Intestinal microbiota diversity from broilers with runting and stunting syndrome performed by metagenomics.

RESEARCH HIGHLIGHTS: RSS causes dysbiosis of the gut microbiota of the ilea of chicks.A difference was found in gut microbiota between chicks with or without RSS.Candidatus Arthromitus was predominant in chicks with RSS.Clostridium sensu stricto 1 was strictly associated with chicks with RSS.

Effects of in ovo injection of bacterial peptides and CpG-ODN on Salmonella enterica serovar Heidelberg infection in specific pathogen-free (SPF) chicks.

RESEARCH HIGHLIGHTS: Peptides + CpG-ODN reduced SH in caeca at the first week post-infection.Administered formulations did not reduce SH-faecal excretion.Levels of intestinal IgA were similar between all groups.CpG-ODN improved some parameters associated with chick intestinal health.

Strategies to control pH in the dark fermentation of sugarcane vinasse: Impacts on sulfate reduction, biohydrogen production and metabolite distribution.

pH is notably known as the main variable defining distinct metabolic pathways during sugarcane vinasse dark fermentation. However, different alkalinizing (e.g. sodium bicarbonate; NaHCO3) and/or neutralizing (e.g. sodium hydroxide; NaOH) approaches were never directly compared to understand the associated impacts on metabolite profiles. Three anaerobic structured-bed reactors (AnSTBR) were operated in parallel and subjected to equivalent operational parameters, except for the pH control: an acidogenic-sulfidogenic (R1; NaOH + NaHCO3) designed to remove sulfur compounds (sulfate and sulfide), a hydrogenogenic (R2; NaOH) aimed to optimize biohydrogen (bioH2) production, and a strictly fermentative system without pH adjustment (R3) to mainly evaluate lactic acid (HLa) production and other soluble metabolites. NaHCO3 dosing triggered advantages not only for sulfate reduction (up to 56%), but also to enhance the stripping of sulfide to the gas phase (75-96% of the theoretical sulfide produced) by the high and constant biogas flow resulting from the CO2 released during NaHCO3 dissociation. Meanwhile, molasses-based vinasse presented higher potential for bioH2 (up to 4545 mL-H2 L-1 d-1) and HLa (up to 4800 mg L-1) production by butyric-type and capnophilic lactic fermentation pathways. Finally, heterolactic fermentation was the main metabolic route established when no pH control was provided (R3), as indicated by the high production of both HLa (up to 4315 mg L-1) and ethanol (1987 mg L-1). Hence, one single substrate (from which one single source of inoculum was originated) offers a wide range of metabolic possibilities to be exploited, providing substantial versatility to the application of anaerobic digestion in sugarcane biorefineries.

Calcium ferrites for phosphate adsorption and recovery from wastewater.

In this study, calcium ferrites with different Ca : Fe atomic ratios (1 : 1, 1 : 2, 1 : 3 and 2 : 1) were prepared from Ca and Fe nitrates treated at 300, 700 and 900 °C and evaluated for phosphate adsorption and recovery from wastewater. TG, XRD, Mössbauer spectroscopy, SEM, VSM magnetic measurements, and BET analyses showed the formation of two different calcium ferrite phases, i.e., CaFe2O4 and Ca2Fe2O5 at 700 and 900 °C. The adsorption results indicated that the formation of calcium ferrite structure is critical for phosphate adsorption/recovery. Evaluation of the pH, initial phosphate concentration, contact time, coexisting ions and desorption conditions showed remarkable adsorption capacities of 62-75 mg g-1 for CaFe1:2-700 and 28-43 mg g-1 for CaFe1:2-900. The phosphate adsorption on the Ca ferrite surfaces is so strong that the recovery/desorption showed limited efficiencies, e.g., 15-39%.

Investigating the Neuroprotective and Cognitive-Enhancing Effects of Bacopa monnieri: A Systematic Review Focused on Inflammation, Oxidative Stress, Mitochondrial Dysfunction, and Apoptosis.

The aging of the global population has increased the prevalence of neurodegenerative conditions. Bacopa monnieri (BM), an herb with active compounds, such as bacosides A and B, betulinic acid, loliolide, asiatic acid, and quercetin, demonstrates the potential for brain health. Limited research has been conducted on the therapeutic applications of BM in neurodegenerative conditions. This systematic review aims to project BM's beneficial role in brain disorders. BM has anti-apoptotic and antioxidant actions and can repair damaged neurons, stimulate kinase activity, restore synaptic function, improve nerve transmission, and increase neuroprotection. The included twenty-two clinical trials demonstrated that BM can reduce Nuclear Factor-κB phosphorylation, improve emotional function, cognitive functions, anhedonia, hyperactivity, sleep routine, depression, attention deficit, learning problems, memory retention, impulsivity, and psychiatric problems. Moreover, BM can reduce the levels of pro-inflammatory biomarkers and oxidative stress. Here, we highlight that BM provides notable therapeutic benefits and can serve as a complementary approach for the care of patients with neurodegenerative conditions associated with brain disorders. This review adds to the growing interest in natural products and their potential therapeutic applications by improving our understanding of the mechanisms underlying cognitive function and neurodegeneration and informing the development of new therapeutic strategies for neurodegenerative diseases.

Machine learning polysomnographically-derived electroencephalography biomarkers predictive of epworth sleepiness scale.

Excessive daytime sleepiness (EDS) causes difficulty in concentrating and continuous fatigue during the day. In the clinical setting, the assessment and diagnosis of EDS rely mostly on subjective questionnaires and verbal reports, which compromises the reliability of clinical diagnosis and the ability to robustly discern candidacy for available therapies and track treatment response. In this study, we used a computational pipeline for the automated, rapid, high-throughput, and objective analysis of previously collected encephalography (EEG) data to identify surrogate biomarkers for EDS, thereby defining the quantitative EEG changes in individuals with high Epworth Sleepiness Scale (ESS) (n = 31), compared to a group of individuals with low ESS (n = 41) at the Cleveland Clinic. The epochs of EEG analyzed were extracted from a large overnight polysomnogram registry during the most proximate period of wakefulness. Signal processing of EEG showed significantly different EEG features in the low ESS group compared to high ESS, including enhanced power in the alpha and beta bands and attenuation in the delta and theta bands. Our machine learning (ML) algorithms trained on the binary classification of high vs. low ESS reached an accuracy of 80.2%, precision of 79.2%, recall of 73.8% and specificity of 85.3%. Moreover, we ruled out the effects of confounding clinical variables by evaluating the statistical contribution of these variables on our ML models. These results indicate that EEG data contain information in the form of rhythmic activity that could be leveraged for the quantitative assessment of EDS using ML.

Sleep Quality and Social Jetlag in Young Adults During the Social Distancing Caused by COVID-19.

Introduction: This study aimed to evaluate the sleep quality and the Social Jetlag frequency in young adults during social distancing because of COVID-19. Methods: This is a cross-sectional study with 308 students aged ≥18 years and with Internet access. Questionnaires used: Pittsburgh Sleep Quality Index - Brazil (PSQI-BR), Epworth Sleepiness Scale, and Munich Chronotype Questionnaire. Results: The mean age of the students was 21 ± 3 years (17 - 42y), with no statistically significant difference between genders. The PSQI-BR indicated that 257 (83.4%) had poor sleep quality. The mean of Social Jetlag for young adults was 02:00 ± 01:49h, and we observed that 16.6% (n = 51) had Social Jetlag. Compared to men in the good sleep quality group, women had higher means for sleep duration on study days and free days, mid-point of sleep on study days and free days and corrected mid-point of sleep on free days. However, when compared to men in the group of poor sleep quality, we observed higher means for women regarding sleep duration on study days, the mid-point of sleep on study days, and the corrected mid-point of sleep on free days. Conclusions: Thus, the high frequency of young adult students who had poor sleep quality associated with Social Jetlag (2 hours) in the present study may reflect a pattern of sleep irregularity, which may be associated with impairment of environmental synchronizers and stimulation of social synchronizers during the lockdown resulting from the COVID-19 pandemic.

Endoscopic Release of the Ulnar Nerve at the Elbow: Technique Description and Case Series.

Objective The endoscopic release of the ulnar nerve reproduces a simple ( in situ ) procedure with smaller incisions, less soft tissue damage, and higher preservation of nerve vascularization. Endoscopy allows the clear visualization of the entire path of the nerve and surrounding noble structures. Moreover, it reveals any signs of compression and allows a safe release of 10 cm distally or proximally to the medial epicondyle. Methods A retrospective survey revealed that 15 subjects (1 with a bilateral injury) underwent an ulnar nerve compression release at the elbow using the endoscopic technique with Agee (Micro-Aire Sugical Instruments, Charlottesville, VA, EUA) equipment from January 2016 to January 2020. Results Symptoms of ulnar nerve compression improved in all patients; on average, they resumed their work activities in 26.5 days. There was no recurrence or need for another procedure. In addition, there were no severe procedure-related complications, such as infection and nerve or vascular injury. One patient had transient paresthesia of the sensory branches to the forearm, with complete functional recovery in 8 weeks. Conclusion Our study shows that the endoscopic release of the ulnar nerve at the elbow with the Agee equipment is a safe, reliable technique with good outcomes.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry for differential identification of adult Schistosoma worms.

BACKGROUND: Schistosomiasis is a major neglected tropical disease that affects up to 250 million individuals worldwide. The diagnosis of human schistosomiasis is mainly based on the microscopic detection of the parasite's eggs in the feces (i.e., for Schistosoma mansoni or Schistosoma japonicum) or urine (i.e., for Schistosoma haematobium) samples. However, these techniques have limited sensitivity, and microscopic expertise is waning outside endemic areas. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has become the gold standard diagnostic method for the identification of bacteria and fungi in many microbiological laboratories. Preliminary studies have recently shown promising results for parasite identification using this method. The aims of this study were to develop and validate a species-specific database for adult Schistosoma identification, and to evaluate the effects of different storage solutions (ethanol and RNAlater) on spectra profiles. METHODS: Adult worms (males and females) of S. mansoni and S. japonicum were obtained from experimentally infected mice. Species identification was carried out morphologically and by cytochrome oxidase 1 gene sequencing. Reference protein spectra for the creation of an in-house MALDI-TOF MS database were generated, and the database evaluated using new samples. We employed unsupervised (principal component analysis) and supervised (support vector machine, k-nearest neighbor, Random Forest, and partial least squares discriminant analysis) machine learning algorithms for the identification and differentiation of the Schistosoma species. RESULTS: All the spectra were correctly identified by internal validation. For external validation, 58 new Schistosoma samples were analyzed, of which 100% (58/58) were correctly identified to genus level (log score values ≥ 1.7) and 81% (47/58) were reliably identified to species level (log score values ≥ 2). The spectra profiles showed some differences depending on the storage solution used. All the machine learning algorithms classified the samples correctly. CONCLUSIONS: MALDI-TOF MS can reliably distinguish adult S. mansoni from S. japonicum.

Sleep-Disordered Breathing, Hypoxia, and Pulmonary Physiologic Influences in Atrial Fibrillation.

Background We leverage a large clinical cohort to elucidate sleep-disordered breathing and sleep-related hypoxia in incident atrial fibrillation (AF) development given the yet unclear contributions of sleep-related hypoxia and pulmonary physiology in sleep-disordered breathing and AF. Methods and Results Patients who underwent sleep studies at Cleveland Clinic January 2, 2000, to December 30, 2015, comprised this retrospective cohort. Cox proportional hazards models were used to examine apnea hypopnea index, percentage time oxygen saturation <90%, minimum and mean oxygen saturation, and maximum end-tidal carbon dioxide on incident AF adjusted for age, sex, race, body mass index, cardiopulmonary disease and risk factors, antiarrhythmic medications, and positive airway pressure. Those with spirometry were additionally adjusted for forced expiratory volume in 1 second, forced vital capacity, and forced expiratory volume in 1 second/forced vital capacity. This cohort (n=42 057) was 50.7±14.1 years, 51.3% men, 74.1% White individuals, had median body mass index 33.2 kg/m2, and 1947 (4.6%) developed AF over 5 years. A 10-unit apnea hypopnea index increase was associated with 2% higher AF risk (hazard ratio [HR], 1.02 [95% CI, 1.00-1.03]). A 10-unit increase in percentage time oxygen saturation <90% and 10-unit decreases in mean and minimum oxygen saturation were associated with 6% (HR, 1.06 [95% CI, 1.04-1.08]), 30% (HR, 1.30 [95% CI, 1.18-1.42]), and 9% (HR, 1.09 [95% CI, 1.03-1.15]) higher AF risk, respectively. After adjustment for spirometry (n=9683 with available data), only hypoxia remained significantly associated with incident AF, although all coefficients were stable. Conclusions Sleep-related hypoxia was associated with incident AF in this clinical cohort, consistent across 3 measures of hypoxia, persistent after adjustment for pulmonary physiologic impairment. Findings identify a strong role for sleep-related hypoxia in AF development without pulmonary physiologic interdependence.

First report of Giardia duodenalis in pet rabbits in Brazil.

Giardia duodenalis is a flagellate protozoan that multiplies in the small intestine of a wide variety of hosts, animals and humans. It has a worldwide distribution, however it is considered a neglected disease by the World Health Organization (WHO). Nowadays, rabbits are being chosen as pets, especially by children. There are already reports of the occurrence of G. duodenalis in rabbits from other countries, but research has not been carried out in Brazil yet. Thus, the objective of our work was to verify the occurrence and molecularly characterize G. duodenalis that affect pet rabbits, through the polymerase chain reaction (PCR) in the northwest region of the state of São Paulo, Brazil. Fecal samples from 100 rabbits were collected, which later underwent a process of DNA extraction and amplification by nested-PCR (nPCR), using the SSU rRNA gene, and ß-giardin (bg), glutamate dehydrogenase (gdh) and triosephosphate isomerase (tpi) to determine the assemblage. A questionnaire was answered by the owners with information about gender, age, deworming, diarrhea, water source, food, place of residence and contact with other animals. From those samples, 40 were positive for G. duodenalis. Good quality of the SSU rRNA gene by nPCR were obtained from two samples. For the first time, we report the occurrence of G. duodenalis assemblage A on pet rabbits in Brazil.

Distribution of Dalbulus maidis (DeLong) (Hemiptera: Cicadellidae) and incidence of maize rayado fino virus and Candidatus Phytoplasma asteris in corn succession planting systems.

BACKGROUND: Corn is one of the main crops grown globally to produce food for human consumption and animal feed, including raw materials for bioenergy. Effective pest management is critical for the economic viability of corn production. The leafhopper Dalbulus maidis and the diseases transmitted by it have become relevant to corn production. Our study aimed to determine environmental parameters that affect D. maidis populations and the impacts of pathogen dispersion on corn productivity under different rotation systems and sowing seasons. RESULTS: The population density of leafhoppers found in the studied crops was low but capable of establishing the diseases and spreading them widely in the crops. The leafhopper's highest occurrence was in the corn vegetative development stage, and its population peaks were earlier in the corn off-season. The incidence of maize rayado fino virus and maize bushy stunt phytoplasma were higher in corn off-season than in the growing season. The incidence of diseases was higher in the final stages of the cultivation cycle. Yield losses were significantly higher for maize bushy stunt phytoplasma and not significant for maize rayado fino virus. CONCLUSION: Our study observed that corn's physiological stage was the main factor influencing D. maidis dynamics. The occurrence of D. maidis at low densities was sufficient to ensure the efficient transmission and dissemination of maize rayado fino virus and maize bushy stunt phytoplasma, which had a higher incidence in the reproductive stage and the corn sowed off-season. © 2023 Society of Chemical Industry.

A Semi-Analytical Method for Channel and Pipe Flows for the Linear Phan-Thien-Tanner Fluid Model with a Solvent Contribution.

This work presents a semi-analytical method for laminar steady-state channel and pipe flows of viscoelastic fluids using the Linear Phan-Thien-Tanner (LPTT) constitutive equation, with solvent viscosity contribution. For the semi-analytical method validation, it compares its results and two analytical solutions: the Oldroyd-B model and the simplified LPTT model (without solvent viscosity contribution). The results adopted different values of the dimensionless parameters, showing their influence on the viscoelastic fluid flow. The results include the distribution of the streamwise velocity component and the extra-stress tensor components in the wall-normal direction. In order to investigate the proposed semi-analytical method, different solutions were obtained, both for channel and pipe flows, considering different values of Reynolds number, solvent viscosity contribution in the homogeneous mixture, elongational parameter, shear parameter, and Weissenberg number. The results show that the proposed semi-analytical method can find a laminar solution using the non-Newtonian LPTT model with solvent viscosity contribution and verify the effect of the parameters in the resulting flow field.

Cluster analysis of upper airway stimulation adherence patterns and implications on clinical care.

STUDY OBJECTIVES: Upper airway stimulation (UAS) therapy is effective for a subset of obstructive sleep apnea (OSA) patients with continuous positive airway pressure (CPAP) intolerance. While overall adherence is high, some patients have suboptimal adherence, which limits efficacy. Our goal was to identify therapy usage patterns during the first 3 months of therapy to enable targeted strategies for improved adherence. METHODS: Therapy data was retrieved from 2098 patients for three months after device activation. Data included mean and standard deviation (SD) of hours of use, therapy pauses, hours from midnight the therapy was turned ON and OFF, percentage of missing days, and stimulation amplitude. Cluster analysis was performed using Gaussian mixture models that categorized patients into six main groups. RESULTS: The six groups and their prevalence can be summarized as Cluster 1A: Excellent Use (34%); Cluster 1B: Excellent Use with variable timing (23%); Cluster 2A: Good Use with missing days and late therapy ON (16%), Cluster 2B: Good Use with missing days, late therapy ON, and early therapy OFF (12%); Cluster 3A: Variable Use with frequent missing days (8%); Cluster 3B: Variable Use with frequent pauses (7%). Most patients (85%) are excellent or good users with mean therapy use >6 hours per night. CONCLUSIONS: Cluster analysis of early UAS usage patterns identified six distinct groups that may enable personalized interventions for improved long-term management. Differentiation of the patient clusters may have clinical implications with regard to sleep hygiene education, therapy discomfort, comorbid insomnia, and other conditions that impact adherence.

Adherence to r-hGH Therapy in Pediatric Growth Hormone Deficiency: Current Perspectives on How Patient-Generated Data Will Transform r-hGH Treatment Towards Integrated Care.

Pediatric growth hormone (GH) deficiency is a licensed indication for replacement therapy with recombinant human growth hormone (r-hGH). Treatment, consisting of daily subcutaneous injections, extends from the time of diagnosis until cessation of linear growth at completion of puberty. Suboptimal adherence to r-hGH therapy is common and has been well documented to substantially impair the growth response and achievement of the optimal goal which is attainment of adult height within the genetic target range. The causes of poor adherence are complex and include disease-, patient-, doctor-, and treatment-related factors. Interventions for suboptimal adherence are important for a long-term successful outcome and can include both face-to-face and digital strategies. Face-to-face interventions include behavioral change approaches such as motivational interviewing and non-judgmental assessment. Medical and nursing staff require training in these techniques. Digital solutions are rapidly advancing as evidenced by the electronic digital auto-injector device, easypod® (Merck Healthcare KGaA, Darmstadt, Germany), which uses the web-based easypod® connect platform allowing adherence data to be transmitted electronically to healthcare professionals (HCPs), who can then access GH treatment history, enhancing clinical decisions. Over the past 10 years, the multi-national Easypod® Connect Observational Study has reported high levels of adherence (>85%) from up to 40 countries. The easypod® connect system can be supported by a smartphone app, growlink™, which facilitates the interactions between the patients, their care team, and patient support services. HCPs are empowered by new digital techniques, however, the human-digital partnership remains essential for optimal growth management. The pediatric patient on r-hGH therapy will benefit from these innovations to enhance adherence and optimize long-term response.

Unbalanced relationships: insights into the interaction between gut microbiota, geohelminths, and schistosomiasis.

Hosts and their microbiota and parasites have co-evolved in an adaptative relationship since ancient times. The interaction between parasites and intestinal bacteria in terms of the hosts' health is currently a subject of great research interest. Therapeutic interventions can include manipulations of the structure of the intestinal microbiota, which have immunological interactions important for modulating the host's immune system and for reducing inflammation. Most helminths are intestinal parasites; the intestinal environment provides complex interactions with other microorganisms in which internal and external factors can influence the composition of the intestinal microbiota. Moreover, helminths and intestinal microorganisms can modulate the host's immune system either beneficially or harmfully. The immune response can be reduced due to co-infection, and bacteria from the intestinal microbiota can translocate to other organs. In this way, the treatment can be compromised, which, together with drug resistance by the parasites makes healing even more difficult. Thus, this work aimed to understand interactions between the microbiota and parasitic diseases caused by the most important geohelminths and schistosomiasis and the consequences of these associations.

Using Deep Learning for Individual-Level Predictions of Adherence with Growth Hormone Therapy.

The problem of consistent therapy adherence is a current challenge for health informatics, and its solution can increase the success rate of treatments. Here we show a methodology to predict, at individual-level, future therapy adherence for patients receiving daily injections of growth hormone (GH) therapy for GH deficiency. Our proposed model is able to generate predictions of future adherence using a recurrent neural network with adherence data recorded by easypodTM, a connected autoinjection device. The model was trained with a multi-year long dataset with 2500 patients, from January 2007 to June 2019. When testing, the model reached an average sensitivity of 0.70 and a specificity of 0.88 per patient when predicting non-adherence (<85%) periods. When evaluated with thousands of therapy segments extracted from a test set, our model reached an AUC-PR score of 0.79 and AUC-ROC of 0.90; both metrics were consistently better than traditional approaches, such as simple average model. Using this model, we can perform precise early identification of patients who are likely to become non-adherent patients. This opens a path for healthcare practitioners to personalize GH therapy at any stage of the patients' journey and improve shared decision making with patients and caregivers to achieve optimal outcomes.

A Data-Driven Intervention Framework for Improving Adherence to Growth Hormone Therapy Based on Clustering Analysis and Traffic Light Alerting Systems.

Recombinant human growth hormone (r-hGH) is an established therapy for growth hormone deficiency (GHD); yet, some patients fail to achieve their full height potential, with poor adherence and persistence with the prescribed regimen often a contributing factor. A data-driven clinical decision support system based on "traffic light" visualizations for adherence risk management of patients receiving r-hGH treatment was developed. This research was feasible thanks to data-sharing agreements that allowed the creation of these models using real-world data of r-hGH adherence from easypod™ connect; data was retrieved for 11,015 children receiving r-hGH therapy for ≥180 days. Patients' adherence to therapy was represented using four values (mean and standard deviation [SD] of daily adherence and hours to next injection). Cluster analysis was used to categorize adherence patterns using a Gaussian mixture model. Following a traffic lights-inspired visualization approach, the algorithm was set to generate three clusters: green, yellow, or red status, corresponding to high, medium, and low adherence, respectively. The area under the receiver operating characteristic curve (AUC-ROC) was used to find optimum thresholds for independent traffic lights according to each metric. The most appropriate traffic light used the SD of the hours to the next injection, with an AUC-ROC value of 0.85 when compared to the complex clustering algorithm. For the daily adherence-based traffic lights, optimum thresholds were >0.82 (SD, <0.37), 0.53-0.82 (SD, 0.37-0.61), and <0.53 (SD, >0.61) for high, medium, and low adherence, respectively. For hours to next injection, the corresponding optimum thresholds were <27.18 (SD, <10.06), 27.18-34.01 (SD, 10.06-29.63), and >34.01 (SD, >29.63). Our research indicates that implementation of a practical data-driven alert system based on recognised traffic-light coding would enable healthcare practitioners to monitor sub-optimally-adherent patients to r-hGH treatment for early intervention to improve treatment outcomes.

Worker allometry in relation to colony size and social form in the fire ant Solenopsis invicta.

Workers of the polymorphic fire ant Solenopsis invicta Buren (Hymenoptera: Formicidae) show modest changes of shape with increases in body size. These shape changes (allometries) have been described only for workers taken from mature colonies of the monogyne social form. For the study reported here, workers were collected from small and large monogyne and large polygyne colonies for tests of the effects of colony size and social form on allometry. The differential growth of body parts in relation to total body growth was determined by measurement of all major body parts and regression of the logs of these measurements, or their ratios, on the log of the body size. The slopes of these regressions defined the allometric relationships, and the slopes for these three types of colonies were compared for determination of the influence of colony size and social form on allometric rules. Most allometric constants did not differ with colony size or social form, but head shape, relative antennal size, and alinotum shape did. For a given worker size, heads of workers from small monogyne colonies or from polygyne colonies were narrower above the eyes. Antennae of workers from large monogyne colonies were relatively shorter than those from small monogyne or polygyne colonies (which did not differ). Alinotum heights of small workers from small monogyne colonies were greater than those from large monogyne or polygyne colonies (which were isometric and did not differ). These observed differences in allometric constants suggest that the relative growth rules are not completely determined by worker body size but are affected by colony size and social form. These differences are discussed in light of the growth of imaginai discs under conditions of fixed resources.