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High-power lasers are vital for particle acceleration, imaging, fusion and materials processing, requiring precise control and high-energy delivery. Laser plasma accelerators (LPAs) demand laser positional stability at focus to ensure consistent electron beams in applications such as X-ray free-electron lasers and high-energy colliders. Achieving this stability is especially challenging for the low-repetition-rate lasers in current LPAs. We present a machine learning method that predicts and corrects laser pointing instabilities in real-time using a high-frequency pilot beam. By preemptively adjusting a correction mirror, this approach overcomes traditional feedback limits. Demonstrated on the BELLA petawatt laser operating at the terawatt level (30 mJ amplification), our method achieved root mean square pointing stabilization of 0.34 and 0.59 $\unicode{x3bc} \mathrm{rad}$ in the x and y directions, reducing jitter by 65% and 47%, respectively. This is the first successful application of predictive control for shot-to-shot stabilization in low-repetition-rate laser systems, paving the way for full-energy petawatt lasers and transformative advances across science, industry and security.
Numerous studies have indicated that turbulence typically initiates along the boundary layer of the stationary disk within a rotor–stator cavity. To describe the transition process to turbulence on the stationary side of a closed rotor–stator cavity, a comprehensive approach combining global linear stability analysis with direct numerical simulation was adopted in the present study. The proposed model aligns with that of Yim et al. (J. Fluid Mech., vol. 848, 2018, pp. 631–647), who investigated the stability characteristics of the rotating-disk boundary layer in a rotor–stator cavity. In order to achieve a stable inflow for the stationary-disk boundary layer, we rotate the shroud together with the rotating disk. Through careful global stability analysis, the predominant spiral mode exhibiting the highest instability in the boundary layer of the stationary disk was discerned, corroborating observations from simulations. Initially, the spiral mode undergoes linear amplification, reaches a state of linear saturation and enters the nonlinear regime. Following nonlinear saturation in the flow field, a circular wave mode arises due to the influence of mean flow distortion. As the Reynolds number attained a sufficiently high level, the interplay between the downstream-propagating circular mode and spiral mode amplified disturbances in the boundary layer of the stationary disk, ultimately leading to the development of localised turbulence at the mid-radius of the rotor–stator cavity. Notably, the present study is the first to elucidate the coexistence of laminar–transitional–turbulent flow states in the stationary-disk boundary layer through direct numerical simulations.
Oil palm has been criticized for being an environmentally unfriendly oil crop. In recent decades, oil palm plantations have extended into conservation landscapes, causing severe environmental damage and harming biodiversity. Nevertheless, oil palm remains a highly productive oil crop from which most of the world's vegetable oil is produced. Therefore, measuring the environmental impact of oil palm plantations and identifying suitable land to support its sustainable development is crucial.
Technical summary
To meet the rising global palm oil demand sustainably, we tracked annual land cover changes in oil palm plantation and mapped areas worldwide suitable for sustainable oil palm cultivation. From 1982 to 2019, 3.6 Mha of forests were converted to oil palm plantations. Despite a recent decline in overall conversion, the shift from forest to oil palm plantations has become increasingly more common over the last decade, rising from 14.1 to 34.5% between 2009 and 2019. During 1982–2019, 2.23 Mha of peatland and 0.1 Mha of protected areas were converted for oil palm plantations. The potential sustainable land amounts to 103.5–317.9 Mha (Asia: 44.6–105.1 Mha, Africa: 34.7–96.4 Mha, and Latin America: 35.2–116.5 Mha). Future oil palm expansion is anticipated to take place in countries like Brazil, Nigeria, Colombia, Indonesia, Ivory Coast, the Democratic Republic of the Congo, and Ghana, where more sustainable land is available for cultivation. Malaysia, on the other hand, is about to exceed the area of sustainable cultivation, and further expansion is not recommended. These findings can advance our understanding of the environmentally damaging impacts of oil palm and enhance the feasibility of sustainable oil palm development.
Social media summary
How should suitable land be chosen for the establishment of oil palm plantations to support the sustainable development of the oil palm plantation industry?
Fine mapping and discovery of watermelon rind trait candidate genes are of great significance for modern watermelon breeding and development. In this study, we used the high-resolution genetic mapping and genome-wide genetic variation detection technology, combined with genome survey and sequencing technology, to locate and discover the candidate genes for rind traits of star watermelon varieties ‘Su XuanBai’ and ‘SHLX21’. Firstly, we identified a total of eight quantitative trait loci (QTLs) related to watermelon rind traits on chromosome 6. Secondly, a total of 208,240 single nucleotide polymorphisms and 75,345 small Indels (insertions/deletions) were detected in the two parents by high-coverage re-sequencing, respectively. Based on the genetic variation of the two parents and combined with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using the planta database, the QTL region was reduced to 0.02 Mb. Finally, we identified the six potential regulatory factors for watermelon rind traits using real-time quantitative PCR. In conclusion, our results revealed the fine localization of candidate genes for watermelon rind traits and the successful discovery of candidate genes for regulating watermelon rind traits, which is of importance for watermelon rind traits and breeding-improved watermelon varieties.
COVID-19 lockdowns increased the risk of mental health problems, especially for children with autism spectrum disorder (ASD). However, despite its importance, little is known about the protective factors for ASD children during the lockdowns.
Methods
Based on the Shanghai Autism Early Developmental Cohort, 188 ASD children with two visits before and after the strict Omicron lockdown were included; 85 children were lockdown-free, while 52 and 51 children were under the longer and the shorter durations of strict lockdown, respectively. We tested the association of the lockdown group with the clinical improvement and also the modulation effects of parent/family-related factors on this association by linear regression/mixed-effect models. Within the social brain structures, we examined the voxel-wise interaction between the grey matter volume and the identified modulation effects.
Results
Compared with the lockdown-free group, the ASD children experienced the longer duration of strict lockdown had less clinical improvement (β = 0.49, 95% confidence interval (CI) [0.19–0.79], p = 0.001) and this difference was greatest for social cognition (2.62 [0.94–4.30], p = 0.002). We found that this association was modulated by parental agreeableness in a protective way (−0.11 [−0.17 to −0.05], p = 0.002). This protective effect was enhanced in the ASD children with larger grey matter volumes in the brain's mentalizing network, including the temporal pole, the medial superior frontal gyrus, and the superior temporal gyrus.
Conclusions
This longitudinal neuroimaging cohort study identified that the parental agreeableness interacting with the ASD children's social brain development reduced the negative impact on clinical symptoms during the strict lockdown.
To identify risk genes whose expression are regulated by the reported risk variants and to explore the potential regulatory mechanism in schizophrenia (SCZ).
Methods
We systematically integrated three independent brain expression quantitative traits (eQTLs) (CommonMind, GTEx, and BrainSeq Phase 2, a total of 1039 individuals) and GWAS data (56 418 cases and 78 818 controls), with the use of transcriptome-wide association study (TWAS). Diffusion magnetic resonance imaging was utilized to quantify the integrity of white matter bundles and determine whether polygenic risk of novel genes linked to brain structure was present in patients with first-episode antipsychotic SCZ.
Results
TWAS showed that eight risk genes (CORO7, DDAH2, DDHD2, ELAC2, GLT8D1, PCDHA8, THOC7, and TYW5) reached transcriptome-wide significance (TWS) level. These findings were confirmed by an independent integrative approach (i.e. Sherlock). We further conducted conditional analyses and identified the potential risk genes that driven the TWAS association signal in each locus. Gene expression analysis showed that several TWS genes (including CORO7, DDAH2, DDHD2, ELAC2, GLT8D1, THOC7 and TYW5) were dysregulated in the dorsolateral prefrontal cortex of SCZ cases compared with controls. TWS genes were mainly expressed on the surface of glutamatergic neurons, GABAergic neurons, and microglia. Finally, SCZ cases had a substantially greater TWS genes-based polygenic risk (PRS) compared to controls, and we showed that fractional anisotropy of the cingulum-hippocampus mediates the influence of TWS genes PRS on SCZ.
Conclusions
Our findings identified novel SCZ risk genes and highlighted the importance of the TWS genes in frontal-limbic dysfunctions in SCZ, indicating possible therapeutic targets.
Inflammation plays a crucial role in the pathogenesis of major depressive disorder (MDD) and bipolar disorder (BD). This study aimed to examine whether the dysregulation of complement components contributes to brain structural defects in patients with mood disorders.
Methods
A total of 52 BD patients, 35 MDD patients, and 53 controls were recruited. The human complement immunology assay was used to measure the levels of complement factors. Whole brain-based analysis was performed to investigate differences in gray matter volume (GMV) and cortical thickness (CT) among the BD, MDD, and control groups, and relationships were explored between neuroanatomical differences and levels of complement components.
Results
GMV in the medial orbital frontal cortex (mOFC) and middle cingulum was lower in both patient groups than in controls, while the CT of the left precentral gyrus and left superior frontal gyrus were affected differently in the two disorders. Concentrations of C1q, C4, factor B, factor H, and properdin were higher in both patient groups than in controls, while concentrations of C3, C4 and factor H were significantly higher in BD than in MDD. Concentrations of C1q, factor H, and properdin showed a significant negative correlation with GMV in the mOFC at the voxel-wise level.
Conclusions
BD and MDD are associated with shared and different alterations in levels of complement factors and structural impairment in the brain. Structural defects in mOFC may be associated with elevated levels of certain complement factors, providing insight into the shared neuro-inflammatory pathogenesis of mood disorders.
The impact of the dietary potential inflammatory effect on diabetic kidney disease (DKD) has not been adequately investigated. The present study aimed to explore the association between dietary inflammatory index (DII) and DKD in US adults.
Design:
This is a cross-sectional study.
Setting:
Data from the National Health and Nutrition Examination Survey (2007–2016) were used. DII was calculated from 24-h dietary recall interviews. DKD was defined as diabetes with albuminuria, impaired glomerular filtration rate or both. Logistic regression and restricted cubic spline models were adopted to evaluate the associations.
Participants:
Data from the National Health and Nutrition Examination Survey (2007–2016) were used, which can provide the information of participants.
Results:
Four thousand two-hundred and sixty-four participants were included in this study. The adjusted OR of DKD was 1·04 (95 % CI 0·81, 1·36) for quartile 2, 1·24 (95 % CI 0·97, 1·59) for quartile 3 and 1·64 (95 % CI 1·24, 2·17) for quartile 4, respectively, compared with the quartile 1 of DII. A linear dose–response pattern was observed between DII and DKD (Pnonlinearity = 0·73). In the stratified analyses, the OR for quartile 4 of DII were significant among adults with higher educational level (OR 1·83, 95 % CI 1·26, 2·66) and overweight or obese participants (OR 1·67, 95 % CI 1·23, 2·28), but not among the corresponding another subgroup. The interaction effects between DII and stratified factors on DKD were not statistically significant (all P values for interactions were >0·05).
Conclusions:
Our findings suggest that a pro-inflammatory diet, shown by a higher DII score, is associated with increased odd of DKD.
Grey matter (GM) reduction is a consistent observation in established late stages of schizophrenia, but patients in the untreated early stages of illness display an increase as well as a decrease in GM distribution relative to healthy controls (HC). The relative excess of GM may indicate putative compensatory responses, though to date its relevance is unclear.
Methods
343 first-episode treatment-naïve patients with schizophrenia (FES) and 342 HC were recruited. Multivariate source-based morphometry was performed to identify covarying ‘networks' of grey matter concentration (GMC). Neurocognitive scores using the Cambridge Neuropsychological Test Automated Battery (CANTAB) and symptom burden using the Positive and Negative Symptoms Scale (PANSS) were obtained. Bivariate linear relationships between GMC and cognition/symptoms were studied.
Results
Compared to healthy subjects, FES had prominently lower GMC in two components; the first consists of the anterior insula, inferior frontal gyrus, anterior cingulate and the second component with the superior temporal gyrus, precuneus, inferior/superior parietal lobule, cuneus, and lingual gyrus. Higher GMC was seen in adjacent areas of the middle and superior temporal gyrus, middle frontal gyrus, inferior parietal cortex and putamen. Greater GMC of this component was associated with lower duration of untreated psychosis, less severe positive symptoms and better performance on cognitive tests.
Conclusions
In untreated stages of schizophrenia, both a distributed lower and higher GMC is observable. While the higher GMC is relatively modest, it occurs across frontoparietal, temporal and subcortical regions in association with reduced illness burden suggesting a compensatory role for higher GMC in the early stages of schizophrenia.
In [2], Beilinson–Lusztig–MacPherson (BLM) gave a beautiful realization for quantum $\mathfrak {gl}_n$ via a geometric setting of quantum Schur algebras. We introduce the notion of affine Schur superalgebras and use them as a bridge to link the structure and representations of the universal enveloping superalgebra ${\mathcal U}_{\mathbb Q}(\widehat {\mathfrak {gl}}_{m|n})$ of the loop algebra $\widehat {\mathfrak {gl}}_{m|n}$ of ${\mathfrak {gl}}_{m|n}$ with those of affine symmetric groups ${\widehat {{\mathfrak S}}_{r}}$. Then, we give a BLM type realization of ${\mathcal U}_{\mathbb Q}(\widehat {\mathfrak {gl}}_{m|n})$ via affine Schur superalgebras.
The first application of the realization of ${\mathcal U}_{\mathbb Q}(\widehat {\mathfrak {gl}}_{m|n})$ is to determine the action of ${\mathcal U}_{\mathbb Q}(\widehat {\mathfrak {gl}}_{m|n})$ on tensor spaces of the natural representation of $\widehat {\mathfrak {gl}}_{m|n}$. These results in epimorphisms from $\;{\mathcal U}_{\mathbb Q}(\widehat {\mathfrak {gl}}_{m|n})$ to affine Schur superalgebras so that the bridging relation between representations of ${\mathcal U}_{\mathbb Q}(\widehat {\mathfrak {gl}}_{m|n})$ and ${\widehat {{\mathfrak S}}_{r}}$ is established. As a second application, we construct a Kostant type $\mathbb Z$-form for ${\mathcal U}_{\mathbb Q}(\widehat {\mathfrak {gl}}_{m|n})$ whose images under the epimorphisms above are exactly the integral affine Schur superalgebras. In this way, we obtain essentially the super affine Schur–Weyl duality in arbitrary characteristics.
Deficits in event-related potential (ERP) including duration mismatch negativity (MMN) and P3a have been demonstrated widely in chronic schizophrenia (SZ) but inconsistent findings were reported in first-episode patients. Psychotropic medications and diagnosis might contribute to different findings on MMN/P3a ERP in first-episode patients. The present study examined MMN and P3a in first episode drug naïve SZ and bipolar disorder (BPD) patients and explored the relationships among ERPs, neurocognition and global functioning.
Methods
Twenty SZ, 24 BPD and 49 age and sex-matched healthy controls were enrolled in this study. Data of clinical symptoms [Positive and Negative Symptoms Scale (PANSS), Young Manic Rating Scale (YMRS), Hamilton Depression Rating Scale (HAMD)], neurocognition [Wechsler Adult Intelligence Scale (WAIS), Cattell's Culture Fair Intelligence Test (CCFT), Delay Matching to Sample (DMS), Rapid Visual Information Processing (RVP)], and functioning [Functioning Assessment Short Test (FAST)] were collected. P3a and MMN were elicited using a passive auditory oddball paradigm.
Results
Significant MMN and P3a deficits and impaired neurocognition were found in both SZ and BPD patients. In SZ, MMN was significantly correlated with FAST (r = 0.48) and CCFT (r = −0.31). In BPD, MMN was significantly correlated with DMS (r = −0.54). For P3a, RVP and FAST scores were significant predictors in SZ, whereas RVP, WAIS and FAST were significant predictors in BPD.
Conclusions
The present study found deficits in MMN, P3a, neurocognition in drug naïve SZ and BPD patients. These deficits appeared to link with levels of higher-order cognition and functioning.
Schizophrenia is a severe and complex psychiatric disorder that needs treatment based on extensive experience. Antipsychotic drugs have already become the cornerstone of the treatment for schizophrenia; however, the therapeutic effect is of significant variability among patients, and only around a third of patients with schizophrenia show good efficacy. Meanwhile, drug-induced metabolic syndrome and other side-effects significantly affect treatment adherence and prognosis. Therefore, strategies for drug selection are desperately needed. In this study, we will perform pharmacogenomics research and set up an individualised preferred treatment prediction model.
Aims
We aim to create a standard clinical cohort, with multidimensional index assessment of antipsychotic treatment for patients with schizophrenia.
Method
This trial is designed as a randomised clinical trial comparing treatment with different kinds of antipsychotics. A total sample of 2000 patients with schizophrenia will be recruited from in-patient units from five clinical research centres. Using a computer-generated program, the participants will be randomly assigned to four treatment groups: aripiprazole, olanzapine, quetiapine and risperidone. The primary outcomes will be measured as changes in the Positive and Negative Syndrome Scale of schizophrenia, which reflects the efficacy. Secondary outcomes include the measure of side-effects, such as metabolic syndromes. The efficacy evaluation and side-effects assessment will be performed at baseline, 2 weeks, 6 weeks and 3 months.
Results
This trial will assess the efficacy and side effects of antipsychotics and create a standard clinical cohort with a multi-dimensional index assessment of antipsychotic treatment for schizophrenia patients.
Conclusion
This study aims to set up an individualized preferred treatment prediction model through the genetic analysis of patients using different kinds of antipsychotics.
To assess the relationship between the neutrophil-to-lymphocyte ratio (NLR) and related parameters to the severity of coronavirus disease 2019 (COVID-19) symptoms. Clinical data from 38 COVID-19 patients who were diagnosed, treated and discharged from the Qishan Hospital in Yantai over the period from January to February 2020 were analysed. NLR and procalcitonin (PCT) were determined in the first and fourth weeks after their admission, along with the clinical characteristics and laboratory test results of these patients. Based on results as obtained on the first and fourth weeks after admission, five indices consisting of NLR, white blood cells, neutrophils, lymphocytes (LY) and monocytes (MON) were selected to generate receiver operating characteristic curves, while optimal cutoff values, sensitivities and specificities were obtained according to the Yuden index. Statistically significant differences in neutrophils, LY and the NLR were present in the severe vs. moderate COVID-19 group from the first to the fourth week of their hospitalisation. The cut-off value of NLR for predicting the severity of COVID-19 was 4.425, with a sensitivity of 0.855 and a specificity of 0.979. A statistically significant positive correlation was present between PCT and NLR in the severe group as determined within the first week of admission. NLR can serve as a predictor of COVID-19 disease severity as patients' progress from the first to the fourth week of their hospitalisation. The statistically significant positive correlation between levels of NLR and PCT in severe patients indicated that increases in NLR were accompanied with gradual increases in PCT.
Partial differential equations (PDEs) are used with huge success to model phenomena across all scientific and engineering disciplines. However, across an equally wide swath, there exist situations in which PDEs fail to adequately model observed phenomena, or are not the best available model for that purpose. On the other hand, in many situations, nonlocal models that account for interaction occurring at a distance have been shown to more faithfully and effectively model observed phenomena that involve possible singularities and other anomalies. In this article we consider a generic nonlocal model, beginning with a short review of its definition, the properties of its solution, its mathematical analysis and of specific concrete examples. We then provide extensive discussions about numerical methods, including finite element, finite difference and spectral methods, for determining approximate solutions of the nonlocal models considered. In that discussion, we pay particular attention to a special class of nonlocal models that are the most widely studied in the literature, namely those involving fractional derivatives. The article ends with brief considerations of several modelling and algorithmic extensions, which serve to show the wide applicability of nonlocal modelling.
Understanding the patterns of treatment response is critical for the treatment of patients with schizophrenia; one way to achieve this is through using a longitudinal dynamic process study design.
Aims
This study aims to explore the response trajectory of antipsychotics and compare the treatment responses of seven different antipsychotics over 6 weeks in patients with schizoprenia (trial registration: Chinese Clinical Trials Registry Identifier: ChiCTR-TRC-10000934).
Method
Data were collected from a multicentre, randomised open-label clinical trial. Patients were evaluated with the Positive and Negative Syndrome Scale (PANSS) at baseline and follow-up at weeks 2, 4 and 6. Trajectory groups were classified by the method of k-means cluster modelling for longitudinal data. Trajectory analyses were also employed for the seven antipsychotic groups.
Results
The early treatment response trajectories were classified into a high-trajectory group of better responders and a low-trajectory group of worse responders. The results of trajectory analysis showed differences compared with the classification method characterised by a 50% reduction in PANSS scores at week 6. A total of 349 patients were inconsistently grouped by the two methods, with a significant difference in the composition ratio of treatment response groups using these two methods (χ2 = 43.37, P < 0.001). There was no differential contribution of high- and low trajectories to different drugs (χ2 = 12.52, P = 0.051); olanzapine and risperidone, which had a larger proportion in the >50% reduction at week 6, performed better than aripiprazole, quetiapine, ziprasidone and perphenazine.
Conclusions
The trajectory analysis of treatment response to schizophrenia revealed two distinct trajectories. Comparing the treatment responses to different antipsychotics through longitudinal analysis may offer a new perspective for evaluating antipsychotics.
To eliminate the toxic effect of chemotherapy drug of lobaplatin (LBP) on body tissue in liver cancer therapy, this work prepared a nanodrug carrier based on polyethylene glycol-modified carbon nanotubes (PEG–CNTs) and then constructed a targeted drug delivery system (LBP–PEG–CNTs) by loading LBP on PEG–CNTs. Fluorescein isothiocyanate (FITC) was used to label PEG–CNTs to observe the cellular uptake of PEG–CNTs. In addition, the inhibitions of LBP–PEG–CNTs on HepG2 cells were investigated. The results show that the FITC-labeled PEG–CNTs have good cell penetrability; meanwhile, LBP–PEG–CNTs have good stability, pH-controlled release property, and high inhibition rate on HepG2 cells. To be specific, 80% of LBP is released under physiological conditions of liver cancer cells at pH 5.0, and LBP–PEG–CNTs show a high inhibition rate of 77.86% on HepG2 cells, demonstrating that they have targeted, pH-controlled release and inhibition properties on HepG2 cells.
This paper is concerned with numerical approximations of a nonlocal heat equation define on an infinite domain. Two classes of artificial boundary conditions (ABCs) are designed, namely, nonlocal analog Dirichlet-to-Neumann-type ABCs (global in time) and high-order Padé approximate ABCs (local in time). These ABCs reformulate the original problem into an initial-boundary-value (IBV) problem on a bounded domain. For the global ABCs, we adopt a fast evolution to enhance computational efficiency and reduce memory storage. High order fully discrete schemes, both second-order in time and space, are given to discretize two reduced problems. Extensive numerical experiments are carried out to show the accuracy and efficiency of the proposed methods.
Choline and betaine are essential nutrients involved in one-carbon metabolism and have been hypothesised to affect breast cancer risk. Functional polymorphisms in genes encoding choline-related one-carbon metabolism enzymes, including phosphatidylethanolamine N-methyltransferase (PEMT), choline dehydrogenase (CHDH) and betaine-homocysteine methyltransferase (BHMT), have important roles in choline metabolism and may thus interact with dietary choline and betaine intake to modify breast cancer risk. This study aimed to investigate the interactive effect of polymorphisms in PEMT, BHMT and CHDH genes with choline/betaine intake on breast cancer risk among Chinese women. This hospital-based case–control study consecutively recruited 570 cases with histologically confirmed breast cancer and 576 age-matched (5-year interval) controls. Choline and betaine intakes were assessed by a validated FFQ, and genotyping was conducted for PEMT rs7946, CHDH rs9001 and BHMT rs3733890. OR and 95 % CI were estimated using unconditional logistic regression. Compared with the highest quartile of choline intake, the lowest intake quartile showed a significant increased risk of breast cancer. The SNP PEMT rs7946, CHDH rs9001 and BHMT rs3733890 had no overall association with breast cancer, but a significant risk reduction was observed among postmenopausal women with AA genotype of BHMT rs3733890 (OR 0·49; 95 % CI 0·25, 0·98). Significant interactions were observed between choline intake and SNP PEMT rs7946 (Pinteraction=0·029) and BHMT rs3733890 (Pinteraction=0·006) in relation to breast cancer risk. Our results suggest that SNP PEMT rs7946 and BHMT rs3733890 may interact with choline intake on breast cancer risk.
Findings from observational studies have suggested a possible relation between Ca and breast cancer risk. However, the results of these studies are inconclusive, and the dose–response relationship between Ca intake and risk of breast cancer remains to be determined. A meta-analysis of prospective studies was conducted to address these issues. PubMed and Embase databases were searched for relevant studies concerning the association between Ca intake and breast cancer up to March 2016. The summary relative risks (RR) with 95 % CI were calculated with a random-effects model. The final analysis included eleven prospective cohort studies involving 26 606 cases and 872 895 participants. The overall RR of breast cancer for high v. low intake of Ca was 0·92 (95 % CI 0·85, 0·99), with moderate heterogeneity (P=0·026, I2=44·2 %). In the subgroup analysis, the inverse association appeared stronger for premenopausal breast cancer (RR 0·75; 95 % CI 0·59, 0·96) than for postmenopausal breast cancer (RR 0·94; 95 % CI 0·87, 1·01). Dose–response analysis revealed that each 300 mg/d increase in Ca intake was associated with 2 % (RR 0·98; 95 % CI 0·96, 0·99), 8 % (RR 0·92; 95 % CI 0·87, 0·98) and 2 % (RR 0·98; 95 % CI 0·97, 0·99) reduction in the risk of total, premenopausal and postmenopausal breast cancer, respectively. Our findings suggest an inverse dose–response association between Ca intake and risk of breast cancer.