Kaempferol attenuates particle-induced osteogenic impairment by regulating ER stress via the IRE1α-XBP1s pathway.

Periprosthetic osteolysis and subsequent aseptic loosening are the primary causes of failure following total joint arthroplasty. Wear particle-induced osteogenic impairment is recognized as an important contributing factor in the development of osteolysis, with endoplasmic reticulum (ER) stress emerging as a pivotal underlying mechanism. Hence, searching for potential therapeutic targets and agents capable of modulating ER stress in osteoblasts is crucial for preventing aseptic loosening. Kaempferol (KAE), a natural flavonol compound, has shown promising osteoprotective effects and anti-ER stress properties in diverse diseases. However, the influence of KAE on ER stress-mediated osteogenic impairment induced by wear particles remains unclear. In this study, we observed that KAE effectively relieved TiAl6V4 particles-induced osteolysis by improving osteogenesis in a mouse calvarial model. Furthermore, we demonstrated that KAE could attenuate ER stress-mediated apoptosis in osteoblasts exposed to TiAl6V4 particles, both in vitro and in vivo. Mechanistically, our results revealed that KAE mitigated ER stress-mediated apoptosis by upregulating the IRE1α-XBP1s pathway while concurrently partially inhibiting the IRE1α-regulated RIDD and JNK activation. Collectively, our findings suggest that KAE is a prospective therapeutic agent for treating wear particle-induced osteolysis and highlight the IRE1α-XBP1s pathway as a potential therapeutic target for preventing aseptic loosening.

A maximum kernel-based association test to detect the pleiotropic genetic effects on multiple phenotypes.

MOTIVATION: Testing the association between multiple phenotypes with a set of genetic variants simultaneously, rather than analyzing one trait at a time, is receiving increasing attention for its high statistical power and easy explanation on pleiotropic effects. The kernel-based association test (KAT), being free of data dimensions and structures, has proven to be a good alternative method for genetic association analysis with multiple phenotypes. However, KAT suffers from substantial power loss when multiple phenotypes have moderate to strong correlations. To handle this issue, we propose a maximum KAT (MaxKAT) and suggest using the generalized extreme value distribution to calculate its statistical significance under the null hypothesis. RESULTS: We show that MaxKAT reduces computational intensity greatly while maintaining high accuracy. Extensive simulations demonstrate that MaxKAT can properly control type I error rates and obtain remarkably higher power than KAT under most of the considered scenarios. Application to a porcine dataset used in biomedical experiments of human disease further illustrates its practical utility. AVAILABILITY AND IMPLEMENTATION: The R package MaxKAT that implements the proposed method is available on Github https://github.com/WangJJ-xrk/MaxKAT.

The Study of SRSF1 Regulates Abnormal Alternative Splicing of BCL2L11 and the Role in Refractory Acute Myeloid Leukemia.

INTRODUCTION: Abnormalities in splicing factors, such as mutations or deregulated expression, can lead to aberrant splicing of target genes, potentially contributing to the pathogenesis of acute myeloid leukemia (AML). Despite this, the precise mechanism underlying the abnormal alternative splicing (AS) induced by SRSF1, a splicing factor associated with poor AML prognosis, remains elusive. METHODS: Using strict splicing criteria, we globally screened for AS events in NPMc-positive and NPMc-negative AML samples from TCGA. An AS network associated with AML prognosis was then established. Functional assays, including CCK-8, flow cytometry, and Western blot, were conducted on K562 and THP-1 cells overexpressing SRSF1. Cell viability following 72-h Omipalisib treatment was also assessed. To explore the mechanism of SRSF1-induced AS, we created a BCL2L11 miniGene with a site-specific mutation at its branch point. The AS patterns of both wild-type and mutant miniGenes were analyzed following SRSF1 overexpression in HEK-293T, along with the subcellular localization of different spliceosomes. RESULTS: SRSF1 was significantly associated with AML prognosis. Notably, its expression was markedly upregulated in refractory AML patients compared to those with a favorable chemotherapy response. Overexpression of SRSF1 promoted THP-1 cell proliferation, suppressed apoptosis, and reduced sensitivity to Omipalisib. Mechanistically, SRSF1 recognized an aberrant branch point within the BCL2L11 intron, promoting the inclusion of a cryptic exon 3, which in turn led to apoptosis arrest. CONCLUSION: Overexpression of SRSF1 and the resulting abnormal splicing of BCL2L11 are associated with drug resistance and poor prognosis in AML.

Change point detection for high dimensional data via kernel measure with application to human aging brain data.

Identifying the existence and locations of change points has been a broadly encountered task in many statistical application areas. The existing change point detection methods may produce unsatisfactory results for high-dimensional data since certain distributional assumptions are made on data, which are hard to verify in practice. Moreover, some parameters (such as the number of change points) need to be estimated beforehand for some methods, making their powers sensitive to these values. Here, we propose a kernel-based U $$ U $$ -statistic to identify change points (KUCP) for high dimensional data, which is free of distributional assumptions and sup-parameter estimations. Specifically, we employ a kernel function to describe similarities among the subjects and construct a U $$ U $$ -statistic to test the existence of change point for a given location. The asymptotic properties of the U $$ U $$ -statistic are deduced. We also develop a procedure to locate the change points sequentially via a dichotomy algorithm. Extensive simulations demonstrate that KUCP has higher sensitivity in identifying existence of change points and higher accuracy in locating these change points than its counterparts. We further illustrate its practical utility by analyzing a gene expression data of human brain to detect the time point when gene expression profiles begin to change, which has been reported to be closely related with aging brain.

A retrospective cohort study of obstetric complications and birth outcomes in women with polycystic ovarian syndrome.

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women and a high risk factor for adverse pregnancy complications. Therefore, we aimed to analyse the relationship between PCOS and pregnancy complications in a large sample from China. Additionally, since obesity and assisted reproductive technology (ART) are common in women with PCOS, we also aimed to determine whether both of these factors increased the complication incidence for women with PCOS. A retrospective cohort study that included 1357 pregnant women with PCOS and 6940 without PCOS was performed. Our results indicated women with PCOS had higher incidence of gestational diabetes mellitus (GDM), hypertension, postpartum haemorrhage, preterm birth, macrosomia and cervical incompetence. Additionally, obesity was associated with an increased incidence of hypertension and GDM in women with PCOS generally. ART did not result in an increase in the obstetric complication rate in women with PCOS. In conclusion, PCOS appeared to result in an increased risk of adverse pregnancy complications. Obesity may further increase the risks of hypertension and GDM among women with PCOS. However, ART did not increase the risk of pregnancy complications, which suggests that ART is a relatively safe and effective method to address infertility problems in women with PCOS.IMPACT STATEMENTWhat is already known on this subject? There are several studies evaluating the associations of PCOS with the risk of pregnancy complications. However, reports about the risk of pregnancy complications between PCOS women with and without obesity or ART are limited.What do the results of this study add? PCOS appeared to increase the risk of adverse pregnancy complications, including GDM, pregnancy-induced hypertension, postpartum haemorrhage, preterm birth, macrosomia and cervical incompetence. Obesity further increased the risks of hypertension and GDM in women with PCOS, but it did not increase the incidence of macrosomia and postpartum haemorrhage. Additionally, ART did not increase the risk of adverse pregnancy complications among women with PCOS, except for postpartum haemorrhage.What are the implications of these findings for clinical practice and/or further research? This study contributes to the literature because it showed that PCOS independently increased the risk of adverse pregnancy complications in a large sample of patients. Second, obesity is a high risk factor for adverse complications in pregnant women with PCOS. Third, ART is a relatively safe and effective method for addressing infertility problems for women with PCOS.

Group analysis of distance matrices.

Distance-based regression model has become a powerful approach to identifying phenotypic associations in many fields. It is found to be particularly useful for high-dimensional biological and genetic data with proper distance or similarity measures being available. The pseudo F statistic used in this model accumulates information and is effective when the signals, that is the variations represented by the eigenvalues of the similarity matrix, scatter evenly along the eigenvectors of the similarity matrix. However, it might lose power for the uneven signals. To deal with this issue, we propose a group analysis on the variations of signals along the eigenvalues of the similarity matrix and take the maximum among them. The new procedure can automatically choose an optimal grouping point on some given thresholds and thus can improve the power evidence. Extensive computer simulations and applications to a prostate cancer data and an aging human brain data illustrate the effectiveness of the proposed method.

A Novel Feature Extraction Method for Power Transformer Vibration Signal Based on CEEMDAN and Multi-Scale Dispersion Entropy.

Effective diagnosis of vibration fault is of practical significance to ensure the safe and stable operation of power transformers. Aiming at the traditional problems of transformer vibration fault diagnosis, a novel feature extraction method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and multi-scale dispersion entropy (MDE) was proposed. In this paper, CEEMDAN method is used to decompose the original transformer vibration signal. Additionally, then MDE is used to capture multi-scale fault features in the decomposed intrinsic mode functions (IMFs). Next, the principal component analysis (PCA) method is employed to reduce the feature dimension and extract the effective information in vibration signals. Finally, the simplified features are sent into density peak clustering (DPC) to get the fault diagnosis results. The experimental data analysis shows that CEEMDAN-MDE can effectively extract the information of the original vibration signals and DPC can accurately diagnose the types of transformer faults. By comparing different algorithms, the practicability and superiority of this proposed method are verified.

A powerful test for ordinal trait genetic association analysis.

Response selective sampling design is commonly adopted in genetic epidemiologic study because it can substantially reduce time cost and increase power of identifying deleterious genetic variants predispose to human complex disease comparing with prospective design. The proportional odds model (POM) can be used to fit data obtained by this design. Unlike the logistic regression model, the estimated genetic effect based on POM by taking data as being enrolled prospectively is inconsistent. So the power of resulted Wald test is not satisfactory. The modified POM is suitable to fit this type of data, however, the corresponding Wald test is not optimal when the genetic effect is small. Here, we propose a new association test to handle this issue. Simulation studies show that the proposed test can control the type I error rate correctly and is more powerful than two existing methods. Finally, we applied three tests to Anticyclic Citrullinated Protein Antibody data from Genetic Workshop 16.

Comprehensive Identification of the Human Secretome as Potential Indicators in Treatment Outcome of HPV-Positive and -Negative Cervical Cancer Patients.

BACKGROUND: The aim of this work was to explore the novel and promising biomarkers for the diagnosis and prognosis of cervical cancer patients. METHODS: The secretome of primary cervical tissues was extracted and then determined by the LC-MS/MS assay. The level of screened targets was confirmed using the RT-PCR and ELISA in cervical cancer tissue samples. The median expression level of certain targets was used as a cutoff value to divide the patients into 2 groups, and then the patients were followed up. The predictive abilities of the targets on the prognosis were further studied. RESULTS: LC-MS/MS, together with bioinformatic analysis, demonstrated that totally 95 targets were dysregulated in cervical cancer. Among them, ECM2, KLK6, and MASP1 were increased in cervical cancer in a stage-dependent manner, whereas FGA was negatively associated with the stage of cervical cancers. Overall survival (OS) and disease-free survival (DFS) rates were significantly decreased in the KLK6 high group, whereas little difference was found between the high and low groups of other 3 cases. Univariate analysis of the 5-year OS and DFS revealed a significantly worse outcome for patients with KLK6 high tumors. In multivariate analysis, KLK6 remained a highly significant prognostic marker for OS and DFS. Combined survival analysis of KLK6 expression and the HPV infection revealed that KLK6highHPV(-) predicted the most poor OS rate and the KLK6lowHPV(+) group showed the best prognosis. CONCLUSION: Through the secretome analysis, we identified a series of secreted proteins differentially expressed in the clinical cancer, among which KLK6 has the potential to become a promising biomarker for the diagnosis and prognosis of cervical cancer patients.

[Diagnose and treatment of post-cesarean section scar diverticulum by hysteroscopy combined ultrasonography and laparoscopy].

OBJECTIVE: To investigate the application of hysteroscopy combined ultrasonography and laparoscopy in the diagnose and treatment of post-cesarean section scar diverticulum (PCSD). METHODS: From March 2011 to February 2013, 27 patients with PCSD were diagnosed and treated in Beijing Obstetrics and Gynecology Hospital. All patients were diagnosed by hysteroscopy and ultrasonography. Treatment protocols were decided by the thickness of the diverticulum. The clinical data of all patients were analysed fully. RESULTS: (1) All patients were diagnosed by hysteroscopy combined ultrasound, of which only 17 cases were diagnosed by preoperative ultrasound, the coincidence rate was 63% (17/27). (2) The thickness of diverticulum was measured by hysteroscopy combined ultrasound. Thickness of less than 3 mm in 19 cases, were treated by hysteroscopy combined with laparoscopy diverticulectomy repair; no less than 3 mm in 8 cases, were used hysteroscopy diverticulum incision. (3) The effective rate was 7/8 after hysteroscopy, and which was 16/19 after laparoscopy combined with hysteroscopy surgery. There was no difference in the treatment effect (P=0.663). The ineffective rate was 1/8 after hysteroscopy, and which was 3/19 after laparoscopy combined with hysteroscopy surgery. The size of the PCSD was smaller and the thickness of diverticulum was thicker than preoperation in the later one, which has no difference in the former one. CONCLUSIONS: (1) Hysteroscopy combined ultrasound is an accurate method for the diagnose of PCSD. (2) According to the thickness of the diverticulum operation method is choosed, which is beneficial to reduce the trauma, and relieve symptoms. (3) Diverticulum poor positioning and incomplete resection are the main causes of postoperative recurrence of the diverticulum.

CD20-specific adoptive immunotherapy for lymphoma using a chimeric antigen receptor with both CD28 and 4-1BB domains: pilot clinical trial results.

Cellular immune responses have the potential to elicit dramatic and sustained clinical remissions in lymphoma patients. Recent clinical trial data demonstrate that modification of T cells with chimeric antigen receptors (CARs) is a promising strategy. T cells containing CARs with costimulatory domains exhibit improved activity against tumors. We conducted a pilot clinical trial testing a "third-generation" CD20-specific CAR with CD28 and 4-1BB costimulatory domains in patients with relapsed indolent B-cell and mantle cell lymphomas. Four patients were enrolled, and 3 received T-cell infusions after cyclophosphamide lymphodepletion. Treatment was well tolerated, although one patient developed transient infusional symptoms. Two patients without evaluable disease remained progression-free for 12 and 24 months. The third patient had an objective partial remission and relapsed at 12 months after infusions. Modified T cells were detected by quantitative PCR at tumor sites and up to 1 year in peripheral blood, albeit at low levels. No evidence of host immune responses against infused cells was detected. In conclusion, adoptive immunotherapy with CD20-specific T cells was well tolerated and was associated with antitumor activity. We will pursue alternative gene transfer technologies and culture conditions in future studies to improve CAR expression and cell production efficiency.

Screening properties of trend tests in genetic association studies.

In genome-wide association study, extracting disease-associated genetic variants among millions of single nucleotide polymorphisms is of great importance. When the response is a binary variable, the Cochran-Armitage trend tests and associated MAX test are among the most widely used methods for association analysis. However, the theoretical guarantees for applying these methods to variable screening have not been built. To fill this gap, we propose screening procedures based on adjusted versions of these methods and prove their sure screening properties and ranking consistency properties. Extensive simulations are conducted to compare the performances of different screening procedures and demonstrate the robustness and efficiency of MAX test-based screening procedure. A case study on a dataset of type 1 diabetes further verifies their effectiveness.

Association of Serum Vitamin D With Periodontal Disease.

OBJECTIVE: There are conflicting reports on the relationship between vitamin D and periodontal disease. Our research is intended to further analyse the association between serum 25(OH)D3, a vitamin D precursor and periodontal disease based on a large national survey sample in Japan. METHODS: We downloaded the 2009-2018 National Health and Nutrition Examination Survey (NHANES) cycle, which included a total of 23,324 samples. Logistic regression of factors influencing perioral disease including periodntal disease, and subgroup logistic regression were performed to analyse the relationship between serum vitamin D and perioral disease, using WTMEC2YR as weights for regression analysis. Then machine learning model-based prediction of perioral disease onset was performed, and the machine learning algorithms used included boost tree, artificial neural network, AdaBoost, and random forest. RESULTS: We evaluated the vitamin D, age, sex, race, education, marriage, body mass index, ratio of family income to poverty (PIR), smoking, alcohol consumption, diabetes, and hypertension as variables in the included samples. Vitamin D was negatively associated with perioral disease; compared with Q1, the odds ratios and 95% CI were 0.8 (0.67-0.96) for Q2, 0.84 (0.71-1.00) for Q3, and 0.74 (0.6-0.92) for Q4 (P for trend <.05), respectively. The results of the subgroup analysis showed that the effect of 25(OH)D3 on periodontal disease was more pronounced in women younger than 60 years. Based on the accuracy and receiver operating characteristic curve, we concluded that a boost tree was a relatively good model to predict periodontal disease. CONCLUSIONS: Vitamin D might be a protective factor for periodontal disease, and boost tree analysis we emplyed was a relatively good model to predict perioral disease.

Divided-and-combined omnibus test for genetic association analysis with high-dimensional data.

Advances in biologic technology enable researchers to obtain a huge amount of genetic and genomic data, whose dimensions are often quite high on both phenotypes and variants. Testing their association with multiple phenotypes has been a hot topic in recent years. Traditional single phenotype multiple variant analysis has to be adjusted for multiple testing and thus suffers from substantial power loss due to ignorance of correlation across phenotypes. Similarity-based method, which uses the trace of product of two similarity matrices as a test statistic, has emerged as a useful tool to handle this problem. However, it loses power when the correlation strength within multiple phenotypes is middle or strong, for some signals represented by the eigenvalues of phenotypic similarity matrix are masked by others. We propose a divided-and-combined omnibus test to handle this drawback of the similarity-based method. Based on the divided-and-combined strategy, we first divide signals into two groups in a series of cut points according to eigenvalues of the phenotypic similarity matrix and combine analysis results via the Cauchy-combined method to reach a final statistic. Extensive simulations and application to a pig data demonstrate that the proposed statistic is much more powerful and robust than the original test under most of the considered scenarios, and sometimes the power increase can be more than 0.6. Divided-and-combined omnibus test facilitates genetic association analysis with high-dimensional data and achieves much higher power than the existing similarity based method. In fact, divided-and-combined omnibus test can be used whenever the association analysis between two multivariate variables needs to be conducted.

Using preoperative control nutritional status scores as prognostic factors for endometrial cancer.

Background: Previous investigations have reported that controlling nutritional (CONUT) status scores, incorporating total cholesterol (TC) and serum albumin (SA) values, and total lymphocyte (LY) counts, are reliable malignant tumor predictors. However, CONUT scores for predicting endometrial cancer (EC) remain unexplored. Objective: To evaluate preoperative CONUT scores as prognostic factors for postoperative EC. Methods: We retrospectively evaluated preoperative CONUT scores in 785 surgically resected EC patients at our hospital between June 2012 and May 2016. Using time-dependent receiver operating characteristic (ROC) analyses, patients were split into: 1) CONUT-high (CH) (≥1) and 2) CONUT-low (CL) (<1) groups. Relationships between CONUT scores and different clinicopathological, pathological differentiation, muscle layer infiltration depth, and prognosis factors were examined, and Cox regression analyses performed to assess prognostic values on overall survival (OS) rates. Results: We assigned 404 (51.5%) and 381 (58.5%) patients to CH and CL groups, respectively. In the CH group, body mass index (BMI), prognostic nutrition index (PNI), and LY/monocyte ratios (LMR) were decreased, however, neutrophil/LY (NLR) and platelet/LY ratios (PLR) were increased. Pathological differentiation analyses showed that G1 proportions were higher in the CL group, while G2 and G3 proportions were more prevalent in the CH group. Muscle layer infiltration depth in CL patients was < 50%, while that it was ≥50% in the CH group. No significant differences in OS rates were recorded between CH and CL groups over 60 months. However long-term survival (LTS) rates after 60 months in the CH group were significantly lower when compared with the CL group, and was more obvious in type II EC patients. Also, periuterine infiltration and preoperative CONUT scores were independent prognostic factors for OS rates as indicated by multi-factor analyses. Conclusion: CONUT scores not only facilitated the estimation of nutritional status, but were highly beneficial for predicting OS rates in patients with EC after curative resection. CONUT scores provided high predictive values for LTS rates over 60 months in these patients.

Worldwide Bronchiolitis obliterans research: A bibliometric analysis of the published literature between 2002 and 2022.

Bronchiolitis obliterans (BO) is a rare and irreversible chronic respiratory disease. The diagnosis of BO is challenging, and there still needs to be specific therapies and uniform treatment guidelines available. Research on BO has grown steadily over the past 20 years, and with the continued interest of researchers in this area, a bibliometric study of BO becomes necessary. This topic aims to assess the current state of research in BO over the last 2 decades and to identify research hotspots and emerging directions. Information on BO-related articles were obtained from the Science Citation Index Expand of the Web of Science Core Collection (WOSCC [SCI-E]) database. Citespace (6.1.R6), VOSviewer (1.6.18), and the online bibliometrics website (https://bibliometric.com/) were used for bibliometric analysis mainly to include country/region, institution, author, journal, keywords, and references and to construct visual knowledge network diagrams. A total of 4153 publications from the WOSCC [SCI-E] database were included in this study. Most publications come from the United States, Japan, and Germany, which collaborate relatively more frequently. Research institutions in the United States, especially the University of Washington, published the largest number of BO-related articles. Regarding authors, Vos, R is the most productive author, while Verleden, GM is the most influential in BO. In addition, JOURNAL OF HEART AND LUNG TRANSPLANTATION is the journal with the most published articles. The most cited article is Estenne M, 2002. Based on the clustering analysis of keywords and references, the diagnosis of bronchiolitis obliterans syndrome (BOS), treatment of BOS, and risk factors of BO are the current research hotspots and future research trends. We analyzed the publication trends in BO by bibliometrics and mapped the knowledge network of major contributing countries/regions, institutions, authors, and journals. Current research hotspots were found based on the main keywords and references. The outcome may help researchers identify potential collaborators, collaborating institutions, and hot fronts in BO to enhance collaboration on critical issues and improve the diagnosis and treatment of BO.

Correlation Between Hemoglobin Levels and Polycystic Ovary Syndrome Metabolic Disorder.

Objective: The purpose of this study was to explore the relationship between hemoglobin levels and metabolic disorders in patients with PCOS. Methods: A total of 573 patients were selected, based on the hemoglobin level; 342 patients with PCOS were divided into two groups as follows: Group A (normal Hb group, n = 269) and Group B (high Hb group, n = 73); 231 non-PCOS patients were divided into two groups as follows: Group C (normal Hb group, n = 199), and Group D (high Hb group, n = 32). The general information, glucose and lipid metabolism indicators, and uric acid levels of all patients were compiled for data analysis. Results: (1) Hb, HGB concentration in mean red blood cells and RDW in PCOS patients were higher than those in non-PCOS patients, and MCV was lower than that in non-PCOS patients (P < 0.05); (2) Compared with Group A, patients in Group B had higher BMI, Hb, 2-hPG, FINS, 2-hINS, HOMA-IR, LDL-C, and uric acid levels while the QUICKI was lower; in Group C, the age, FSH, HDL-C, and LDL-C were higher, and AMH, BMI, T, TG, and uric acid level were lower (P<0.05); compared with Group D, AMH, BMI, FINS, HOMA-IR, TG, uric acid level increased, while age, FSH, and QUICKI decreased in Group B; and Hb and T decreased in Group C (P<0.05); (3) Pearson's correlation analysis indicated that Hb in PCOS patients was positively correlated with BMI, FPG, 2-hPG, FINS, 2-hINS, and HOMA-IR, and negatively correlated with the QUICKI (P<0.05); (4) Multi-factor logistic regression analysis suggested that the high Hb level in PCOS patients was an independent risk factor of IR (P<0.05). Conclusion: Hb level in patients with PCOS was associated with BMI and glucose metabolism indicators; a high Hb level may be an independent risk factor for IR.

Bibliometric and visual analysis of Kawasaki disease in children from 2012 to 2022.

Background: In recent years, the incidence of Kawasaki disease among the pediatric population has experienced a significant increase. With complications mainly affecting the cardiovascular system, Kawasaki disease has received widespread attention from scholars worldwide. Numerous articles on Kawasaki disease in children have been published far. However, there is a lack of studies that use visualization methods to perform a bibliometric analysis of the relevant literature. This study aims to obtain overall information on the output characteristics of publications on childhood Kawasaki disease between 2012 and 2022 through bibliometric analysis, identify research hotspots and frontiers, and provide new ideas and references for future clinical and scientific research. Methods: Literature meeting the inclusion criteria was screened from the Web of Science Core Collection, PubMed, and Scopus databases. Visual analysis of the literature by country, institution, journal, author, keywords, and references was performed using Citespace (6.1.R6), VOSviewer (1.6.18), and the online bibliometric website (https://bibliometric.com/). Results: A total of 4,867 eligible publications were included. The number of annual publications is generally rising, rapidly increasing since 2019. Among countries and institutions, China and KAOHSIUNG CHANG GUNG MEMORIAL HOSPITAL have the highest output of articles. With 104 publications, Ho-Chang Kuo has a high impact in the field of KD. The most cited author is Jane W. Newburger. The most prolific journal is FRONTIERS IN PEDIATRICS. CIRCULATION is the most frequently co-cited journal. The most popular keyword in frequency and centrality is "immunoglobulin". The reference with the highest burst intensity was Verdoni L, LANCET, 2020. Conclusion: Kawasaki disease in children remains a hot topic among pediatricians worldwide and is receiving increasing attention. We innovated the "national-institutional-journal" model, which promotes further international cooperation in this field. The hot topics in the field of pediatric KD are "KD pathogenesis", "immunoglobulin resistance and complementary therapy", and "cardiovascular complications". Frontiers include disease-related ("multisystem inflammatory syndrome", "coronavirus disease 2019", "hypotension"), treatment-related ("procalcitonin", " anakinra"), and pathogenesis ("polymerase chain reaction").

Natural variation of codon repeats in COLD11 endows rice with chilling resilience.

Abnormal temperature caused by global climate change threatens the rice production. Defense signaling network for chilling has been uncovered in plants. However, less is known about repairing DNA damage produced from overwhelmed defense and its evolution during domestication. Here, we genetically identified a major QTL, COLD11, using the data-merging genome-wide association study based on an algorithm combining polarized data from two subspecies, indica and japonica, into one system. Rice loss-of-function mutations of COLD11 caused reduced chilling tolerance. Genome evolution analysis of representative rice germplasms suggested that numbers of GCG sequence repeats in the first exon of COLD11 were subjected to strong domestication selection during the northern expansion of rice planting. The repeat numbers affected the biochemical activity of DNA repair protein COLD11/RAD51A1 in renovating DNA damage under chilling stress. Our findings highlight a potential way to finely manipulate key genes in rice genome and effectively improve chilling tolerance through molecular designing.

Mathematical modeling of chimeric TCR triggering predicts the magnitude of target lysis and its impairment by TCR downmodulation.

We investigated relationships among chimeric TCR (cTCR) expression density, target Ag density, and cTCR triggering to predict lysis of target cells by cTCR(+) CD8(+) T human cells as a function of Ag density. Triggering of cTCR and canonical TCR by Ag could be quantified by the same mathematical equation, but cTCR represented a special case in which serial triggering was abrogated. The magnitude of target lysis could be predicted as a function of cTCR triggering, and the predicted minimum cTCR density required for maximal target lysis by CD20-specific cTCR was experimentally tested. cTCR density below approximately 20,000 cTCR/cell impaired target lysis, but increasing cTCR expression above this density did not improve target lysis or Ag sensitivity. cTCR downmodulation to densities below this critical minimum by interaction with Ag-expressing targets limited the sequential lysis of targets in a manner that could be predicted based on the number of cTCRs remaining. In contrast, acute inhibition of lysis of primary, intended targets (e.g., leukemic B cells) due to the presence of an excess of secondary targets (e.g., normal B cells) was dependent on the Ag density of the secondary target but occurred at Ag densities insufficient to promote significant cTCR downmodulation, suggesting a role for functional exhaustion rather than insufficient cTCR density. This suggests increasing cTCR density above a critical threshold may enhance sequential lysis of intended targets in isolation, but will not overcome the functional exhaustion of cTCR(+) T cells encountered in the presence of secondary targets with high Ag density.