CT1812 biomarker signature from a meta-analysis of CSF proteomic findings from two Phase 2 clinical trials in Alzheimer's disease.

INTRODUCTION: CT1812 is in clinical development for the treatment of Alzheimer's disease (AD). Cerebrospinal fluid (CSF) exploratory proteomics was employed to identify pharmacodynamic biomarkers of CT1812 in mild to moderate AD from two independent clinical trials. METHODS: Unbiased analysis of tandem-mass tag mass spectrometry (TMT-MS) quantitative proteomics, pathway analysis and correlation analyses with volumetric magnetic resonance imaging (vMRI) were performed for the SPARC cohort (NCT03493282). Comparative analyses and a meta-analysis with the interim SHINE cohort (NCT03507790; SHINE-A) followed by network analysis (weighted gene co-expression network analysis [WGCNA]) were used to understand the biological impact of CT1812. RESULTS: CT1812 pharmacodynamic biomarkers and biological pathways were identified that replicate across two clinical cohorts. The meta-analysis revealed novel candidate biomarkers linked to S2R biology and AD, and network analysis revealed treatment-associated networks driven by S2R.  DISCUSSION: Early clinical validation of CT1812 candidate biomarkers replicating in independent cohorts strengthens the understanding of the biological impact of CT1812 in patients with AD, and supports CT1812's synaptoprotective mechanism of action and its continued clinical development. HIGHLIGHTS: This exploratory proteomics study identified candidate biomarkers of CT1812 in SPARC (NCT03493282) Comparative analyses identified biomarkers replicating across trials/cohorts Two independent Ph2 trial cohorts (SPARC and interim SHINE [NCT03507790; SHINE-A]) were used in a meta-analysis Amyloid beta (Aß) & synaptic biology impacted by CT1812 and volumetric magnetic resonance imaging (vMRI) treatment-related correlates emerge Network analyses revealed sigma-2 receptor (S2R)-interacting proteins that may be "drivers" of changes.

Smartphone-based fluorescence spectroscopic device for cervical precancer diagnosis: a random forest classification of in vitro data.

Cervical cancer can be treated and cured if diagnosed at an early stage. Optical devices, developed on smartphone-based platforms, are being tested for this purpose as they are cost-effective, robust, and field portable, showing good efficiency compared to the existing commercial devices. This study reports on the applicability of a 3D printed smartphone-based spectroscopic device (3D-SSD) for the early diagnosis of cervical cancer. The proposed device has the ability to evaluate intrinsic fluorescence (IF) from the collected polarized fluorescence (PF) and elastic-scattering (ES) spectra from cervical tissue samples of different grades. IF spectra of 30 cervical tissue samples have been analyzed and classified using a combination of principal component analysis (PCA) and random forest (RF)-based multi-class classification algorithm with an overall accuracy above 90%. The usage of smartphone for image collection, spectral data analysis, and display makes this device a potential contender for use in clinics as a regular screening tool.

Activity- and memory training-induced acetylation of α-tubulin in the hippocampus.

Posttranslational modifications play crucial roles in synaptic plasticity and memory formation. The important role of histone acetylation is well established in these processes. However, activity-dependent regulation of acetylation of non-histone proteins is not well understood. We previously showed that α-tubulin is acetylated in an activity-dependent manner. Here, we show that cyclin-dependent kinase 5 (CDK5) plays an important role in α-tubulin acetylation induced by KCl depolarization or N-methyl-D-aspartate stimulation of the hippocampal slices. In addition, KCl depolarization inhibits the activity of SIRT2, an α-tubulin deacetylase. The inhibitory effect of KCl on SIRT2 activity requires CDK5 activity. Furthermore, α-tubulin acetylation is enhanced by memory training in object recognition task. These results suggest that memory formation may involve α-tubulin acetylation.

Anti-Müllerian hormone receptor type 2 is expressed in gonadotrophs of postpubertal heifers to control gonadotrophin secretion.

Preantral and small antral follicles may secret anti-Müllerian hormone (AMH) to control gonadotrophin secretion from ruminant gonadotrophs. The present study investigated whether the main receptor for AMH, AMH receptor type 2 (AMHR2), is expressed in gonadotrophs of postpubertal heifers to control gonadotrophin secretion. Expression of AMHR2 mRNA was detected in anterior pituitaries (APs) of postpubertal heifers using reverse transcription-polymerase chain reaction. An anti-AMHR2 chicken antibody was developed against the extracellular region near the N-terminus of bovine AMHR2. Western blotting using this antibody detected the expression of AMHR2 protein in APs. Immunofluorescence microscopy using the same antibody visualised colocalisation of AMHR2 with gonadotrophin-releasing hormone (GnRH) receptor on the plasma membrane of gonadotrophs. AP cells were cultured for 3.5 days and then treated with increasing concentrations (0, 1, 10, 100, or 1000pgmL-1) of AMH. AMH (10-1000pgmL-1) stimulated (P<0.05) basal FSH secretion. In addition, AMH (100-1000pgmL-1) weakly stimulated (P<0.05) basal LH secretion. AMH (100-1000pgmL-1) inhibited GnRH-induced FSH secretion, but not GnRH-induced LH secretion, in AP cells. In conclusion, AMHR2 is expressed in gonadotrophs of postpubertal heifers to control gonadotrophin secretion.

From health for all to universal health coverage: Alma Ata is still relevant.

With increasing adoption of universal health coverage (UHC), the health for all agenda is resurgent around the world. However, after a promising start the first time in 1978, the health for all agenda fizzled over the next decade. This commentary discusses the origin of the health for all agenda in the 1970s and the influence of global politico-economic forces in shaping that agenda, its demise and the resurgence in the form of UHC in the twenty-first century. We discuss UHC's focus on finances and the increasing role of market economy in health care, and the opportunities and risks UHC poses. We conclude by saying that UHC's greater focus on finances is prudent, but in order to achieve its promise, UHC needs to regulate the market based provision of healthcare, and incorporate more of the people and community centered ethos of its earlier iteration from 40 years ago.

Reconsidering the roles of endogenous estrogens and xenoestrogens: the membrane estradiol receptor G protein-coupled receptor 30 (GPR30) mediates the effects of various estrogens.

Estrone (E1) and estriol (E3) are considered "weak" estrogens, which exert suppressive effects through estrogen receptors α and ß. However, recent studies have demonstrated that E1 and E3, as well as estradiol (E2), suppress gonadotropin-releasing hormone-induced luteinizing hormone secretion from bovine gonadotrophs via G-protein-coupled receptor 30, which is expressed in various reproductive organs. Currently, there is a lack of fundamental knowledge regarding E1 and E3, including their blood levels. In addition, xenoestrogens may remain in the body over long time periods because of enterohepatic circulation. Therefore, it is time to reconsider the roles of endogenous estrogens and xenoestrogens for reproduction.

Survey of Ambient Air Pollution Health Risk Assessment Tools.

Designing air quality policies that improve public health can benefit from information about air pollution health risks and impacts, which include respiratory and cardiovascular diseases and premature death. Several computer-based tools help automate air pollution health impact assessments and are being used for a variety of contexts. Expanding information gathered for a May 2014 World Health Organization expert meeting, we survey 12 multinational air pollution health impact assessment tools, categorize them according to key technical and operational characteristics, and identify limitations and challenges. Key characteristics include spatial resolution, pollutants and health effect outcomes evaluated, and method for characterizing population exposure, as well as tool format, accessibility, complexity, and degree of peer review and application in policy contexts. While many of the tools use common data sources for concentration-response associations, population, and baseline mortality rates, they vary in the exposure information source, format, and degree of technical complexity. We find that there is an important tradeoff between technical refinement and accessibility for a broad range of applications. Analysts should apply tools that provide the appropriate geographic scope, resolution, and maximum degree of technical rigor for the intended assessment, within resources constraints. A systematic intercomparison of the tools' inputs, assumptions, calculations, and results would be helpful to determine the appropriateness of each for different types of assessment. Future work would benefit from accounting for multiple uncertainty sources and integrating ambient air pollution health impact assessment tools with those addressing other related health risks (e.g., smoking, indoor pollution, climate change, vehicle accidents, physical activity).

Histone deacetylase inhibition facilitates massed pattern-induced synaptic plasticity and memory.

Massed training is less effective for long-term memory formation than the spaced training. The role of acetylation in synaptic plasticity and memory is now well established. However, the role of this important protein modification in synaptic plasticity induced by massed pattern of stimulation or memory induced by massed training is not well understood. Here we show that increasing the level of acetylation enhances long-term potentiation induced by massed pattern of high frequency stimulation. Furthermore, enhancing acetylation level facilitates long-term memory by massed training. Thus, increasing acetylation level facilitates synaptic plasticity and memory by massed patterns.

Comparison of In Vivo Study of Co-Polarized and Cross-Polarized Fluorescence Spectroscopy to Co-Minus Cross-Polarized Fluorescence Spectroscopy to Diagnose Precancerous Cervical Lesions by Handheld Probe.

Background: In 2020, the number of new cases of cervix uteri was 604,127, i.e., 3.1% of all cancers, and the number of deaths was 341,831 (3.3%) among both sexes. In vivo fluorescence spectroscopy is an emerging optical technology that offers promise for the diagnosis of disease & has the capability to quickly, noninvasively and quantitatively probe the biochemical and morphological changes that occur as tissue becomes dysplastic. Materials and Method: A cross-sectional observational study was conducted from December 2019 to September 2021 in the OBGY Department, UISEMH, in collaboration with optical imaging laboratory, BIOPHOTONICS, IIT Kanpur. A fabricated in-house fluorescence spectroscope consisting of a laser diode (405 nm) as light source and a miniature spectrometer is used to detect fluorescence signal from the sample. Patient's cervix was examined in the OPD, using an optical handheld probe, which functions on the principle of polarized fluorescence spectroscopy. The tissues were examined and classified on the basis of varying patterns of polarized spectroscopy (co-polarized, cross-polarized and co-minus cross-polarized light). The results were compared with that of cytological, colposcopy and histopathological findings and on various demographic variables. Results and Conclusion: In vivo handheld probe based on polarized fluorescence spectroscopy is an excellent screening technique. Co- and cross- polarized light has shown enhanced accuracy. Accuracy of co-minus cross-polarized light is poor. It is fast, noninvasive and quantitative and, with further developments, has the potential to become a regular screening tool in future.

A laboratory perspective on accelerating preparatory processes before earthquakes and implications for foreshock detectability.

Dynamic failure in the laboratory is commonly preceded by many foreshocks which accompany premonitory aseismic slip. Aseismic slip is also thought to govern earthquake nucleation in nature, yet, foreshocks are rare. Here, we examine how heterogeneity due to different roughness, damage and pore pressures affects premonitory slip and acoustic emission characteristics. High fluid pressures increase stiffness and reduce heterogeneity which promotes more rapid slip acceleration and shorter precursory periods, similar to the effect of low geometric heterogeneity on smooth faults. The associated acoustic emission activity in low-heterogeneity samples becomes increasingly dominated by earthquake-like double-couple focal mechanisms. The similarity of fluid pressure increase and roughness reduction suggests that increased stress and geometric homogeneity may substantially shorten the duration of foreshock activity. Gradual fault activation and extended foreshock activity is more likely observable on immature faults at shallow depth.

Cervical pre-cancer classification using entropic features and CNN: In vivo validation with a handheld fluorescence probe.

Cervical cancer is one of the most prevalent forms of cancer, with a lengthy latent period and a gradual onset phase. Conventional techniques are found to be severely lacking in real time detection of disease progression which can greatly enhance the cure rate. Due to their high sensitivity and specificity, optical techniques are emerging as reliable tools, particularly in case of cancer. It has been seen that biochemical changes are better highlighted through intrinsic fluorescence devoid of interference from absorption and scattering. Its effectiveness in in-vivo conditions is affected by the fact that the intrinsic spectral signatures vary from patient to patient, as well as in different population groups. Here, we overcome this limitation by collectively enumerating the subtle changes in the spectral profiles and correlations through an information theory based entropic approach, which significantly amplifies the minute spectral variations. In conjunction with artificial intelligence (AI)/machine learning (ML) tools, it yields high specificity and sensitivity with a small dataset from patients in clinical conditions, without artificial augmentation. We have used an in-house developed handheld probe (i-HHP) for extracting intrinsic fluorescence spectra of human cervix from 110 different subjects drawn from diverse population groups. The average classification accuracy of the proposed methodology using 10-fold cross validation is 93.17%. A combination of polarised fluorescence spectra from i-HHP and the proposed classifier is proven to be minimally invasive with the ability to diagnose patients in real time. This paves the way for effective use of relatively smaller sized sensitive fluorescence data with advanced AI/ML tools for early cervical cancer detection in clinics.

A smartphone-based standalone fluorescence spectroscopy tool for cervical precancer diagnosis in clinical conditions.

Real-time prediction about the severity of noncommunicable diseases like cancers is a boon for early diagnosis and timely cure. Optical techniques due to their minimally invasive nature provide better alternatives in this context than the conventional techniques. The present study talks about a standalone, field portable smartphone-based device which can classify different grades of cervical cancer on the basis of the spectral differences captured in their intrinsic fluorescence spectra with the help of AI/ML technique. In this study, a total number of 75 patients and volunteers, from hospitals at different geographical locations of India, have been tested and classified with this device. A classification approach employing a hybrid mutual information long short-term memory model has been applied to categorize various subject groups, resulting in an average accuracy, specificity, and sensitivity of 96.56%, 96.76%, and 94.37%, respectively using 10-fold cross-validation. This exploratory study demonstrates the potential of combining smartphone-based technology with fluorescence spectroscopy and artificial intelligence as a diagnostic screening approach which could enhance the detection and screening of cervical cancer.

Excessive Protein Accumulation and Impaired Autophagy in the Hippocampus of Angelman Syndrome Modeled in Mice.

BACKGROUND: Angelman syndrome (AS), a neurodevelopmental disorder caused by abnormalities of the 15q11.2-q13.1 chromosome region, is characterized by impairment of cognitive and motor functions, sleep problems, and seizures. How the genetic defects of AS produce these neurological symptoms is unclear. Mice modeling AS (AS mice) accumulate activity-regulated cytoskeleton-associated protein (ARC/ARG3.1), a neuronal immediate early gene (IEG) critical for synaptic plasticity. This accumulation suggests an altered protein metabolism. METHODS: Focusing on the dorsal hippocampus (dHC), a brain region critical for memory formation and cognitive functions, we assessed levels and tissue distribution of IEGs, de novo protein synthesis, and markers of protein synthesis, endosomes, autophagy, and synaptic functions in AS mice at baseline and following learning. We also tested autophagic flux and memory retention following autophagy-promoting treatment. RESULTS: AS dHC exhibited accumulation of IEGs ARC, FOS, and EGR1; autophagy proteins MLP3B, SQSTM1, and LAMP1; and reduction of the endosomal protein RAB5A. AS dHC also had increased levels of de novo protein synthesis, impaired autophagic flux with accumulation of autophagosome, and altered synaptic protein levels. Contextual fear conditioning significantly increased levels of IEGs and autophagy proteins, de novo protein synthesis, and autophagic flux in the dHC of normal mice, but not in AS mice. Enhancing autophagy in the dHC alleviated AS-related memory and autophagic flux impairments. CONCLUSIONS: A major biological deficit of AS brain is a defective protein metabolism, particularly that dynamically regulated by learning, resulting in stalled autophagy and accumulation of neuronal proteins. Activating autophagy ameliorates AS cognitive impairments and dHC protein accumulation.

Neuronal activity drives IGF2 expression from pericytes to form long-term memory.

Investigations of memory mechanisms have been, thus far, neuron centric, despite the brain comprising diverse cell types. Using rats and mice, we assessed the cell-type-specific contribution of hippocampal insulin-like growth factor 2 (IGF2), a polypeptide regulated by learning and required for long-term memory formation. The highest level of hippocampal IGF2 was detected in pericytes, the multi-functional mural cells of the microvessels that regulate blood flow, vessel formation, the blood-brain barrier, and immune cell entry into the central nervous system. Learning significantly increased pericytic Igf2 expression in the hippocampus, particularly in the highly vascularized stratum lacunosum moleculare and stratum moleculare layers of the dentate gyrus. Igf2 increases required neuronal activity. Regulated hippocampal Igf2 knockout in pericytes, but not in fibroblasts or neurons, impaired long-term memories and blunted the learning-dependent increase of neuronal immediate early genes (IEGs). Thus, neuronal activity-driven signaling from pericytes to neurons via IGF2 is essential for long-term memory.

Fermatean fuzzy CRITIC-EDAS approach for the selection of sustainable third-party reverse logistics providers using improved generalized score function.

In today's world, the demand for sustainable third-party reverse logistics providers (S3PRLPs) becomes an increasingly considerable issue for industries seeking improved customer service, cost reduction and sustainability perspectives. However, the assessment and selection of right S3PRLP is a complex uncertain decision-making problem due to involvement of numerous conflicting attributes, imprecise human mind and lack of information. Recently, Fermatean fuzzy set (FFS) has been recognized as one of the suitable tools to tackle the uncertain and inaccurate information. In this paper, we introduce a hybrid methodology based on CRITIC and EDAS methods with Fermatean fuzzy sets (FFSs) to solve the S3PRLP selection problem in which the attributes and decision makers' weights are completely unknown. In this framework, CRITIC approach is applied to calculate the attribute weight and EDAS method is used to evaluate the priority order of S3PRLP options. To do this, a new improved generalized score function (IGSF) is developed with its elegant properties. Also, a formula is discussed to calculate the decision makers' weights based on the developed IGSF. Next, developed framework is applied to assess a case study of S3PRLP selection problem with Fermatean fuzzy information, which elucidates the usefulness and practicality of the proposed method. Finally, comparative study is implemented to show the strength of introduced framework with extant approaches. The outcomes of the work confirm that the introduced approach is more feasible and well-consistent with the other extant approaches.

Improving quality of antenatal care services in a high case load tertiary care teaching hospital (Ganesh Shankar Vidyarthi Memorial (GSVM) Medical College) in Kanpur, Uttar Pradesh, India.

In India, half of all pregnant women between the ages of 15 and 49 years are anaemic. In Uttar Pradesh (UP), this figure is slightly higher at 51%. Unfortunately, only 5.4% pregnant women received full antenatal care (ANC) (National Family Health Survey 4, 2015-2016). A formative research conducted in UP in 2016 found that only 9% of pregnant women in UP consume the five recommended food groups, as per global recommendations.Ganesh Shankar Vidyarthi Memorial Medical College Hospital is one of the four high case load tertiary care facilities in Kanpur, UP, with an obstetrics and gynaecology (OBGY) outpatient department (OPD) of 2500-3000 consultations with delivery load of 250-300 deliveries per month and paediatric OPD of approximately 5400-6000 consultations per month. It was identified that pregnant women visiting the OPD for ANC were not receiving maternal nutrition-related services, and anthropometric measurements to assess nutritional status and gestational weight gain were also not done.The department of OBGY decided to apply the four-step Point of Care Quality Improvement (POCQI) approach using Plan-Do-Study-Act cycle for implementation of the maternal nutrition protocol during ANC.In April 2019, with the support of A&T, the hospital team applied the POCQI methodology to improve ANC service provision. By the end of 2019, the measurement and recording of anthropometric parameters increased to 84% and 74% for height and weight, respectively, from the baseline of zero. Hb testing increased from 58% to 84% and blood pressure (BP) monitoring from zero to 84%. Maternal nutrition counselling was delivered to 76% of the pregnant women visiting the OPD, which was a significant achievement for a new practice introduced into the system.The improved practices identified and implemented by the department are being sustained through active engagement of the staff and supportive leadership of the department of OBGY.

Autophagy coupled to translation is required for long-term memory.

An increase in protein synthesis following learning is a fundamental and evolutionarily conserved mechanism of long-term memory. To maintain homeostasis, this protein synthesis must be counterbalanced by mechanisms such as protein degradation. Recent studies reported that macroautophagy/autophagy, a major protein degradation mechanism, is required for long-term memory formation. However, how learning regulates autophagy and recruits it into long-term memory formation remains to be established. Here, we show that inhibitory avoidance in rats significantly increases the levels of autophagy and lysosomal degradation proteins, including BECN1/beclin 1, LC3-II, SQSTM1/p62 and LAMP1, as well as autophagic flux in the hippocampus. Moreover, pharmacological inhibition or targeted molecular disruption of the learning-induced autophagy impairs long-term memory, leaving short-term memory intact. The increase in autophagy proteins results from active translation of their mRNA and not from changes in their total mRNA levels. Additionally, the induction of autophagy requires the immediate early gene Arc/Arg3.1. Finally, in contrast to classical regulation of autophagy in other systems, we found that the increase in autophagy upon learning is dispensable for the increase in protein synthesis. We conclude that coupling between learning-induced translation and autophagy, rather than translation per se, is an essential mechanism of long-term memory.Abbreviations: AAV: adeno-associated virus; ARC/ARG3.1: activity regulated cytoskeletal-associated protein; ATG: autophagy related; DG: dentate gyrus; GFP: green fluorescent protein; IA: inhibitory avoidance; LAMP1: lysosomal-associated membrane protein 1; MAP1LC3B/LC3B: microtubule-associated protein 1 light chain 3 beta; ODN: oligodeoxynucleotide; qPCR: quantitative polymerase chain reaction; SBI: SBI0206965; SQSTM1/p62: sequestosome 1; SUnSET: surface sensing of translation; TRAP: translating ribosome affinity purification; ULK1: unc-51 like kinase 1.

COVID-19 control strategies and intervention effects in resource limited settings: A modeling study.

INTRODUCTION: Many countries with weaker health systems are struggling to put together a coherent strategy against the COVID-19 epidemic. We explored COVID-19 control strategies that could offer the greatest benefit in resource limited settings. METHODS: Using an age-structured SEIR model, we explored the effects of COVID-19 control interventions-a lockdown, physical distancing measures, and active case finding (testing and isolation, contact tracing and quarantine)-implemented individually and in combination to control a hypothetical COVID-19 epidemic in Kathmandu (population 2.6 million), Nepal. RESULTS: A month-long lockdown will delay peak demand for hospital beds by 36 days, as compared to a base scenario of no intervention (peak demand at 108 days (IQR 97-119); a 2 month long lockdown will delay it by 74 days, without any difference in annual mortality, or healthcare demand volume. Year-long physical distancing measures will reduce peak demand to 36% (IQR 23%-46%) and annual morality to 67% (IQR 48%-77%) of base scenario. Following a month long lockdown with ongoing physical distancing measures and an active case finding intervention that detects 5% of the daily infection burden could reduce projected morality and peak demand by more than 99%. CONCLUSION: Limited resource settings are best served by a combination of early and aggressive case finding with ongoing physical distancing measures to control the COVID-19 epidemic. A lockdown may be helpful until combination interventions can be put in place but is unlikely to reduce annual mortality or healthcare demand.

Autophagy-targeted therapy to modulate age-related diseases: Success, pitfalls, and new directions.

Autophagy is a critical metabolic process that supports homeostasis at a basal level and is dynamically regulated in response to various physiological and pathological processes. Autophagy has some etiologic implications that support certain pathological processes due to alterations in the lysosomal-degradative pathway. Some of the conditions related to autophagy play key roles in highly relevant human diseases, e.g., cardiovascular diseases (15.5%), malignant and other neoplasms (9.4%), and neurodegenerative conditions (3.7%). Despite advances in the discovery of new strategies to treat these age-related diseases, autophagy has emerged as a therapeutic option after preclinical and clinical studies. Here, we discuss the pitfalls and success in regulating autophagy initiation and its lysosome-dependent pathway to restore its homeostatic role and mediate therapeutic effects for cancer, neurodegenerative, and cardiac diseases. The main challenge for the development of autophagy regulators for clinical application is the lack of specificity of the repurposed drugs, due to the low pharmacological uniqueness of their target, including those that target the PI3K/AKT/mTOR and AMPK pathway. Then, future efforts must be conducted to deal with this scenery, including the disclosure of key components in the autophagy machinery that may intervene in its therapeutic regulation. Among all efforts, those focusing on the development of novel allosteric inhibitors against autophagy inducers, as well as those targeting autolysosomal function, and their integration into therapeutic regimens should remain a priority for the field.

Ambient particulate pollution and the world-wide prevalence of asthma, rhinoconjunctivitis and eczema in children: Phase One of the International Study of Asthma and Allergies in Childhood (ISAAC).

OBJECTIVES: To investigate the effect of ambient particulate matter on variation in childhood prevalence of asthma, rhinoconjunctivitis and eczema. METHODS: Prevalences of asthma, rhinoconjunctivitis and eczema obtained in Phase One of the International Study of Asthma and Allergies in Childhood (ISAAC) were matched with city-level estimates of residential PM(10) obtained from a World Bank model. Associations were investigated using binomial regression adjusting for GNP per capita and for clustering within country. For countries with more than one centre, a two stage meta-analysis was carried out. The results were compared with a meta-analysis of published multi-centre studies. RESULTS: Annual concentrations of PM(10) at city level were obtained for 105 ISAAC centres in 51 countries. After controlling for GNP per capita, there was a weak negative association between PM(10) and various outcomes. For severe wheeze in 13-14-year-olds, the OR for a 10 microg/m(3) increase in PM(10) was 0.92 (95% CI 0.84 to 1.00). In 24 countries with more than one centre, most summary estimates for within-country associations were weakly positive. For severe wheeze in 13-14-year-olds, the summary OR for a 10 microg/m(3) increase in PM(10) was 1.01 (0.92 to 1.10). This result was close to a summary OR of 0.99 (0.91 to 1.06) obtained from published multi-centre studies. CONCLUSIONS: Modelled estimates of particulate matter at city level are imprecise and incomplete estimates of personal exposure to ambient air pollutants. Nevertheless, our results together with those of previous multi-centre studies, suggest that urban background PM(10) has little or no association with the prevalence of childhood asthma, rhinoconjunctivitis or eczema either within or between countries.