TC-14, a cathelicidin-derived antimicrobial peptide with broad-spectrum antibacterial activity and high safety profile.

Cathelicidins, a major class of antimicrobial peptides (AMPs), hold considerable potential for antimicrobial drug development. In the present study, we identified a novel cathelicidin AMP (TC-33) derived from the Chinese tree shrew. Despite TC-33 demonstrating weak antimicrobial activity, the novel peptide TC-14, developed based on its active region, exhibited a 432-fold increase in antimicrobial activity over the parent peptide. Structural analysis revealed that TC-14 adopted an amphipathic α-helical conformation. The bactericidal mechanism of TC-14 involved targeting and disrupting the bacterial membrane, leading to rapid membrane permeabilization and rupture. Furthermore, TC-14 exhibited a high-safety profile, as evidenced by the absence of cytotoxic and hemolytic activities, as well as high biocompatibility and safety in vivo. Of note, its potent antimicrobial activity provided significant protection in a murine model of skin infection. Overall, this study presents TC-14 as a promising drug candidate for antimicrobial drug development.

Water Impact Dynamics and Mechanism Analysis of Polypropylene and Polypropylene/poly(ethylene-co-octene) Replica Surfaces with Nanowires under Low Temperature Conditions.

In this work, polypropylene (PP) and PP/poly(ethylene-co-octene) (PP/POE) blend replica surfaces with densely arranged nanowires are fabricated using a molding process. Morphology analysis shows that the nanowires on these replica surfaces have sharp tips and high aspect ratios. The droplet impact behaviors on the surfaces of the PP/POE blend replicas and PP replicas are investigated before and after freezing at -20 °C for 4 h. The height of the nanowires on the PP/POE blend replica surfaces is higher than that on the PP surface before and after freezing. The static wettability and droplet impact tests on the surfaces of PP/POE blend replicas and PP replica show that adding POE into the PP matrix can significantly increase the toughness of the nanowires on the PP/POE blend replica surfaces during the droplet impact at low temperatures. These investigations are favorable to broaden the practical applications of superhydrophobic surfaces in some severe environments.

Leveraging Transfer Superposition Theory for StableState Visual Evoked Potential Cross-Subject Frequency Recognition.

In steady-state visual evoked potential (SSVEP)based brain-computer interfaces (BCIs), various spatial filtering methods based on individual calibration data have been proposed to alleviate the interference of spontaneous activities in SSVEP signals for enhancing the SSVEP detection performance. However, the necessary calibration procedures take time, cause visual fatigue and reduce usability. For the calibration-free scenario, we propose a cross-subject frequency identification method based on transfer superimposed theory for SSVEP frequency decoding. First, a multi-channel signal decomposition model was constructed. Next, we used the cross least squares iterative method to create individual specific transfer spatial filters as well as source subject transfer superposition templates in the source subject. Then, we identified common knowledge among source subjects using a prototype spatial filter to make common transfer spatial filters and common impulse responses. Following, we reconstructed a global transfer superimposition template with SSVEP frequency characteristics. Finally, an ensemble cross-subject transfer learning method was proposed for SSVEP frequency recognition by combining the sourcesubject transfer mode, the global transfer mode, and the sinecosine reference template. Offline tests on two public datasets show that the proposed method significantly outperforms the FBCCA, TTCCA, and CSSFT methods. More importantly, the proposed method can be directly used in online SSVEP recognition without calibration. The proposed algorithm was robust, which is important for a practical BCI.

NIR-II Responsive Fe-Doped Carbon Nanoparticles for Photothermal-Enhanced Chemodynamic Synergistic Oncotherapy.

Phototherapy has demonstrated substantial development because in the second near-infrared (NIR-II) window it has a larger tissue penetration and fewer adverse consequences. In this work, a particular kind of NIR-II responsive Fe-doped carbon nanoparticles (FDCNs) is synthesized using a one-pot hydrothermal method for combined photothermal and chemodynamic therapy. The mesoporous nanostructure of FDCN, which has a size distribution that exceeds 225 nm, allows for effective acidification. The iron ions released from these nanoparticles can catalyze the decomposition of hydrogen peroxide (H2O2) into hydroxyl radical (•OH) for chemodynamic therapy (CDT). In addition to their CDT utility, FDCN can effectively adsorb and transform 1064 nm light into local heat, achieving a photothermal conversion efficacy (PCE) of 36.3%. This dual functionality not only allows for the direct eradication of cancer cells through photothermal therapy (PTT) but also enhances the chemodynamic reaction, creating a synergistic effect that amplifies the therapeutic outcome. The FDCN has demonstrated remarkable anticancer activity in both cellular and animal tests without incurring major systemic toxicity. This suggests that the compound has great promise for use in clinical cancer therapy.

W-Shaped π-Extended Double Undecabenzo[7]helicene.

A chiral W-shaped fully π-extended double [7]helicene (ED7H) has been synthesized and fully characterized. It displays fluorescence emission (λem = 636 nm) with a quantum yield (Φf) of 0.10. In comparison to its X-shaped and monomict π-extended [7]helicene analogues, enantiopure W-shaped ED7H exhibited superior chiral optical characteristics, including distinct circular dichroism signals from 400 to 650 nm, a good dissymmetric emission factor |glum| of 4 × 10-3, and a circularly polarized luminescence brightness value BCPL of 42 M-1 cm-1.

Respiratory SARS-CoV-2 Infection Causes Skeletal Muscle Atrophy and Long-Lasting Energy Metabolism Suppression.

Muscle fatigue represents the most prevalent symptom of long-term COVID, with elusive pathogenic mechanisms. We performed a longitudinal study to characterize histopathological and transcriptional changes in skeletal muscle in a hamster model of respiratory SARS-CoV-2 infection and compared them with influenza A virus (IAV) and mock infections. Histopathological and bulk RNA sequencing analyses of leg muscles derived from infected animals at days 3, 30, and 60 post-infection showed no direct viral invasion but myofiber atrophy in the SARS-CoV-2 group, which was accompanied by persistent downregulation of the genes related to myofibers, ribosomal proteins, fatty acid ß-oxidation, tricarboxylic acid cycle, and mitochondrial oxidative phosphorylation complexes. While both SARS-CoV-2 and IAV infections induced acute and transient type I and II interferon responses in muscle, only the SARS-CoV-2 infection upregulated TNF-α/NF-κB but not IL-6 signaling in muscle. Treatment of C2C12 myotubes, a skeletal muscle cell line, with combined IFN-γ and TNF-α but not with IFN-γ or TNF-α alone markedly impaired mitochondrial function. We conclude that a respiratory SARS-CoV-2 infection can cause myofiber atrophy and persistent energy metabolism suppression without direct viral invasion. The effects may be induced by the combined systemic interferon and TNF-α responses at the acute phase and may contribute to post-COVID-19 persistent muscle fatigue.

Anisomyopia and orthokeratology for myopia control - Axial elongation and relative peripheral refraction.

PURPOSE: To investigate axial elongation (AE) and changes in relative peripheral refraction (RPR) in anisomyopic children undergoing orthokeratology (ortho-k). METHODS: Bilateral anisomyopic children, 7-12 years of age, were treated with ortho-k. Axial length (AL) and RPR, from 30° nasal (N30°) to 30° temporal (T30°), were measured at baseline and every 6 months over the study period. AE, changes in RPR and changes in the interocular AL difference were determined over time. RESULTS: Twenty-six of the 33 subjects completed the 2-year study. The AE of the higher myopic (HM) eyes (at least 1.50 D more myopia than the other eye) (0.26 ± 0.29 mm) was significantly smaller than for the less myopic (LM) eyes (0.50 ± 0.27 mm; p = 0.003), leading to a reduction in the interocular difference in AL (p = 0.001). Baseline RPR measurements in the HM eyes were relatively more hyperopic at T30°, N20° and N30° (p ≤ 0.02) and greater myopic shifts were observed at T20° (p < 0.001), T30° (p < 0.001), N20° (p = 0.02) and N30° (p = 0.01) after lens wear. After 2 years of ortho-k lens wear, temporal-nasal asymmetry increased significantly, being more myopic at the temporal locations in both eyes (p < 0.001), while AE was associated with the change in RPR at N20° (ß = 0.134, p = 0.01). The interocular difference in AE was also positively associated with the interocular difference in RPR change at N30° (ß = 0.111, p = 0.02). CONCLUSIONS: Ortho-k slowed AE in bilateral anisomyopia, with slower growth in the HM eyes leading to a reduction in interocular AL differences. After ortho-k, RPR changed from hyperopia to myopia, with greater changes induced in the HM eyes, and slower AE was associated with a more myopic shift in RPR, especially in the nasal field of both eyes.

Cation Configuration and Structural Degradation of Layered Transition Metal Oxides in Sodium-Ion Batteries.

Given the pressing depletion of lithium resources, sodium-ion batteries (SIBs) stand out as a cost-effective alternative for energy storage solutions in the near future. Layered transition metal oxides (LTMOs) emerge as the leading cathode materials for SIBs due to their superior specific capacities and abundant raw materials. Nonetheless, achieving long-term stability in LTMOs for SIBs remains a challenge due to the inevitable structural degradation during charge-discharge cycles. The complexity and diversity of cation configurations/superstructures within the transition metal layers (TMO2) further complicate the understanding for newcomers. Therefore, it is critical to summarize and discuss the factors leading to structural degradation and the available strategies for enhancing LTMOs' stability. In this review, the cationic configurations of TMO2 layers are introduced from a crystallographic perspective. It then identifies and examines four key factors responsible for structural decay, alongside the impacts of various modification strategies. Finally, more effective and practical research approaches for investigating LTMOs have been proposed. The work aims to enhance the comprehension of the structural deterioration of LTMOs and facilitate a substantial improvement in their cycle life and energy density.

Obesity-enriched gut microbe degrades myo-inositol and promotes lipid absorption.

Numerous studies have reported critical roles for the gut microbiota in obesity. However, the specific microbes that causally contribute to obesity and the underlying mechanisms remain undetermined. Here, we conducted shotgun metagenomic sequencing in a Chinese cohort of 631 obese subjects and 374 normal-weight controls and identified a Megamonas-dominated, enterotype-like cluster enriched in obese subjects. Among this cohort, the presence of Megamonas and polygenic risk exhibited an additive impact on obesity. Megamonas rupellensis possessed genes for myo-inositol degradation, as demonstrated in vitro and in vivo, and the addition of myo-inositol effectively inhibited fatty acid absorption in intestinal organoids. Furthermore, mice colonized with M. rupellensis or E. coli heterologously expressing the myo-inositol-degrading iolG gene exhibited enhanced intestinal lipid absorption, thereby leading to obesity. Altogether, our findings uncover roles for M. rupellensis as a myo-inositol degrader that enhances lipid absorption and obesity, suggesting potential strategies for future obesity management.

BTA2 regulates tiller angle and the shoot gravity response through controlling auxin content and distribution in rice.

Tiller angle is a key agricultural trait that establishes plant architecture, which in turn strongly affects grain yield by influencing planting density in rice. The shoot gravity response plays a crucial role in the regulation of tiller angle in rice, but the underlying molecular mechanism is largely unknown. Here, we report the identification of the BIG TILLER ANGLE2 (BTA2), which regulates tiller angle by controlling the shoot gravity response in rice. Loss-of-function mutation of BTA2 dramatically reduced auxin content and affected auxin distribution in rice shoot base, leading to impaired gravitropism and therefore a big tiller angle. BTA2 interacted with AUXIN RESPONSE FACTOR7 (ARF7) to modulate rice tiller angle through the gravity signaling pathway. The BTA2 protein was highly conserved during evolution. Sequence variation in the BTA2 promoter of indica cultivars harboring a less expressed BTA2 allele caused lower BTA2 expression in shoot base and thus wide tiller angle during rice domestication. Overexpression of BTA2 significantly increased grain yield in the elite rice cultivar Huanghuazhan under appropriate dense planting conditions. Our findings thus uncovered the BTA2-ARF7 module that regulates tiller angle by mediating the shoot gravity response. Our work offers a target for genetic manipulation of plant architecture and valuable information for crop improvement by producing the ideal plant type.

On-site analysis and rapid identification of citrus herbs by miniature mass spectrometry and machine learning.

BACKGROUND: Natural medicines present a considerable analytical challenge due to their diverse botanical origins and complex multi-species composition. This inherent complexity complicates their rapid identification and analysis. Tangerine peel, a product of the Citrus species from the Rutaceae family, is widely used both as a culinary ingredient and in traditional Chinese medicine. It is classified into two primary types in China: Citri Reticulatae Pericarpium (CP) and Citri Reticulatae Pericarpium Viride (QP), differentiated by harvest time. A notable price disparity exists between CP and another variety, Citri reticulatae "Chachi" (GCP), with differences being based on the original variety. METHODS: This study introduces an innovative method using portable miniature mass spectrometry for swift on-site analysis of QP, CP, and GCP, requiring less than a minute per sample. And combined with machine learning to differentiate the three types on site, the method was used to try to distinguish GCP from different storage years. RESULTS: This novel method using portable miniature mass spectrometry for swift on-site analysis of tangerine peels enabled the characterization of 22 compounds in less than one minute per sample. The method simplifies sample processing and integrates machine learning to distinguish between the CP, QP, and GCP varieties. Moreover, a multiple-perceptron neural network model is further employed to specifically differentiate between CP and GCP, addressing the significant price gap between them. CONCLUSIONS: The entire analytical time of the method is about 1 minute, and samples can be analyzed on site, greatly reducing the cost of testing. Besides, this approach is versatile, operates independently of location and environmental conditions, and offers a valuable tool for assessing the quality of natural medicines.

Tea and coffee consumption and risk of acute stroke: The INTERSTROKE Study.

BACKGROUND: Stroke is a leading global cause of death and disability. Daily tea/coffee intake is consumed by > 50% of populations and may represent an important population-level exposure. Therefore, it is first essential that we better understand the associations between the tea/coffee intake and stroke. AIMS: This research aims to generate hypotheses about the global associations between tea and coffee intake and stroke. These insights will identify interventions for stroke prevention that can be further explored using alternative study designs. METHODS: INTERSTROKE is a large international matched case-control study of first stroke from 32 countries. Participants were asked "how many cups do you drink each day?" of coffee, green tea, black tea, and other tea. Multivariable conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between intake and stroke. RESULTS: We included 13,462 cases and 13,488 controls from INTERSTROKE; mean age was 61.7 (13.4) years and 59.6% (n = 16,010) were male. Overall, 19.4% (n = 5239) did not consume tea/coffee, 47.0% (n = 12,666) consumed tea only, 14.9% (n = 4024) consumed coffee alone, and 18.6% (n = 5021) consumed both, with significant regional variations. After multivariable adjustment, there was no association between low/moderate coffee intake and stroke, but high consumption (> 4/day) was associated with higher odds of all stroke (OR = 1.37 (95% CI = 1.06-1.77)) or ischemic stroke (OR = 1.32 (95% CI = 1.00-1.74)). Tea consumption was associated with lower odds of all (OR = 0.81 (95% CI = 0.69-0.94) for highest intake) or ischemic stroke (OR = 0.81 (95% CI = 0.68-0.98) for highest intake). CONCLUSIONS: High coffee consumption was associated with higher odds of all or ischemic stroke; low-moderate coffee had no association with stroke. In contrast, tea consumption was associated with lower odds of stroke. These associations suggest that individuals consider avoiding high coffee consumption (⩾ five cups/day) to impact future stroke risk. DATA ACCESS STATEMENT: The design and rationale of INTERSTROKE was published previously. Individual participant data, or other documents are not available.

An auto-segmented multi-time window dual-scale neural network for brain-computer interfaces based on event-related potentials.

Objective.Event-related potentials (ERPs) are cerebral responses to cognitive processes, also referred to as cognitive potentials. Accurately decoding ERPs can help to advance research on brain-computer interfaces (BCIs). The spatial pattern of ERP varies with time. In recent years, convolutional neural networks (CNNs) have shown promising results in electroencephalography (EEG) classification, specifically for ERP-based BCIs.Approach.This study proposes an auto-segmented multi-time window dual-scale neural network (AWDSNet). The combination of a multi-window design and a lightweight base network gives AWDSNet good performance at an acceptable cost of computing. For each individual, we create a time window set by calculating the correlation of signedR-squared values, which enables us to determine the length and number of windows automatically. The signal data are segmented based on the obtained window sets in sub-plus-global mode. Then, the multi-window data are fed into a dual-scale CNN model, where the sizes of the convolution kernels are determined by the window sizes. The use of dual-scale spatiotemporal convolution focuses on feature details while also having a large enough receptive length, and the grouping parallelism undermines the increase in the number of parameters that come with dual scaling.Main results.We evaluated the performance of AWDSNet on a public dataset and a self-collected dataset. A comparison was made with four popular methods including EEGNet, DeepConvNet, EEG-Inception, and PPNN. The experimental results show that AWDSNet has excellent classification performance with acceptable computational complexity.Significance.These results indicate that AWDSNet has great potential for applications in ERP decoding.

A cross-dataset adaptive domain selection transfer learning framework for motor imagery-based brain-computer interfaces.

Objective. In brain-computer interfaces (BCIs) that utilize motor imagery (MI), minimizing calibration time has become increasingly critical for real-world applications. Recently, transfer learning (TL) has been shown to effectively reduce the calibration time in MI-BCIs. However, variations in data distribution among subjects can significantly influence the performance of TL in MI-BCIs.Approach.We propose a cross-dataset adaptive domain selection transfer learning framework that integrates domain selection, data alignment, and an enhanced common spatial pattern (CSP) algorithm. Our approach uses a huge dataset of 109 subjects as the source domain. We begin by identifying non-BCI illiterate subjects from this huge dataset, then determine the source domain subjects most closely aligned with the target subjects using maximum mean discrepancy. After undergoing Euclidean alignment processing, features are extracted by multiple composite CSP. The final classification is carried out using the support vector machine.Main results.Our findings indicate that the proposed technique outperforms existing methods, achieving classification accuracies of 75.05% and 76.82% in two cross-dataset experiments, respectively.Significance.By reducing the need for extensive training data, yet maintaining high accuracy, our method optimizes the practical implementation of MI-BCIs.

Rapid analysis of bioactive compounds from citrus samples by direct analysis in real-time mass spectrometry combined with chemometrics.

Renowned for their nutritional benefits, citrus fruits are harvested at various stages in China for functional food production. This study introduces an innovative analytical method, DART-MS, enabling direct qualitative analysis of citrus samples without the need for preprocessing. Simultaneously, the combination of chemometrics can be applied to distinguish between three different citrus samples: Citri Reticulatae Pericarpium, Citri Reticulatae Pericarpium Viride, and Citri Reticulatae "Chachi". Notably, given the international regulatory concerns surrounding synephrine, a precise quantitative analysis method for synephrine was developed. The limit of detection (LOD) and the limit of quantification (LOQ) were 39 ng mL-1 and 156 ng mL-1, respectively. The recovery rates obtained varied from 98.46% to 100.71%. Furthermore, the intra-day and inter-day precision demonstrated robust consistency, with values spanning 5.0-6.1% and 5.03-6.08%, respectively, offering quicker results compared to those from HPLC-MS, promising a safer assessment of herbal and food products.

A teosinte-derived allele of ZmSC improves salt tolerance in maize.

Maize, a salt-sensitive crop, frequently suffers severe yield losses due to soil salinization. Enhancing salt tolerance in maize is crucial for maintaining yield stability. To address this, we developed an introgression line (IL76) through introgressive hybridization between maize wild relatives Zea perennis, Tripsacum dactyloides, and inbred Zheng58, utilizing the tri-species hybrid MTP as a genetic bridge. Previously, genetic variation analysis identified a polymorphic marker on Zm00001eb244520 (designated as ZmSC), which encodes a vesicle-sorting protein described as a salt-tolerant protein in the NCBI database. To characterize the identified polymorphic marker, we employed gene cloning and homologous cloning techniques. Gene cloning analysis revealed a non-synonymous mutation at the 1847th base of ZmSCIL76 , where a guanine-to-cytosine substitution resulted in the mutation of serine to threonine at the 119th amino acid sequence (using ZmSCZ58 as the reference sequence). Moreover, homologous cloning demonstrated that the variation site derived from Z. perennis. Functional analyses showed that transgenic Arabidopsis lines overexpressing ZmSCZ58 exhibited significant reductions in leaf number, root length, and pod number, alongside suppression of the expression of genes in the SOS and CDPK pathways associated with Ca2+ signaling. Similarly, fission yeast strains expressing ZmSCZ58 displayed inhibited growth. In contrast, the ZmSCIL76 allele from Z. perennis alleviated these negative effects in both Arabidopsis and yeast, with the lines overexpressing ZmSCIL76 exhibiting significantly higher abscisic acid (ABA) content compared to those overexpressing ZmSCZ58 . Our findings suggest that ZmSC negatively regulates salt tolerance in maize by suppressing downstream gene expression associated with Ca2+ signaling in the CDPK and SOS pathways. The ZmSCIL76 allele from Z. perennis, however, can mitigate this negative regulatory effect. These results provide valuable insights and genetic resources for future maize salt tolerance breeding programs.

Integrating intratumoral and peritumoral radiomics with deep transfer learning for DCE-MRI breast lesion differentiation: A multicenter study comparing performance with radiologists.

PURPOSE: To conduct the fusion of radiomics and deep transfer learning features from the intratumoral and peritumoral areas in breast DCE-MRI images to differentiate between benign and malignant breast tumors, and to compare the diagnostic accuracy of this fusion model against the assessments made by experienced radiologists. MATERIALS AND METHODS: This multi-center study conducted a retrospective analysis of DCE-MRI images from 330 women diagnosed with breast cancer, with 138 cases categorized as benign and 192 as malignant. The training and internal testing sets comprised 270 patients from center 1, while the external testing cohort consisted of 60 patients from center 2. A fusion feature set consisting of radiomics features and deep transfer learning features was constructed from both intratumoral (ITR) and peritumoral (PTR) areas. The Least absolute shrinkage and selection operator (LASSO) based support vector machine was chosen as the classifier by comparing its performance with five other machine learning models. The diagnostic performance and clinical usefulness of fusion model were verified and assessed through the area under the receiver operating characteristics (ROC) and decision curve analysis. Additionally, the performance of the fusion model was compared with the diagnostic assessments of two experienced radiologists to evaluate its relative accuracy. The study strictly adhered to CLEAR and METRICS guidelines for standardization to ensure rigorous and reproducible methods. RESULTS: The findings show that the fusion model, utilizing radiomics and deep transfer learning features from the ITR and PTR, exhibited exceptional performance in classifying breast tumors, achieving AUCs of 0.950 in the internal testing set and 0.921 in the external testing set. This performance significantly surpasses that of models relying on singular regional radiomics or deep transfer learning features alone. Moreover, the fusion model demonstrated superior diagnostic accuracy compared to the evaluations conducted by two experienced radiologists, thereby highlighting its potential to support and enhance clinical decision-making in the differentiation of benign and malignant breast tumors. CONCLUSION: The fusion model, combining multi-regional radiomics with deep transfer learning features, not only accurately differentiates between benign and malignant breast tumors but also outperforms the diagnostic assessments made by experienced radiologists. This underscores the model's potential as a valuable tool for improving the accuracy and reliability of breast tumor diagnosis.

Replicating CD Nanogrooves onto PDMS to Guide Nanowire Growth for Monolithic Flexible Photodetectors with High Bending-Stable UV-vis-NIR Photoresponse.

Guided nanowires grown on polymer surfaces facilitate their seamless integration as flexible devices without post-growth processing steps. However, this is challenging due to the inability of polymer films to provide the required lattice-matching effect. In this work, this challenge is addressed by replicating highly aligned nanogrooves from a compact disc (CD) onto a casted flexible polydimethylsiloxane (PDMS) surface. Leveraging the replicated nanogrooves, copper hexadecafluorophthalocyanine (F16CuPc) and various metal phthalocyanines are guided into large-area, self-aligned nanowires. Subsequently, by employing specifically designed shadow masks during electrode deposition, these nanowires are seamlessly integrated as either a monolithic flexible photodetector with a large sensing area or on-chip flexible photodetector arrays. The resulting flexible photodetectors exhibit millisecond and long-term stable response to UV-vis-NIR light. Notably, they demonstrate exceptional bending stability, retaining stable and sensitive photoresponse even at a curvature radius as low as 0.5 cm and after enduring 1000 bending cycles. Furthermore, the photodetector array showcases consistent sensitivity and response speed across the entire array. This work not only proves the viability of guided nanowire growth on flexible polymer surfaces by replicating CD nanogrooves but also underscores the potential for large-scale monolithic integration of guided nanowires as flexible devices.

Blood pressure variability in acute stroke: Risk factors and association with functional outcomes at 1 month.

BACKGROUND AND PURPOSE: Blood pressure variability, in acute stroke, may be an important modifiable determinant of functional outcome after stroke. In a large international cohort of participants with acute stroke, it was sought to determine the association of blood pressure variability (in the early period of admission) and functional outcomes, and to explore risk factors for increased blood pressure variability. PATIENTS AND METHODS: INTERSTROKE is an international case-control study of risk factors for first acute stroke. Blood pressure was recorded at the time of admission, the morning after admission and the time of interview in cases (median time from admission 36.7 h). Multivariable ordinal regression analysis was employed to determine the association of blood pressure variability (standard deviation [SD] and coefficient of variance) with modified Rankin score at 1-month follow-up, and logistic regression was used to identify risk factors for blood pressure variability. RESULTS: Amongst 13,206 participants, the mean age was 62.19 ± 13.58 years. When measured by SD, both systolic blood pressure variability (odds ratio 1.13; 95% confidence interval 1.03-1.24 for SD ≥20 mmHg) and diastolic blood pressure variability (odds ratio 1.15; 95% confidence interval 1.04-1.26 for SD ≥10 mmHg) were associated with a significant increase in the odds of poor functional outcome. The highest coefficient of variance category was not associated with a significant increase in risk of higher modified Rankin score at 1 month. Increasing age, female sex, high body mass index, history of hypertension, alcohol use, and high urinary potassium and low urinary sodium excretion were associated with increased blood pressure variability. CONCLUSION: Increased blood pressure variability in acute stroke, measured by SD, is associated with an increased risk of poor functional outcome at 1 month. Potentially modifiable risk factors for increased blood pressure variability include low urinary sodium excretion.

Markers of periodontal disease and risk of stroke: INTERSTROKE case-control study.

BACKGROUND: Periodontal disease may be an important modifiable risk factor for stroke. AIMS: To determine the contribution of markers of periodontal disease to stroke risk globally, within subpopulations, and by stroke subtypes. METHODS: INTERSTROKE is the largest international case-control study of risk factors for first acute stroke. All participants were asked a standardised set of questions about the presence or absence of painful teeth, painful gums or lost teeth, as markers of periodontal disease, within the previous year. The total number of reported variables was calculated per participant. Multivariable conditional logistic regression examined the association of these variables with acute stroke. RESULTS: In 26901 participants, across 32 countries, there was a significant multivariable association between lost teeth and stroke (OR 1.11, 95 % CI 1.01 - 1.22), but not painful teeth (OR 1.00, 95 % CI 0.91-1.10) or painful gums (OR 1.01, 95 % CI 0.89 - 1.14). When these symptoms were considered together there was a graded increased odds of stroke, with the largest magnitude of association seen if a patient reported all three of painful teeth, painful gums and lost teeth (OR 1.34, 95 % CI 1.00 - 1.79). CONCLUSIONS: Our findings suggest that features of severe periodontal disease are a risk factor for acute stroke. Periodontal disease should be considered as a potentially modifiable risk factor for stroke.