"Unable to Feed My Hungry Child": Experiences of Mothers Caring for Children With Prader-Willi Syndrome.

Mothers' experiences of caring for children with Prader-Willi Syndrome (PWS) is largely unknown. With no treatment for PWS, parents undertake (extra)ordinary care practices to keep children safe from overeating and self harm. Knowledge of these care practices could lead to effective interventions. Narrative inquiry was used to study everyday experience with Canadian mothers. Participants cared for a child 3 to 17 years old who had hyperphagia. Participants were interviewed 8 to 12 times each over the course of a year. Narrative accounts were co-composed through a collaborative process of analysis. Engaging with participants' everyday experiences amplified complex care needs for families and gaps in health and social care systems. Narrative threads focused on engaging in (extra)ordinary care practices, rigid care work to keep children healthy and safe, tension from others while enacting these care practices, and difficulty conforming to social expectations with childrearing and care work. Recommendations for practice and policy include (a) shifting from untenable care practices, (b) reconceptualizing care work, and (c) alternative care models.

Uncovering the determinants of brain functioning, behavior and their interplay in the light of context.

Notwithstanding the huge progress in molecular and cellular neuroscience, our ability to understand the brain and develop effective treatments promoting mental health is still limited. This can be partially ascribed to the reductionist, deterministic and mechanistic approaches in neuroscience that struggle with the complexity of the central nervous system. Here, I introduce the Context theory of constrained systems proposing a novel role of contextual factors and genetic, molecular and neural substrates in determining brain functioning and behavior. This theory entails key conceptual implications. First, context is the main driver of behavior and mental states. Second, substrates, from genes to brain areas, have no direct causal link to complex behavioral responses as they can be combined in multiple ways to produce the same response and different responses can impinge on the same substrates. Third, context and biological substrates play distinct roles in determining behavior: context drives behavior, substrates constrain the behavioral repertoire that can be implemented. Fourth, since behavior is the interface between the central nervous system and the environment, it is a privileged level of control and orchestration of brain functioning. Such implications are illustrated through the Kitchen metaphor of the brain. This theoretical framework calls for the revision of key concepts in neuroscience and psychiatry, including causality, specificity and individuality. Moreover, at the clinical level, it proposes treatments inducing behavioral changes through contextual interventions as having the highest impact to reorganize the complexity of the human mind and to achieve a long-lasting improvement in mental health.

The Effects of Phonological Complexity on Word Production in French-Speaking Children.

Word complexity indices, such as the Index of Phonetic Complexity (IPC) and the Word Complexity Measure (WCM), code a word in terms of featural and structural properties that pose difficulty in phonological development. Studies have investigated the influence of complexity indices on vocabulary development; however, few have examined their influence on consonant accuracy. Furthermore, these indices were developed for English-speaking children and have not been widely applied to other languages. This study investigates whether a word's phonological complexity influences how accurately it is produced in French-speaking children. Four databases consisting of the productions of children (n = 74), aged 1;11 to 4;9, were analyzed. Words were coded in terms of the IPC, WCM, and parameters that add complexity during phonological development. Using mixed-effects logistic regression, we examined whether phonological complexity as determined by the IPC, WCM, or by alternative indices better accounts for the influence of complexity on production. We also investigated whether the accuracy of a target sound/structure was influenced by a word's complexity. Results indicated that complexity based on the IPC or WCM significantly influenced consonant accuracy; however, indices tapping fewer features provided superior model fit. At younger ages, the presence of fricatives/liquids and, at all ages, the presence of alveopalatal fricatives, codas, and clusters significantly influenced accuracy. Findings were inconclusive as to whether whole word complexity influenced the accuracy of a target sound/structure. Results suggest that current complexity indices provide only approximate indications of how featural and structural properties of words influence production.

Control of Kinetic Pathways toward Supramolecular Chiral Polymorphs for Tunable Circularly Polarized Luminescence.

An amphiphilic aza-BODIPY dye (S)-1 bearing two chiral hydrophilic side chains with S-stereogenic centers was synthesized. This dye exhibited kinetic-controlled self-assembly pathways and supramolecular chiral polymorphism properties in MeOH/H2O (9/1, v/v) mixed solvent. The (S)-1 monomers first aggregated into a kinetic controlled, off-pathway species Agg. A, which was spontaneously transformed into an on-pathway metastable aggregate (Agg. B) and subsequently into the thermodynamic Agg. C. The three aggregate polymorphs of dye (S)-1 displayed distinct optical properties and nanomorphologies. In particular, chiral J-aggregation characteristics were observed for both Agg. B and Agg. C, such as Davydov-split absorption bands (Agg. B), extremely sharp and intense J-band with large bathochromic shift (Agg. C), non-diminished fluorescence upon aggregation, as well as strong bisignated Cotton effects. Moreover, the AFM and TEM studies revealed that Agg. A had the morphology of nanoparticle while fibril or rod-like helical nanostructures with left-handedness were observed respectively for Agg. B and Agg. C. By controlling the kinetic transformation process from Agg. B to Agg. C, thin films consisting of Agg. B and Agg. C with different ratios were prepared, which displayed tunable CPL with emission maxima at 788 - 805 nm and g-factors between -4.2 × 10-2 and -5.1 × 10-2.

Designing eHealth interventions for children with complex care needs requires continuous stakeholder collaboration and co-creation.

Objective: Hospital-to-home (H2H) transitions challenge families of children with medical complexity (CMC) and healthcare professionals (HCP). This study aimed to gain deeper insights into the H2H transition process and to work towards eHealth interventions for its improvement, by applying an iterative methodology involving both CMC families and HCP as end-users. Methods: For 20-weeks, the Dutch Transitional Care Unit consortium collaborated with the Amsterdam University of Applied Sciences, HCP, and CMC families. The agile SCREAM approach was used, merging Design Thinking methods into five iterative sprints to stimulate creativity, ideation, and design. Continuous communication allowed rapid adaptation to new information and the refinement of solutions for subsequent sprints. Results: This iterative process revealed three domains of care - care coordination, social wellbeing, and emotional support - that were important to all stakeholders. These domains informed the development of our final prototype, 'Our Care Team', an application tailored to meet the H2H transition needs for CMC families and HCP. Conclusion: Complex processes like the H2H transition for CMC families require adaptive interventions that empower all stakeholders in their respective roles, to promote transitional care that is anticipatory, rather than reactive. Innovation: A collaborative methodology is needed, that optimizes existing resources and knowledge, fosters innovation through collaboration while using creative digital design principles. This way, we might be able to design eHealth solutions with end-users, not just for them.

Non-stationary Bayesian spatial model for disease mapping based on sub-regions.

This paper aims to extend the Besag model, a widely used Bayesian spatial model in disease mapping, to a non-stationary spatial model for irregular lattice-type data. The goal is to improve the model's ability to capture complex spatial dependence patterns and increase interpretability. The proposed model uses multiple precision parameters, accounting for different intensities of spatial dependence in different sub-regions. We derive a joint penalized complexity prior to the flexible local precision parameters to prevent overfitting and ensure contraction to the stationary model at a user-defined rate. The proposed methodology can be used as a basis for the development of various other non-stationary effects over other domains such as time. An accompanying R package fbesag equips the reader with the necessary tools for immediate use and application. We illustrate the novelty of the proposal by modeling the risk of dengue in Brazil, where the stationary spatial assumption fails and interesting risk profiles are estimated when accounting for spatial non-stationary. Additionally, we model different causes of death in Brazil, where we use the new model to investigate the spatial stationarity of these causes.

Clinical Productivity and Patient Complexity of Academic Rhinologists: An Analysis of Medicare Metrics.

INTRODUCTION: Current data regarding reimbursement trends in Medicare services and the complexity of patients treated as physicians' progress in their academic career are conflicting. In otolaryngology, there are no data examining these metrics. METHODS: Medicare services, reimbursement, and patient complexity risk scores (based on hierarchical condition category coding) of US rhinology fellowship-trained faculty were stratified and compared by rank and years in practice. RESULTS: A cohort of 209 rhinologists were included. Full professors were reimbursed more per service than assistant professors ($791.53 [$491.69-1052.46] vs. $590.34 [$429.91-853.07] p = 0.045) and had lower risk scores (1.37 [1.26-1.52] vs. 1.49 [1.29-1.68], p = 0.013). Full professors had similar risk scores to associate professors (1.47 [1.25-1.64], p = 0.14). Full professors ($791.53 [$491.69-1,052.46], p < 0.001), associate professors ($706.85 [$473.48-941.15], p < 0.001), and assistant professors ($590.34 [$429.91-853.07], p < 0.001) were all reimbursed more per service than non-ranked faculty ($326.08 [$223.37-482.36]). As a cohort, significant declines in risk scores occurred within the 10th-14th year of practice (p = 0.032) and after the 20th year (p = 0.038). Years in practice were inversely correlated with risk score (R = -0.358, p < 0.001). CONCLUSION: Full professors were reimbursed more per service and treated less comorbid Medicare patients than junior academic colleagues. Patient comorbidity was correlated negatively with years in practice, with significant drops in mid and late career. Rhinologists employed at academic institutions had greater total reimbursement and reimbursement per service than non-ranked faculty. LEVEL OF EVIDENCE: N/A Laryngoscope, 2024.

Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.

INTRODUCTION: Intravenous (IV) medications are a fundamental cause of fluid overload (FO) in the intensive care unit (ICU); however, the association between IV medication use (including volume), administration timing, and FO occurrence remains unclear. METHODS: This retrospective cohort study included consecutive adults admitted to an ICU ≥72 hours with available fluid balance data. FO was defined as a positive fluid balance ≥7% of admission body weight within 72 hours of ICU admission. After reviewing medication administration record (MAR) data in three-hour periods, IV medication exposure was categorized into clusters using principal component analysis (PCA) and Restricted Boltzmann Machine (RBM). Medication regimens of patients with and without FO were compared within clusters to assess for temporal clusters associated with FO using the Wilcoxon rank sum test. Exploratory analyses of the medication cluster most associated with FO for medications frequently appearing and used in the first 24 hours was conducted. RESULTS: FO occurred in 127/927 (13.7%) of the patients enrolled. Patients received a median (IQR) of 31 (13-65) discrete IV medication administrations over the 72-hour period. Across all 47,803 IV medication administrations, ten unique IV medication clusters were identified with 121-130 medications in each cluster. Among the ten clusters, cluster 7 had the greatest association with FO; the mean number of cluster 7 medications received was significantly greater in patients in the FO cohort compared to patients who did not experience FO (25.6 vs.10.9. p<0.0001). 51 of the 127 medications in cluster 7 (40.2%) appeared in > 5 separate 3-hour periods during the 72-hour study window. The most common cluster 7 medications included continuous infusions, antibiotics, and sedatives/analgesics. Addition of cluster 7 medications to a prediction model with APACHE II score and receipt of diuretics improved the ability for the model to predict fluid overload (AUROC 5.65, p =0.0004). CONCLUSIONS: Using ML approaches, a unique IV medication cluster was strongly associated with FO. Incorporation of this cluster improved the ability to predict development of fluid overload in ICU patients compared with traditional prediction models. This method may be further developed into real-time clinical applications to improve early detection of adverse outcomes.

Genotyping Plasmodium falciparum gametocytes using amplicon deep sequencing.

BACKGROUND: Understanding the dynamics of gametocyte production in polyclonal Plasmodium falciparum infections requires a genotyping method that detects distinct gametocyte clones and estimates their relative frequencies. Here, a marker was identified and evaluated to genotype P. falciparum mature gametocytes using amplicon deep sequencing. METHODS: A data set of polymorphic regions of the P. falciparum genome was mined to identify a gametocyte genotyping marker. To assess marker resolution, the number of unique haplotypes in the marker region was estimated from 95 Malawian P. falciparum whole genome sequences. Specificity of the marker for detection of mature gametocytes was evaluated using reverse transcription-polymerase chain reaction of RNA extracted from NF54 mature gametocytes and rings from a non-gametocyte-producing strain of P. falciparum. Amplicon deep sequencing was performed on experimental mixtures of mature gametocytes from two distinct parasite clones, as well as gametocyte-positive P. falciparum field isolates to evaluate the quantitative ability and determine the limit of detection of the genotyping approach. RESULTS: A 400 bp region of the pfs230 gene was identified as a gametocyte genotyping marker. A larger number of unique haplotypes was observed at the pfs230 marker (34) compared to the sera-2 (18) and ama-1 (14) markers in field isolates from Malawi. RNA and DNA genotyping accurately estimated gametocyte and total parasite clone frequencies when evaluating agreement between expected and observed haplotype frequencies in gametocyte mixtures, with concordance correlation coefficients of 0.97 [95% CI: 0.92-0.99] and 0.92 [95% CI: 0.83-0.97], respectively. The detection limit of the genotyping method for male gametocytes was 0.41 pfmget transcripts/µl [95% CI: 0.28-0.72] and for female gametocytes was 1.98 ccp4 transcripts/µl [95% CI: 1.35-3.68]. CONCLUSIONS: A region of the pfs230 gene was identified as a marker to genotype P. falciparum gametocytes. Amplicon deep sequencing of this marker can be used to estimate the number and relative frequency of parasite clones among mature gametocytes within P. falciparum infections. This gametocyte genotyping marker will be an important tool for studies aimed at understanding dynamics of gametocyte production in polyclonal P. falciparum infections.

Patterns of comorbidities in patients with atrial fibrillation and impact on management and long-term prognosis: an analysis from the Prospective Global GLORIA-AF Registry.

BACKGROUND: Clinical complexity, as the interaction between ageing, frailty, multimorbidity and polypharmacy, is an increasing concern in patients with AF. There remains uncertainty regarding how combinations of comorbidities influence management and prognosis of patients with atrial fibrillation (AF). We aimed to identify phenotypes of AF patients according to comorbidities and to assess associations between comorbidity patterns, drug use and risk of major outcomes. METHODS: From the prospective GLORIA-AF Registry, we performed a latent class analysis based on 18 diseases, encompassing cardiovascular, metabolic, respiratory and other conditions; we then analysed the association between phenotypes of patients and (i) treatments received and (ii) the risk of major outcomes. Primary outcome was the composite of all-cause death and major adverse cardiovascular events (MACE). Secondary exploratory outcomes were also analysed. RESULTS: 32,560 AF patients (mean age 70.0 ± 10.5 years, 45.4% females) were included. We identified 6 phenotypes: (i) low complexity (39.2% of patients); (ii) cardiovascular (CV) risk factors (28.2%); (iii) atherosclerotic (10.2%); (iv) thromboembolic (8.1%); (v) cardiometabolic (7.6%) and (vi) high complexity (6.6%). Higher use of oral anticoagulants was found in more complex groups, with highest magnitude observed for the cardiometabolic and high complexity phenotypes (odds ratio and 95% confidence interval CI): 1.76 [1.49-2.09] and 1.57 [1.35-1.81], respectively); similar results were observed for beta-blockers and verapamil or diltiazem. We found higher risk of the primary outcome in all phenotypes, except the CV risk factor one, with highest risk observed for the cardiometabolic and high complexity groups (hazard ratio and 95%CI: 1.37 [1.13-1.67] and 1.47 [1.24-1.75], respectively). CONCLUSIONS: Comorbidities influence management and long-term prognosis of patients with AF. Patients with complex phenotypes may require comprehensive and holistic approaches to improve their prognosis.

Use of artificial intelligence in critical care: opportunities and obstacles.

BACKGROUND: Perhaps nowhere else in the healthcare system than in the intensive care unit environment are the challenges to create useful models with direct time-critical clinical applications more relevant and the obstacles to achieving those goals more massive. Machine learning-based artificial intelligence (AI) techniques to define states and predict future events are commonplace activities of modern life. However, their penetration into acute care medicine has been slow, stuttering and uneven. Major obstacles to widespread effective application of AI approaches to the real-time care of the critically ill patient exist and need to be addressed. MAIN BODY: Clinical decision support systems (CDSSs) in acute and critical care environments support clinicians, not replace them at the bedside. As will be discussed in this review, the reasons are many and include the immaturity of AI-based systems to have situational awareness, the fundamental bias in many large databases that do not reflect the target population of patient being treated making fairness an important issue to address and technical barriers to the timely access to valid data and its display in a fashion useful for clinical workflow. The inherent "black-box" nature of many predictive algorithms and CDSS makes trustworthiness and acceptance by the medical community difficult. Logistically, collating and curating in real-time multidimensional data streams of various sources needed to inform the algorithms and ultimately display relevant clinical decisions support format that adapt to individual patient responses and signatures represent the efferent limb of these systems and is often ignored during initial validation efforts. Similarly, legal and commercial barriers to the access to many existing clinical databases limit studies to address fairness and generalizability of predictive models and management tools. CONCLUSIONS: AI-based CDSS are evolving and are here to stay. It is our obligation to be good shepherds of their use and further development.

The association between urbanization and depression in the elderly: A network analysis from the complexity science perspective.

IMPORTANCE: The global increase in urbanization has coincided with a rise in depression prevalence. However, the effect of urbanization on depression remains controversial, especially for the elderly. OBJECTIVE: To clarify how urbanization impacts depression in the elderly from a network perspective. DESIGN, SETTING, AND PARTICIPANTS: This sectional cohort study used data from China Health and Retirement Longitudinal Study (CHARLS). MAIN OUTCOMES AND MEASURES: The occurrence of depressive symptoms in urban and rural elderly residents. Network metrics of depressive symptoms. RESULTS: Of the 13,993 participants, lower incidence of depressive symptoms was observed in urban (26.3 %, 95 % CI, 24.7 %-27.8 %) than in rural (40.4 %, 95 % CI, 39.5 %-41.3 %, P < 0.0001) residents. However, higher incidence of depressive symptoms was observed in urban (26.3 %, 95 % CI, 25.2 %-28.4 %) than in rural (17.5 %, 95 % CI, 16.1 %-18.9 %, P < 0.0001) residents in a subset of 2898 pairs of participants after PSM. No difference in the network structure and metrics between urban and rural residents before (M = 0.071, p = 0.054, S = 0.037, p = 0.80) and after (M = 0.085, p = 0.133, S = 0.086, p = 0.47) PSM was detected. The networks structure revealed that negative affect was strongly connected to somatic symptoms and that the two anhedonic symptoms were also strongly connected. CONCLUSIONS: The current study indicated the homogeneity of the ultimate nature of depression between rural and urban residents from the network perspective, supporting the viewpoint that urbanization might not impose influence on depression. Further researches delving deeper into the complexity of the issue may provide new insights into our understanding of depression in an urban environment among the elderly.

Feasibility of a mindfulness app in parents of a child with medical complexity: A pilot study.

The prevalence of pediatric chronic conditions is increasing rapidly. Parents of a child with medical complexity (CMC) experience stress, depression which may also impact family functioning. Research has shown that mindfulness applications (apps) have significantly improved stress and depression in other populations, but have not been studied in this population. The purpose of this pilot study was to assess the feasibility and efficacy of a mindfulness app in parents of a CMC. Parents were recruited to participate from a non-profit organization and asked to use a mindfulness app for 4 weeks and fill out questionnaires before and after the intervention. Eight mothers participated in the study for the entire study period. Data analysis showed that using a mindfulness app in this population is feasible and reduces depressive symptoms and improves family functioning.

Noncovalent Catalyst-cum-Inhibitor Directed Supramolecular Pathway Selection and Asymmetry Amplification by Aggregate Cross-Nucleation.

The key to any controlled supramolecular polymerization (CSP) process lies in controlling the nucleation step, which is typically achieved by sequestering monomers in a kinetically trapped state. However, kinetic traps that are shallow cannot prevent spontaneous nucleation, thus limiting the applicability of the CSP in such systems. We use a molecular additive to overcome this limitation by modifying the energy landscape of a competitive self-assembly process and increasing the kinetic stability of an otherwise short-lived trap state. The additive achieves this by simultaneously catalyzing OFF-pathway nucleation and inhibiting ON-pathway aggregation. In the process, it guides the molecular assembly exclusively toward the OFF-pathway aggregate analogue. The mechanisms of OFF-pathway catalysis and ON-pathway inhibition are elucidated. By specifically targeting the nucleation step, it was possible to achieve pathway selection at an extremely low additive-to-monomer ratio of 1:100. The generality of our approach is also demonstrated for other related molecular systems. Finally, removing the additive triggers the cross-nucleation of the ON-pathway aggregate on the surface of a less stable, OFF-pathway aggregate analogue. The resultant supramolecular polymer not only exhibits a more uniform morphology but more importantly, a marked improvement in the structural order that leads to an amplification of chiral asymmetry and a high absorption dissymmetry factor (gAbs) of ∼0.05.

Comparison of coronary artery lesion complexity and body component parameters measured by TANITA.

Introduction: Obesity is one of the main reversible causes of coronary artery disease. Aim: To investigate the relationship between body component measurements calculated with TANITA and SYNTAX score (SXscore), which indicates coronary complexity. Material and methods: 200 acute subendocardial myocardial infarction patients were included in our study. Body component measurements were made with the TANITA BC-601 device. After coronary angiography, patients were divided into two groups: high SXscore (≥ 22) and low-medium SXscore (< 22). Results: When the high SXscore group (50 patients) was compared with the low medium SXscore group (150 patients); for waist height ratio (p = 0.001), total fat weight (p = 0.001), total fat percentage (p = 0.006), total water percentage (p = 0.001), trunk fat percentage (p = 0.001), internal fat (p = 0.001) and metabolic age (p < 0.001), a statistical difference was found. In the correlation analysis, a correlation was detected between high SXscore and the waist height ratio (p = 0.042), trunk fat percentage (p = 0.047), internal fat (p < 0.001) and metabolic age (p = 0.009). ROC curve analysis for prediction of high SXscore detection; the cut-off value for internal fat and metabolic age was found to be 13.5-60.5 with 60-64% sensitivity and 61.3-62.7% specificity. Conclusions: We demonstrated the relationship between parameters such as internal fat, trunk fat percentage and metabolic age calculated by TANITA and SXscore, which is the coronary complexity score. We recommend that patients with high values detected during TANITA measurements be followed more carefully in terms of primary preventive medicine.

Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome.

BACKGROUND: Chronic Fatigue Syndrome patients suffer from symptoms that cannot be explained by a single underlying biological cause. It is sometimes claimed that these symptoms are a manifestation of a disrupted autonomic nervous system. Prior works studying this claim from the complex adaptive systems perspective, have observed a lower average complexity of physical activity patterns in chronic fatigue syndrome patients compared to healthy controls. To further study the robustness of such methods, we investigate the within-patient changes in complexity of activity over time. Furthermore, we explore how these changes might be related to changes in patient functioning. METHODS: We propose an extension of the allometric aggregation method, which characterises the complexity of a physiological signal by quantifying the evolution of its fractal dimension. We use it to investigate the temporal variations in within-patient complexity. To this end, physical activity patterns of 7 patients diagnosed with chronic fatigue syndrome were recorded over a period of 3 weeks. These recordings are accompanied by physicians' judgements in terms of the patients' weekly functioning. RESULTS: We report significant within-patient variations in complexity over time. The obtained metrics are shown to depend on the range of timescales for which these are evaluated. We were unable to establish a consistent link between complexity and functioning on a week-by-week basis for the majority of the patients. CONCLUSIONS: The considerable within-patient variations of the fractal dimension across scales and time force us to question the utility of previous studies that characterise long-term activity signals using a single static complexity metric. The complexity of a Chronic Fatigue Syndrome patient's physical activity signal does not suffice to characterise their high-level functioning over time and has limited potential as an objective monitoring metric by itself.

Innovative computational tools provide new insights into the polyploid wheat genome.

Bread wheat (Triticum aestivum) is an important crop and serves as a significant source of protein and calories for humans, worldwide. Nevertheless, its large and allopolyploid genome poses constraints on genetic improvement. The complex reticulate evolutionary history and the intricacy of genomic resources make the deciphering of the functional genome considerably more challenging. Recently, we have developed a comprehensive list of versatile computational tools with the integration of statistical models for dissecting the polyploid wheat genome. Here, we summarize the methodological innovations and applications of these tools and databases. A series of step-by-step examples illustrates how these tools can be utilized for dissecting wheat germplasm resources and unveiling functional genes associated with important agronomic traits. Furthermore, we outline future perspectives on new advanced tools and databases, taking into consideration the unique features of bread wheat, to accelerate genomic-assisted wheat breeding.

Exploring the Importance of Environmental Complexity for Newly Hatched Zebrafish.

The effects of an early impoverished social or physical environment on vertebrate neural development and cognition has been known for decades. While existing studies have focused on the long-term effects, measuring adult cognitive phenotypes, studies on the effects of environmental complexity on the early stages of development are lacking. Zebrafish (Danio rerio) hatchlings are assumed to have minimal interaction with their environment and are routinely reared in small, bare containers. To investigate the effects of being raised under such conditions on development of behaviour and cognition, hatchlings housed for 10 days in either an enriched or a standard environment underwent two cognitive tasks. The results were mixed. Subjects of the two treatments did not differ in performance when required to discriminate two areas. Conversely, we found a significant effect in a number discrimination task, with subjects from impoverished condition performing significantly worse. In both experiments, larvae reared in impoverished environment showed a reduced locomotor activity. Given the effects that enrichment appears to exert on larvae, a third experiment explored whether hatchlings exhibit a spontaneous preference for more complex environments. When offered a choice between a bare setting and one with objects of different shapes and colors, larvae spent over 70% of time in the enriched sector. Deepening these effects of an early impoverished environment on cognitive development is crucial for the welfare of captive zebrafish populations and for enhancing the quality and reliability of studies on larval zebrafish.