence for homoeologous gene conversion in allopolyploid cottons, and that only two of the 40 best-supported events were shared by more than one species. We did, however, reveal a single, shared homoeologous exchange event at one end of chromosome 1, which occurred shortly after allopolyploidization but prior to divergence of the descendant species. Overall, our analyses demonstrated that homoeologous gene conversion and homoeologous exchanges are uncommon in Gossypium, affecting between zero and 24 genes per subgenome (0.0-0.065%) across the seven species. More generally, we highlighted the potential problems of using simple four-taxon tests to investigate patterns of homoeologous gene conversion in established allopolyploids.

Language in interaction: turn-taking patterns in conversations involving individuals with schizophrenia

Individuals with schizophrenia generally show difficulties in interpersonal communication. Linguistic analyses shed new light on speech atypicalities in schizophrenia. However, very little is known about conversational interaction management by these individuals. Moreover, the relationship between linguistic features, psychopathology, and patients’ subjectivity has received limited attention to date. We used a novel methodology to explore dyadic conversations involving 58 participants (29 individuals with schizophrenia and 29 control persons) and medical doctors. High-quality stereo recordings were obtained and used to quantify turn-taking patterns. We investigated psychopathological dimensions and subjective experiences using the Positive and Negative Syndrome Scale for Schizophrenia (PANSS), the Examination of Anomalous Self Experience scale (EASE), the Autism Rating Scale (ARS) and the Abnormal Bodily Phenomena questionnaire (ABPq). Different turn-taking patterns of both patients and interviewers characterised conversations involving individuals with schizophrenia. We observed higher levels of overlap and mutual silence in dialogues with the patients compared to dialogues with control persons. Mutual silence was associated with negative symptom severity; no dialogical feature was correlated with anomalous subjective experiences. Our findings suggest that individuals with schizophrenia display peculiar turn-taking behaviour, thereby enhancing our understanding of interactional coordination in schizophrenia.

Harnessing large language models' zero-shot and few-shot learning capabilities for regulatory research.

Large language models (LLMs) are sophisticated AI-driven models trained on vast sources of natural language data. They are adept at generating responses that closely mimic human conversational patterns. One of the most notable examples is OpenAI's ChatGPT, which has been extensively used across diverse sectors. Despite their flexibility, a significant challenge arises as most users must transmit their data to the servers of companies operating these models. Utilizing ChatGPT or similar models online may inadvertently expose sensitive information to the risk of data breaches. Therefore, implementing LLMs that are open source and smaller in scale within a secure local network becomes a crucial step for organizations where ensuring data privacy and protection has the highest priority, such as regulatory agencies. As a feasibility evaluation, we implemented a series of open-source LLMs within a regulatory agency's local network and assessed their performance on specific tasks involving extracting relevant clinical pharmacology information from regulatory drug labels. Our research shows that some models work well in the context of few- or zero-shot learning, achieving performance comparable, or even better than, neural network models that needed thousands of training samples. One of the models was selected to address a real-world issue of finding intrinsic factors that affect drugs' clinical exposure without any training or fine-tuning. In a dataset of over 700000 sentences, the model showed a 78.5% accuracy rate. Our work pointed to the possibility of implementing open-source LLMs within a secure local network and using these models to perform various natural language processing tasks when large numbers of training examples are unavailable.

Of the importance to reconsider individual variability in infant studies: Family traits do impact turn-taking perception in 6-month-olds.

Turn-taking is a universal pattern of human conversations characterized by a fast exchange of turns between speakers and an avoidance of overlaps. Language is embedded in this conversational skill acquired well before it during infancy, through everyday interactions with caregivers. The earliness of this skill and its link with language allows us to test whether social environment shapes early language development. We therefore study turn-taking perception of 6-month-old infants by measuring their gazes during video presentation of three different conversational situations where the turn is explicitly given, normally taken or taken with an overlap. We studied 51 infants to cover several family and infant characteristics: infants' sex, presence of siblings, and family socioeconomic status (SES). We found that infants looked more at the second speaker when she overlapped the first speaker than in the other situations, but not all infants were equally sensitive. Indeed, infants from high-SES families reacted differently to the three situations, while infants from the two lower SES categories did not. Also, only singletons reacted differently by looking more at the second speaker after the overlapping and turn-giving situations, and not after the turn-taking situation. Our results emphasize the importance of early social experiences on language development.