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Purpose of Review This review aims to discuss burning mouth disorder (BMD) and its management and offers a guide to general dental practitioners to manage periodontal health in patients with BMD. Recent Findings Dental practitioners are well trained in diagnosing and treating periodontal disease; however, when periodontal disease coexists with BMD, diagnosis and management of these conditions become more complex. Personalised treatment for individual patients is prudent for long-term treatment compliance and effectiveness. Summary BMD is a chronic pain disorder characterised by the absence of visible mucosal lesions. It is often associated with the symptoms of burning, altered taste, and dry mouth with no obvious medical or dental cause. Diagnosis and treatment of BMD are complex and are influenced by multiple factors, which may complicate the diagnosis and treatment of especially painful periodontal disease.

Building on the known scaling law that a single timescale, a cellular unit of time, governs stochastic growth and division of individual bacterial cells under constant growth conditions, here we articulate an analogous ansatz for time-varying growth conditions. We propose that a dynamic rescaling of the cellular unit of time captures the predominant effect of external variations in conditions. Using this temporal scaling ansatz, we derive exact analytic results for how the time-dependent cell age distribution adapts to changing conditions. Our results reveal the natural representation for these time-dependent dynamics. When recast in terms of the new representation, the cell age distribution evolves under time-invarant rules even as growth conditions remain dynamic! This result corresponds to the generalization of the scaling law for constant growth condition. Finally, we provide a prescription for convenient experimental tests of the temporal scaling ansatz.

Introduction Early intervention services for psychosis (EIS) are associated with improved clinical and economic outcomes. In Quebec, clinicians led the development of EIS from the late 1980s until 2017 when the provincial government announced EIS-specific funding, implementation support and provincial standards. This provides an interesting context to understand the impacts of policy commitments on EIS. Our primary objective was to describe the implementation of EIS three years after this increased political involvement. Methods This cross-sectional descriptive study was conducted in 2020 through a 161-question online survey, modeled after our team's earlier surveys, on the following themes: program characteristics, accessibility, program operations, clinical services, training/supervision, and quality assurance. Descriptive statistics were performed. When relevant, we compared data on programs founded before and after 2017. Results Twenty-eight of 33 existing EIS completed the survey. Between 2016 and 2020, the proportion of Quebec's population having access to EIS rose from 46% to 88%; >1,300 yearly admissions were reported by surveyed EIS, surpassing governments’ epidemiological estimates. Most programs set accessibility targets; adopted inclusive intake criteria and an open referral policy; engaged in education of referral sources. A wide range of biopsychosocial interventions and assertive outreach were offered by interdisciplinary teams. Administrative/organisational components were less widely implemented, such as clinical/administrative data collection, respecting recommended patient-to-case manager ratios and quality assurance. Conclusion Increased governmental implementation support including dedicated funding led to widespread implementation of good-quality, accessible EIS. Though some differences were found between programs founded before and after 2017, there was no overall discernible impact of year of implementation. Persisting challenges to collecting data may impede monitoring, data-informed decision-making, and quality improvement. Maintaining fidelity and meeting provincial standards may prove challenging as programs mature and adapt to their catchment area's specificities and as caseloads increase. Governmental incidence estimates may need recalculation considering recent epidemiological data.

Individual bacterial cells grow and divide stochastically. Yet they maintain their characteristic sizes across generations within a tightly controlled range. What rules ensure intergenerational stochastic homeostasis of individual cell sizes? Valuable clues have emerged from high-precision longterm tracking of individual statistically-identicalCaulobacter crescentuscells as reported in [1]: Intergenerational cell size homeostasis is an inherently stochastic phenomenon, follows Markovian or memory-free dynamics, and cells obey an intergenerational scaling law, which governs the stochastic map characterizing generational sequences of characteristic cell sizes. These observed emergent simplicities serve as essential building blocks of the first-principles-based theoretical framework we develop here. Our exact analytic fitting-parameter-free results for the predicted intergenerational stochastic map governing the precision kinematics of cell size homeostasis are remarkably well borne out by experimental data, including extant published data on other microorganisms,Escherichia coliandBacillus subtilis. Furthermore, our framework naturally yields the general exact and analytic condition, necessary and sufficient, which ensures that stochastic homeostasis can be achieved and maintained. Significantly, this condition is more stringent than the known heuristic result for the popular quasi-deterministic adder-sizer-timer frameworks. In turn the fully stochastic treat-ment we present here extends and updates extant frameworks, and challenges the notion that the mythical “average cell” can serve as a reasonable proxy for the inherently stochastic behaviors of actual individual cells.

Biological systems are complex and hierarchical. Yet, key physiological “state” variables are effectively held in homeostasis despite the inherent stochasticity of constitutive molecular processes. To identify quantitative rules governing the control systems responsible for homeostasis, we reconceptualize homeostasis as a dynamical—albeit stochastic—process, rather than as an end state (i.e., a setpoint). We focus on cell size homeostasis as a valuable case study. Using our SChemostat technology, we obtain high-precision multigenerational trains of cell sizes of statistically identical, non-interacting individualCaulobacter crescentuscells in precisely controlled environments. Characterizing the typical generational size of a bacterium by the size immediately following a division event, we first establish that individual cells indeed maintain stochastic intergenerational size homeostasis. Through extensive data analysis from single-cell experiments under multiple growth conditions, we uncover hidden simplicities in these data, including an intergenerational scaling law governing fluctuations in cell sizes across different generations. These “emergent simplicities” comprehensively describe the dynamics—in turn they specify (without need for any fitting parameters) the precise stochastic map governing the intergenerational evolution of cell sizes. Importantly, we find that intergenerational cell size homeostasis is achieved through memory-free, reflexive elastic adaptation. Thus, under balanced growth conditions, cell size cannot serve as a repository of intergenerational memory.

The aim of the study is to appraise the quality, self-management support functions and user-design of phone apps that provide information for people with temporomandibular disorder.

Organisms are able to partition resources adaptively between growth and repair. The precise nature of optimal partitioning and how this emerges from cellular dynamics including insurmountable trade-offs remains an open question. We construct a mathematical framework to estimate optimal partitioning and the corresponding maximal growth rate constrained by empirical scaling laws. We model a biosynthesis tradeoff governing the partitioning of the ribosome economy between replicating functional proteins and replicating the ribosome pool, and also an energy tradeoff arising from the finite energy budget of the cell. Through exact analytic calculations we predict limits on the range of values partitioning ratios take while sustaining growth. We calculate how partitioning and cellular composition scale with protein and ribosome degradation rates and organism size. These results reveal different classes of optimizing strategies corresponding to phenotypically distinct bacterial lifestyles. We summarize these findings in a quadrant-based taxonomy including: a “greedy” strategy maximally prioritizing growth, a “prudent” strategy maximally prioritizing the management of damaged pools, and “strategically limited” intermediates.

Endosomal maturation is a critical and fundamental process for robust transport of cargo (such as activated receptors) to specific cellular compartments in a timely manner. The most prominent model of endosomal maturation involves a phosphoinositide-driven gain or loss of specific proteins at the level of individual endosomes, emphasising an autonomous and stochastic model of maturation. However, to date, direct whole cell-level measurements of absolute number of maturation events have not been performed, owing to limitations in fast, volumetric imaging. Here, we use lattice light-sheet imaging to track individual very early and early endosomes over the entire population. We demonstrate that direct inter-endosomal contact drives the maturation from very early (APPL1-positive) to early (EEA1-positive) endosomes. Using fluorescence lifetime, we show that this endosomal interaction is underpinned by the asymmetric binding of EEA1 to very early and early endosomes through the N- and C-termini, respectively. Thus, stochastic microtubule-mediated inter-endosomal interactions through EEA1 provide a mechanism to bring temporal and population-level control to the process of endosome maturation. Our findings indicate that APPL1- to EEA1-positive endosomal maturation is not a result of autonomous endosomal events but is driven by heterotypic EEA1-mediated endosomal interactions.

Our current understanding of the bacterial cell cycle is framed largely by population-based experiments that focus on the behavior of idealized average cells. Most famously, the contributions of Cooper and Helmstetter help to contextualize the phenomenon of overlapping replication cycles observed in rapidly growing bacteria. Despite the undeniable value of these approaches, their necessary reliance on the behavior of idealized average cells washes out the stochasticity inherent in single cell growth and physiology limiting their mechanistic value. To bridge this gap, we propose an updated and agnostic framework, informed by extant single-cell data, that quantitatively accounts for stochastic variations in single-cell dynamics and the impact of medium composition on cell growth and cell cycle progression. In this framework, stochastic timers sensitive to medium composition impact the relationship between cell cycle events, accounting for observed differences in the relationship between cell cycle events in slow and fast growing cells. We conclude with a roadmap for potential application of this framework to longstanding open questions in the bacterial cell cycle field.

In isolation from their peers,Photinus carolinusfireflies flash with no intrinsic period between successive bursts. Yet, when congregating into large mating swarms, these fireflies transition into predictability, synchronizing with their neighbors with a rhythmic periodicity. Here we propose a mechanism for emergence of synchrony and periodicity, and formulate the principle in a mathematical framework. Remarkably, with no fitting parameters, analytic predictions from this simple principle and framework agree strikingly well with data. Next, we add further sophistication to the framework using a computational approach featuring groups of random oscillators via integrate-and-fire interactions controlled by a tunable parameter. This agent-based framework ofP. carolinusfireflies interacting in swarms of increasing density also shows quantitatively similar phenomenology and reduces to the analytic framework in the appropriate limit of the tunable coupling strength. We discuss our findings and note that the resulting dynamics follow the style of a decentralized follow-the-leader synchronization, where any of the randomly flashing individuals may take the role of the leader of any subsequent synchronized flash burst.

BACKGROUND Given the strong evidence of their effectiveness, early intervention services (EIS) for psychosis are being widely implemented. However, heterogeneity in the implementation of essential components remains an ongoing challenge. Rapid-learning health systems (RLHSs) that embed data collection in clinical settings for real-time learning and continuous quality improvement can address this challenge. Therefore, we implemented an RLHS in 11 EIS in Quebec, Canada. OBJECTIVE This project aims to determine the feasibility and acceptability of implementing an RLHS in EIS and assess its impact on compliance with standards for essential EIS components. METHODS Funding for this project was secured in July 2019, and ethics approval was received in December 2019. The implementation of this RLHS involves 6 iterative phases: external and internal scan, design, implementation, evaluation, adjustment, and dissemination. Multiple stakeholder groups (service users, families, clinicians, researchers, decision makers, and provincial EIS associations) are involved in all phases. Meaningful EIS quality indicators (eg, satisfaction and timeliness of response to referrals) were selected based on a literature review, provincial guidelines, and stakeholder consensus on prioritization of indicators. A digital infrastructure was designed and deployed comprising a user-friendly interface for routinely collecting data from programs; a digital terminal and mobile app to collect feedback from service users and families regarding care received, health, and quality of life; and data analytic, visualization, and reporting functionalities to provide participating programs with real-time feedback on their ongoing performance in relation to standards and to other programs, including tailored recommendations. Our community of practice conducts activities, leveraging insights from data to build program capacity while continuously aligning their practices with standards and best practices. Guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework, we are collecting quantitative and qualitative data on the reach, effectiveness, adoption, implementation, and maintenance of our RLHS for evaluating its impacts. RESULTS Phase 1 (identifying RLHS indicators for EIS based on a literature synthesis, a survey, and consensus meetings with all stakeholder groups) and phase 2 (developing and implementing the RLHS digital infrastructure) are completed (September 2019 to May 2020). Phases 3 to 5 have been ongoing (June 2020 to June 2022). Continuous data collection through the RLHS data capture platforms and real-time feedback to all stakeholders are deployed. Phase 6 will be implemented in 2022 to assess the impact of the RLHS using the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework with quantitative and qualitative data. CONCLUSIONS This project will yield valuable insights into the implementation of RLHS in EIS, offering preliminary evidence of its acceptability, feasibility, and impacts on program-level outcomes. The findings will refine our RLHS further and advance approaches that use data, stakeholder voices, and collaborative learning to improve outcomes and quality in services for psychosis. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/37346

Identifying novel topological properties of topological quantum states of matter, such as exemplified by the quantized Hall conductance, is a valuable step towards realizing materials with attractive topological attributes that guarantee their imperviousness to realistic imperfections, disorder and environmental disturbances. Is the gravitational coupling coefficient of topological quantum states of matter a promising candidate? Substantially building on well established results for quantum Hall states, using disclinations as tools for controlled creation of pristine spatial curvature free of undesirable artifacts such as would interfere with the electronic motion of interest, herein we report that a large class of lattice topological states of matter exhibit gravitational response, i.e., charge response to intrinsic spatial curvature. This phenomenon is characterized by a topologically quantized coupling constant. Remarkably, the charge-gravity relationship remains linear in the curvature, up to the maximum curvature achievable on the lattice, demonstrating absence of higher order nonlinear response. Our findings facilitate articulating the physical principles underlying the topological quantization of the gravitational coupling constant, in analogy with the insights offered by the Chern number description of the quantized Hall conductance.

Background: Given the strong evidence for their effectiveness, early intervention services for psychosis (EIS) are being widely implemented. However, heterogeneity in the implementation of essential components, remains an ongoing challenge. Rapid learning health systems (RLHS), that embed data collection in clinical settings for real-time learning and continual quality improvement, can address this challenge. We therefore implemented a RLHS in 11 EIS in Quebec, Canada. This project aims to determine the feasibility and acceptability of implementing a RLHS in EIS, and to assess its impact on compliance with standards for essential EIS components. Methods: Following literature recommendations, the implementation of this RLHS involves six iterative phases: external and internal scan, design, implementation, evaluation, adjustment, and dissemination. Multiple stakeholder groups (service users, families, clinicians, researchers, decision makers, provincial EIS association) are involved in all phases. Meaningful indicators of EIS quality (e.g., satisfaction, timeliness of response to referrals) were selected based on literature review, provincial guidelines, and stakeholder consensus on indicators prioritisation. A digital infrastructure was designed and deployed that comprises (a) a user-friendly interface for routinely collecting data from programs (b) a digital terminal and mobile app to collect feedback from service users and families regarding care received, health, and quality of life (c) data analytic, visualization and reporting functionalities to provide participating programs with real-time feedback on their performance over time, and in relation to standards and to other programs, along with tailored recommendations. Community of practice activities are being conducted that leverage insights from data to build capacity among programs to continually progress towards aligning their practice with standards/best practices. Guided by the RE-AIM framework, we are collecting quantitative and qualitative data on the Reach, Effectiveness Adoption, Implementation and Maintenance of our RLHS. These RE-AIM data will be analyzed to evaluate our RLHS’s impacts. Discussion: This project will yield valuable insights about how a RLHS can be implemented by EIS, along with preliminary evidence for its acceptability, feasibility and impacts on program-level outcomes. Its findings will refine our RLHS further and advance approaches that bring data, stakeholder voices and collaborative learning to improve outcomes and service quality in psychosis. Trial registration: NA

International audience; Cells are the basic units of all living matter which harness the flow of energy to drive the processes of life. While the biochemical networks involved in energy transduction are well-characterized, the energetic costs and constraints for specific cellular processes remain largely unknown. In particular, what are the energy budgets of cells? What are the constraints and limits energy flows impose on cellular processes? Do cells operate near these limits, and if so how do energetic constraints impact cellular functions? Physics has provided many tools to study nonequilibrium systems and to define physical limits, but applying these tools to cell biology remains a challenge. Physical bioenergetics, which resides at the interface of nonequilibrium physics, energy metabolism, and cell biology, seeks to understand how much energy cells are using, how they partition this energy between different cellular processes, and the associated energetic constraints. Here we review recent advances and discuss open questions and challenges in physical bioenergetics.

Supplemental Material, sj-docx-1-cpa-10.1177_0706743721992679 for Understanding Components of Duration of Untreated Psychosis and Relevance for Early Intervention Services in the Canadian Context: Comprendre les Composantes de la Durée de la Psychose Non Traitée et la Pertinence de Services D’intervention Précoce Dans le Contexte Canadien by Ashok Malla, Manish Dama, Srividya Iyer, Ridha Joober, Norbert Schmitz, Jai Shah, Bilal Issaoui Mansour, Martin Lepage and Ross Norman in The Canadian Journal of Psychiatry

Listing of ethics boards; age of research consent and need for parental consent for each site in the ACCESS Open Minds project. (DOCX 15 kb)

Supplemental Material, LHW_Post-training_Case_scenarios for A Model of Mental Health Care Involving Trained Lay Health Workers for Treatment of Major Mental Disorders Among Youth in a Conflict-Ridden, Low-Middle Income Environment: Part I Adaptation and Implementation by Ashok Malla, Mushtaq Margoob, Srividya Iyer, Ridha Joober, Shalini Lal, Rangawsamy Thara, Huda Mushtaq, and Bilal Issaoui Mansouri in The Canadian Journal of Psychiatry

Psychometric properties of study instruments. (DOCX 20 kb)

Supplemental Material, LHW_Post-training_Quiz for Testing the Effectiveness of Implementing a Model of Mental Healthcare Involving Trained Lay Health Workers in Treating Major Mental Disorders Among Youth in a Conflict-Ridden, Low-Middle Income Environment: Part II Results by Ashok Malla, Mushtaq Margoob, Srividya Iyer, Abdul Majid, Shalini Lal, Ridha Joober, and Bilal Issaoui Mansouri in The Canadian Journal of Psychiatry

SPIRIT 2013 checklist for ACCESS Open Minds. (DOCX 53 kb)

Supplemental Material, 854069_Supplementary_Material for Sex Differences in Clinical and Functional Outcomes among Patients Treated in an Early Intervention Service for Psychotic Disorders: An Observational Study by Manish Dama, Franz Veru, Norbert Schmitz, Jai Shah, Srividya Iyer, Ridha Joober and Ashok Malla in The Canadian Journal of Psychiatry

Model of consent form used in the ACCESS Open Minds project. (DOCX 54 kb)

Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, Geometric Brownian Motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories., Physical Review E, 2017

Often sharp changes in cellular behavior are triggered by thresholded events, i.e., by the attainment of a threshold value of a relevant cellular or molecular dynamical variable. Since the governing variable itself typically undergoes noisy or stochastic dynamics, there is a corresponding variability in the times when the same change occurs in each cell of a population. This time is called the "first passage" time and the corresponding process is a "first passage" (FP) process, referring to the event when a random variable first passes the threshold value. In this review we first present and elucidate fundamentals of the FP formalism within a unified conceptual framework, which naturally integrates the existing techniques. We then discuss applications thereof, with emphasis on the practical use of FP techniques in biophysical systems. Our focus here is on covering a diverse set of analytical techniques; the number of reviewed biological applications is thus limited, out of necessity. We focus on three specific areas: channel transport; receptor binding and adhesion; and single-cell growth and division.

How are granular details of stochastic growth and division of individual cells reflected in smooth deterministic growth of population numbers? We provide an integrated, multiscale perspective of microbial growth dynamics by formulating a data-validated theoretical framework that accounts for observables at both single-cell and population scales. We derive exact analytical complete time-dependent solutions to cell-age distributions and population growth rates as functionals of the underlying interdivision time distributions, for symmetric and asymmetric cell division. These results provide insights into the surprising implications of stochastic single-cell dynamics for population growth. Using our results for asymmetric division, we deduce the time to transition from the reproductively quiescent (swarmer) to replication-competent (stalked) stage of the {\em Caulobacter crescentus} lifecycle. Remarkably, population numbers can spontaneously oscillate with time. We elucidate the physics leading to these population oscillations. For {\em C. crescentus} cells, we show that a simple measurement of the population growth rate, for a given growth condition, is sufficient to characterize the condition-specific cellular unit of time, and thus yields the mean (single-cell) growth and division timescales, fluctuations in cell division times, the cell age distribution, and the quiescence timescale.

In the context of an increasing focus on indicated prevention of psychotic disorders, we describe the operation of the Clinic for Assessment of Youth at Risk (CAYR) over 10 years, a specialized service for identification, monitoring and treatment of young individuals who meet ultra-high risk (UHR) criteria for psychosis, and its integration within the Prevention and Early Intervention Program for Psychosis (PEPP) in Montreal, Canada.We outline rationale, development, inclusion and exclusion criteria, assessment, services offered, community outreach and liaison with potential referral sites, and our research focus on risk and protective factors related to the neural diathesis-stress model of psychosis.Between January 2005 and December 2014, CAYR has received 370 referrals and accepted 177 patients who met UHR criteria based on the Comprehensive Assessment for At Risk Mental States. Conversion rates to a first episode of psychosis were 11%. Our research findings point to high subjective stress levels, poor self-esteem, social support and coping skills, and a dysregulation of the hypothalamus-pituitary-adrenal axis during the high-risk phase.Our efforts at community outreach have resulted in increasing numbers of referrals and patients accepted to CAYR, highlighting the relevance of and need for a high-risk programme in the Montreal area. Patients with psychotic symptoms can be immediately assigned to the first-episode psychosis clinic within PEPP, which has likely contributed to the low conversion rates observed in the UHR group. Our research findings on stress and protective factors emphasize the importance of psychosocial interventions for high-risk patients.

A first-episode psychosis (FEP) is a traumatic experience that can often result in great suffering. However, in addition to suffering, persons affected by FEP may also experience post-traumatic growth (PTG) or the perception that good has followed psychosis. Although much is known concerning the negative outcomes following FEP, little attention has been given to the state of scientific knowledge on PTG following FEP. The aim of this study is to determine the state of knowledge concerning PTG following FEP to help set the stage for a full systematic review.A scoping review was conducted following six steps: identifying the research question and relevant studies, selecting studies, charting the data, coding and summarizing results and consulting with relevant stakeholders regarding the findings.Post-traumatic growth following FEP was described mostly as following the process of recovery and primarily, in qualitative articles. Themes related to PTG included developing positive character traits, making positive lifestyle changes, developing stronger connections with others, integrating the FEP with the self, experiencing greater religiosity and appreciating life more.In addition to the negative aftermath of FEP, PTG may also occur. Evidence of PTG following FEP will be examined in a systematic review focused on the recovery and qualitative literature.

We investigate the intergenerational shape dynamics of single Caulobacter crescentus cells using a novel combination of imaging techniques and theoretical modeling. We determine the dynamics of cell pole-to-pole lengths, cross-sectional widths and medial curvatures from high accuracy measurements of cell contours. Moreover, these shape parameters are determined for over 250 cells across approximately 10000 total generations, which affords high statistical precision. Our data and model show that constriction is initiated early in the cell cycle and that its dynamics are controlled by the time scale of exponential longitudinal growth. Based on our extensive and detailed growth and contour data, we develop a minimal mechanical model that quantitatively accounts for the cell shape dynamics and suggests that the asymmetric location of the division plane reflects the distinct mechanical properties of the stalked and swarmer poles. Furthermore, we find that the asymmetry in the division plane location is inherited from the previous generation. We interpret these results in terms of the current molecular understanding of shape, growth and division of C. crescentus.

Understanding senescence of single bacterial cells will provide key insights into aging in higher organisms. Due to experimental challenges, there is a paucity of high-quality long-term single-cell data, which is essential to quantify this phenomenon; this has led to conflicting results to date. We have developed a system to image the stochastic dynamics of growth and division of individual cells of the asymmetrically-dividing bacterium Caulobacter crescentus with unprecedented precision for more than one hundred generations. We report on conditional senescence in response to adverse environmental conditions, which provoke an irreversible and quantitatively predictable decrease in growth rate. In contrast, single cells do not senesce under steady growth conditions over tens of generations. That individual cells do not senescence under ideal growth conditions but do so following exposure to certain environmental stresses has implications for understanding the origins of aging itself.

Uncovering the quantitative laws that govern the growth and division of single cells remains a major challenge. Using a unique combination of technologies that yields unprecedented statistical precision, we find that the sizes of individual Caulobacter crescentus cells increase exponentially in time. We also establish that they divide upon reaching a critical multiple ($\approx$1.8) of their initial sizes, rather than an absolute size. We show that when the temperature is varied, the growth and division timescales scale proportionally with each other over the physiological temperature range. Strikingly, the cell-size and division-time distributions can both be rescaled by their mean values such that the condition-specific distributions collapse to universal curves. We account for these observations with a minimal stochastic model that is based on an autocatalytic cycle. It predicts the scalings, as well as specific functional forms for the universal curves. Our experimental and theoretical analysis reveals a simple physical principle governing these complex biological processes: a single temperature-dependent scale of cellular time governs the stochastic dynamics of growth and division in balanced growth conditions., Comment: Text+Supplementary

Recent imaging data for single bacterial cells reveal that their mean sizes grow exponentially in time and that their size distributions collapse to a single curve when rescaled by their means. An analogous result holds for the division-time distributions. A model is needed to delineate the minimal requirements for these scaling behaviors. We formulate a microscopic theory of stochastic exponential growth as a Master Equation that accounts for these observations, in contrast to existing quantitative models of stochastic exponential growth (e.g., the Black-Scholes equation or geometric Brownian motion). Our model, the stochastic Hinshelwood cycle (SHC), is an autocatalytic reaction cycle in which each molecular species catalyzes the production of the next. By finding exact analytical solutions to the SHC and the corresponding first passage time problem, we uncover universal signatures of fluctuations in exponential growth and division. The model makes minimal assumptions, and we describe how more complex reaction networks can reduce to such a cycle. We thus expect similar scalings to be discovered in stochastic processes resulting in exponential growth that appear in diverse contexts such as cosmology, finance, technology, and population growth., Comment: Text+Supplementary

The extracellular poly(β-hydroxybutyrate) (PHB) depolymerase of Aspergillus fumigatus Pdf1 was purified by a new, simple, one-step affinity chromatography method using the substrate PHB. The purified enzyme was glycosylated, with the molecular mass of ≃40 KD, and exhibited a novel self-aggregation behavior by means of hydrophobic interaction that was resolved by Triton X-100 (TX-100) pretreatment of enzyme and also TX-100 incorporation in the native gel. The apparent Km value of purified enzyme for PHB was 119 μg/mL and 3-hydroxybutyrate was detected as the main endproduct of PHB hydrolysis. The depolymerase was insensitive to phenylmethyl sulfonyl fluoride (PMSF), sodium azide, ethylenediaminetetraacetic acid (EDTA), and para-chloromercuric benzoic acid (PCMB), but was inactivated by dithioerythritol (DTT) and showed specificity for short chain-length poly(β-hydroxyalkanoates) (PHAs) such as PHB, poly(hydroxyvalerate) (PHV), and copolymers of 3-hydroxybutyrate (3HB) and 3-hydroxyvalerate (3HV). Medium-chain-length PHA failed to get hydrolyzed. The enzyme, however, exhibited strong cross reactivity with the Comamonas sp. PHB depolymerase antibodies, but not with PHV depolymerase antibodies of Pseudomonas lemoignei. Southern hybridization and dot blot analysis of A. fumigatus Pdf1 genomic DNA with alkaline phosphatase labeled probes of P. lemoignei PHB and PHV depolymerase genes revealed no homology, although the enzyme hydrolyzed both PHB and PHV.

Objective Despite the well-acknowledged problem of poor adherence to antipsychotic (AP) medication, long-acting injectables (LAIs) that could improve adherence are underused in Canada. Attitudes concerning LAIs among patients and psychiatrists may contribute to this underuse. Our objective was to investigate perceptions of and attitudes toward LAIs among patients in Canada. Method Focus groups were conducted with 34 patients with a diagnosis of schizophrenia spectrum psychoses in 4 Canadian provinces. The focus groups inquired about experiences with and attitudes toward LAI APs. The sessions were audiotaped and transcribed verbatim, and transcripts were coded using a combination of deductive and inductive methods. Results Four themes emerged: awareness of and knowledge about LAIs; perceptions about LAIs; cost and convenience considerations; and issues arising from the coercive context under which LAIs were often prescribed. Nine patients had never heard about LAIs, and some others reported not having understood what was discussed with them regarding LAIs. Patients had typically heard about LAIs in either a context of coercion or of medication nonadherence. Patients had positive and negative perceptions concerning LAIs. The positive perceptions centred on relapse prevention and reduced effort in ensuring adherence, and the negative perceptions centred on financial costs and the inconvenience of appointments to receive injections. Conclusion To enhance LAI usage, some of the issues that need to be addressed are the inadequacy of information given to patients, the element of coercion involved in LAI introduction, the pragmatic barriers to LAI uptake by patients, and negative subjective perceptions about LAIs.

Based on prior research, we hypothesized that personal or family familiarity with psychosis would have a different effect on pathways to care as compared to personal or family familiarity with mental disorders.Caregivers of 32 patients receiving treatment for a first episode of psychosis at a specialized early intervention centre provided information regarding their familiarity with psychosis and mental disorders. Information on the duration of untreated psychosis (DUP) and on the duration of untreated illness (DUI) was collected from patients and their caregivers.Although we found a trend in the direction of lowered DUP and longer DUI for those with personal or family familiarity with psychosis, these effects were not statistically significant. A trend was found for a higher DUI for those with personal or family familiarity with mental disorders in general, but this effect was not significant.We did not find that differential familiarity with mental disorders and by extension, personal or family familiarity, affected measures of delay in treatment of a first episode of psychosis. Trends in our findings in the hypothesized directions suggest that a larger sample size may reveal significant differential effects of previous experience with mental disorders in general and psychosis in particular on delay in help seeking during different phases of the illness.