Association of white matter hyperintensity burden and infarct volume in the anterior choroidal artery territory with early neurological progression: a dual-center retrospective study

ObjectiveTo investigate the associations of white matter hyperintensity (WMH) burden and infarct volume with early neurological progression in anterior choroidal artery (AChA) territory infarction, and to identify potential imaging-based predictive thresholds.MethodsThis retrospective cohort study consecutively enrolled AChA infarct patients admitted to two comprehensive stroke centers between September 2018 and September 2024. WMH burden and infarct volume were assessed using the Fazekas visual rating scale and an automated volumetric quantification method based on lesion prediction algorithm, respectively. The primary outcome was early neurological progression. Multivariate logistic regression models with stepwise adjustment for confounders were used to evaluate the associations of WMH burden and infarct volume with early progression. Restricted cubic spline regression was performed to explore non-linear relationships and to determine thresholds. Continuous variables were standardized, and piecewise regression analysis was conducted based on the identified thresholds. Subgroup analyses with interaction tests were performed to assess the consistency of these associations across different populations.ResultsA total of 216 patients were included, of whom 82 (38.0%) experienced early neurological progression. After adjustment for potential confounders, WMH burden showed a significant non-linear association with progression risk. For WMH volumes <66.1 mL, each standard deviation increase was associated with a 74% higher risk of progression (standardized OR: 1.74, 95% CI: 1.29–2.40, p < 0.001). Compared with the lowest quartile, patients in the highest WMH quartile showed significantly increased risk (adjusted OR: 5.32, 95% CI: 1.48–13.88, p = 0.009). This association was confirmed by Fazekas scale analysis, with grade 3 patients showing substantially higher risk than grade 0 (adjusted OR: 6.22, 95% CI: 1.74–25.42, p = 0.007). Infarct volume demonstrated a similar non-linear pattern; for volumes <1.1 mL, each standard deviation increase was associated with 59% higher progression risk (standardized OR: 1.59, 95% CI: 1.04–2.47, p = 0.036). Quartile analysis revealed the highest risk in the third quartile compared to the lowest (adjusted OR: 5.63, 95% CI: 2.06–15.40, p < 0.001).ConclusionThis study revealed non-linear associations of WMH and infarct volume with early progression in AChA infarct patients

Identification of FAM3D as a novel endogenous chemotaxis agonist for the FPRs (formyl peptide receptors)

The family with sequence similarity 3 (FAM3) gene family is a cytokine-like gene family with four members FAM3A, FAM3B, FAM3C, and FAM3D. In this study, we found that FAM3D strongly chemoattracted human peripheral blood neutrophils and monocytes. To identify FAM3D receptor, we used chemotaxis, receptor internalization, calcium flux and radioligand-binding assays in FAM3D-stimulated HEK293 cells that transiently expressed FPR1 or FPR2 to show that FAM3D was a high affinity ligand of formyl peptide receptors (FPR1 and FPR2), both of which were highly expressed on the surface of neutrophils and monocytes/macrophages. After being injected into the mouse peritoneal cavity, FAM3D chemoattracted CD11b+Ly6G+ neutrophils in a short time. In response to FAM3D stimulation, p-ERK and p-p38 were up-regulated in the mouse neutrophils, which could be inhibited by an inhibitor of FPR1 or FPR2. FAM3D was reported to be constitutively expressed in the gastrointestinal tract. We found that FAM3D expression increased significantly in dextran sulfate sodium-induced colitis. Taken together, we propose that FAM3D plays a role in gastrointestinal homeostasis and inflammation through its receptors FPR1 and FPR2.</jats:p

Generation and Role of Oscillatory Contractions in Mouse Airway Smooth Muscle

Background/Aims: Tetraethylammonium chloride (TEA) induces oscillatory contractions in mouse airway smooth muscle (ASM); however, the generation and maintenance of oscillatory contractions and their role in ASM are unclear. Methods: In this study, oscillations of ASM contraction and intracellular Ca2+ were measured using force measuring and Ca2+ imaging technique, respectively. TEA, nifedipine, niflumic acid, acetylcholine chloride, lithium chloride, KB-R7943, ouabain, 2-Aminoethoxydiphenyl borate, thapsigargin, tetrodotoxin, and ryanodine were used to assess the mechanism of oscillatory contractions. Results: TEA induced depolarization, resulting in activation of L-type voltage-dependent Ca2+ channels (LVDCCs) and voltage-dependent Na+ (VNa) channels. The former mediated Ca2+ influx to trigger a contraction and the latter mediated Na+ entry to enhance the contraction via activating LVDCCs. Meanwhile, increased Ca2+-activated Cl- channels, inducing depolarization that resulted in contraction through LVDCCs. In addition, the contraction was enhanced by intracellular Ca2+ release from Ca2+ stores mediated by inositol (1,4,5)-trisphosphate receptors (IP3Rs). These pathways together produce the contractile phase of the oscillatory contractions. Furthermore, the increased Ca2+ activated the Na+-Ca2+ exchanger (NCX), which transferred Ca2+ out of and Na+ into the cells. The former induced relaxation and the latter activated Na+/K+-ATPase that induced hypopolarization to inactivate LVDCCs causing further relaxation. This can also explain the relaxant phase of the oscillatory contractions. Moreover, the depolarization induced by VNa channels and NCX might be greater than the hypopolarization caused by Na+/K+-ATPase alone, inducing LVDCC activation and resulting in further contraction. Conclusions: These data indicate that the TEA-induced oscillatory contractions were cooperatively produced by LVDCCs, VNa channels, Ca2+-activated Cl- channels, NCX, Na+/K+ ATPase, IP3Rs-mediated Ca2+ release, and extracellular Ca2+

Semen cassiae Extract Inhibits Contraction of Airway Smooth Muscle

β2-adrenoceptor agonists are commonly used as bronchodilators to treat obstructive lung diseases such as asthma and chronic obstructive pulmonary disease (COPD), however, they induce severe side effects. Therefore, developing new bronchodilators is essential. Herbal plants were extracted and the extracts’ effect on airway smooth muscle (ASM) precontraction was assessed. The ethyl alcohol extract of semen cassiae (EESC) was extracted from Semen cassia. The effects of EESC on the ACh- and 80 mM K+-induced sustained precontraction in mouse and human ASM were evaluated. Ca2+ permeant ion channel currents and intracellular Ca2+ concentration were measured. HPLC analysis was employed to determine which compound was responsible for the EESC-induced relaxation. The EESC reversibly inhibited the ACh- and 80 mM K+-induced precontraction. The sustained precontraction depends on Ca2+ influx, and it was mediated by voltage-dependent L-type Ca2+ channels (LVDCCs), store-operated channels (SOCs), TRPC3/STIM/Orai channels. These channels were inhibited by aurantio-obtusin, one component of EESC. When aurantio-obtusin removed, EESC’s action disappeared. In addition, aurantio-obtusin inhibited the precontraction of mouse and human ASM and intracellular Ca2+ increases. These results indicate that Semen cassia-contained aurantio-obtusin inhibits sustained precontraction of ASM via inhibiting Ca2+-permeant ion channels, thereby, which could be used to develop new bronchodilators

JEco-data for biocrust-vascular plant coexistence

Data was collected from a five year field experiment simulating increased precipitation and nitrogen deposition in a desert shrubland. It contains biocrust cover, vascular plant productivity, and ground-level light.<br

pFedLN: Personalized Federated Learning Framework With Layer-Wised and Neighbor-Based Aggregation for QoS Prediction

In the era of a more advanced and intelligent Internet, the highly sophisticated service-oriented internet provides users with a diverse array of similar services. Accurate Quality of Service (QoS) prediction plays a pivotal role in helping users choose the optimal service from a multitude of available options. Traditional federated learning models offer a secure method for multiple clients to collaborate on QoS predictions. However, these models still employ a uniform approach that overlooks the unique requirements of individual clients. In order to meet the different needs of a wide range of customers for models, we propose an innovative personalized federated learning framework with layer-wised and neighbor-based aggregation for QoS prediction (pFedLN). In the proposed framework, we consider the privacy and functional disparities among layers in neural network models and employ diverse aggregation strategies for layers serving different functions. In addition, the similarity between neighbors will be taken into account during the aggregation process. This results in the creation of personalized models for each client that better align with their specific requirements. Sufficient experiments are conducted on a real-world dataset and the results indicate that our approach have a clear advantage in improving the effectiveness of personalization compared to existing approaches

Detecting Online Counterfeit-goods Seller using Connection Discovery

With the advancement of social media and mobile technology, any smartphone user can easily become a seller on social media and e-commerce platforms, such as Instagram and Carousell in Hong Kong or Taobao in China. A seller shows images of their products and annotates their images with suitable tags that can be searched easily by others. Those images could be taken by the seller, or the seller could use images shared by other sellers. Among sellers, some sell counterfeit goods, and these sellers may use disguising tags and language, which make detecting them a difficult task. This article proposes a framework to detect counterfeit sellers by using deep learning to discover connections among sellers from their shared images. Based on 473K shared images from Taobao, Instagram, and Carousell, it is proven that the proposed framework can detect counterfeit sellers. The framework is 30% better than approaches using object recognition in detecting counterfeit sellers. To the best of our knowledge, this is the first work to detect online counterfeit sellers from their shared images.</jats:p

Social Network Analytic-Based Online Counterfeit Seller Detection using User Shared Images

Selling counterfeit online has become a serious problem, especially with the advancement of social media and mobile technology. Instead of investigating the products directly, one can only check the images, tags annotated by the sellers on the images, or the price to decide if a seller sells counterfeits. One of the ways to detect counterfeit sellers is to investigate their social graphs, in which counterfeit sellers show different behaviour in network measurements, such as those in centrality and EgoNet. However, social graphs are not easily accessible. They may be kept private by the operators, or there are no connections at all. This article proposes a framework to detect counterfeit sellers using their connection graphs discovered from their shared images. Based on 153 K shared images from Taobao, it is proven that counterfeit sellers have different network behaviours. It is observed that the network measurements follow Beta function well. Those distributions are formulated to detect counterfeit sellers by the proposed framework, which is 60% better than approaches using classification.</jats:p