Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

GPR126, also known as ADGRG6, is one of the most deeply studied aGPCRs. Initially, GPR126 was thought to be a receptor associated with muscle development and was primarily expressed in the muscular and skeletal systems. With the deepening of research, it was found that GPR126 is expressed in multiple mammalian tissues and organs, and is involved in many biological processes such as embryonic development, nervous system development, and extracellular matrix interactions. Compared with other aGPCRs proteins, GPR126 has a longer N-terminal domain, which can bind to ligands one-to-one and one-to-many. Its N-terminus contains five domains, a CUB (complement C1r/C1s, Uegf, Bmp1) domain, a PTX (Pentraxin) domain, a SEA (Sperm protein, Enterokinase, and Agrin) domain, a hormone binding (HormR) domain, and a conserved GAIN domain. The GAIN domain has a self-shearing function, which is essential for the maturation, stability, transport and function of aGPCRs. Different SEA domains constitute different GPR126 isomers, which can regulate the activation and closure of downstream signaling pathways through conformational changes. GPR126 has a typical aGPCRs seven-transmembrane helical structure, which can be coupled to Gs and Gi, causing cAMP to up- or down-regulation, mediating transmembrane signaling and participating in the regulation of cell proliferation, differentiation and migration. GPR126 is activated in a tethered-stalk peptide agonism or orthosteric agonism, which is mainly manifested by self-proteolysis or conformational changes in the GAIN domain, which mediates the rapid activation or closure of downstream pathways by tethered agonists. In addition to the tethered short stem peptide activation mode, GPR126 also has another allosteric agonism or tunable agonism mode, which is specifically expressed as the GAIN domain does not have self-shearing function in the physiological state, NTF and CTF always maintain the binding state, and the NTF binds to the ligand to cause conformational changes of the receptor, which somehow transmits signals to the GAIN domain in a spatial structure. The GAIN domain can cause the 7TM domain to produce an activated or inhibited signal for signal transduction, For example, type IV collagen interacts with the CUB and PTX domains of GPR126 to activate GPR126 downstream signal transduction. GPR126 has homology of 51.6%-86.9% among different species, with 10 conserved regions between different species, which can be traced back to the oldest metazoans as well as unicellular animals.In terms of diseases, GPR126 dysfunction involves the pathological process of bone, myelin, embryo and other related diseases, and is also closely related to the occurrence and development of malignant tumors such as breast cancer and colon cancer. However, the biological function of GPR126 in various diseases and its potential as a therapeutic target still needs further research. This paper focuses on the structure, interspecies differences and conservatism, signal transduction and biological functions of GPR126, which provides ideas and references for future research on GPR126.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective To retrospectively analyze the distribution and differences of oral behavior among patients with acute and chro-nic painassociated with temporomandibular disorders(TMD).Methods A total of 212 patients with pain TMD in West China Hospital of Stomatology completed oral behaviors checklist(OBC).SPSS statistical software was used to analyze all the data.Results The pa-tients with pain-related TMD had specific oral behaviors,such as"pressure on the jaw during sleep"(49.5%),"unilateral chewing"(49.5%),"upper and lower teeth contact when not eating"(37.7%),etc.Scores of"upper and lower teeth contact when not eating"and"muscle tension when teeth are not clenched or teeth are not in contact"in patients with chronic pain TMD were higher than those of acute patients,and the difference was statistically significant(P＜0.05).The total OBC scores and daytime OBC scores of chronic pain TMD patients were higher than those of acute pain patients,and the difference was statistically significant(P＜0.05).There was no significant difference in OBC scores of patients with acute and chronic pain TMD during sleep(P＞0.05).Conclusion Pain-related TMD patients had specific oral behaviors,and patients with chronic pain TMD exhibited higher levels of total OBC,daytime OBC,"upper and lower teeth contact when not eating"and"muscle tension when teeth do not bite or teeth are not in contact"oral behavior than acute pain TMD patients.In the treatment of patients with painful TMD,correcting the patient's bad oral behavior can help the treatment of pain-related TMD.

Blonanserin,a second-generation atypical antipsychotic agent,acts as an antagonist for dopamine D2,D3,and serotonin 5-HT2A receptors.Clinical studies have demonstrated that blonanserin is non-inferior to other antipsychotics,such as haloperidol and risperidone,in alleviating the symptoms of schizophrenia.Moreover,it exhib-its beneficial effects on cognitive symptoms and social functioning,with a favorable safety profile,making it one of the key treatment options for schizophrenia.With extensive clinical experience accumulated in China,this expert consensus aims to provide psychiatrists with updated and localized guidance on the optimal use of blonan-serin.Based on a systematic review of the latest evidence-particularly studies in Chinese population,this paper pres-ents the updated Chinese expert recommendations for the clinical use of blonanserin in 2024.

Objective:To investigate the differences in clinical outcomes of septic children with varying serum zinc levels,and to analyze the relationship between reduced serum zinc levels and organ dysfunction as well as 28-day mortality in septic children.Methods:This study conducted a retrospective analysis of clinical data from pediatric patients diagnosed with sepsis or septic shock in the Department of critical care medicine of the children's Hospital of Soochow University between January 2017 and December 2022.Clinical characteristics,organ dysfunction,and prognosis were compared between two groups:children with low serum zinc levels and those with normal zinc levels.Results:The serum zinc level of septic children within 24 hours of admission was 9.60(5.52,13.80)μmol/L,with 50.54%(94/186)of the children exhibiting low serum zinc levels(<10.07 μmol/L).Compared to the normal serum zinc group,the low serum zinc group had a significantly lower Pediatric Critical Illness Score(PCIS)[(78.71±9.35)vs.(85.12±8.51),P=0.005]and higher 28-day mortality(46.80%vs.14.13%,P<0.001).The low serum zinc group also had a higher proportion of invasive mechanical ventilation(64.89%vs.47.82%,P=0.019),renal replacement therapy(15.59%vs.3.26%,P=0.003),and use of vasoactive drugs(56.38%vs.30.43%,P<0.001).The rate of underlying conditions in the low serum zinc group was significantly higher than that in the normal serum zinc group(57.44%vs.36.95%,P=0.005).Additionally,the low serum zinc group had a higher incidence of disseminated intravascular coagulation(DIC),respiratory failure,acute kidney injury,shock,and multiple organ dysfunction syndrome(MODS)compared to the normal serum zinc group(P<0.05).Serum zinc levels had predictive value for 28-day mortality in septic children(AUC=0.813;95%CI:0.725～0.902;P<0.001).A serum zinc level of less than 6.950 μmol/L predicted the death of septic children with a sensitivity of 0.618 and a specificity of 0.902.Conclusion:Sepsis in children is commonly associated with low serum zinc levels,especially in those with underlying conditions such as hematologic and oncologic disorders.Sepsis patients hypozincemia with a higher incidence of DIC,respiratory failure,acute kidney injury,shock,and MODS.A serum zinc level below 6.95 μmol/L serves as a significant predictor of 28-day mortality in children with severe sepsis.

Objective:To investigate the immuno-inflammatory regulatory effects of the Qing Gan San Jie Xiao Ying Formula(QGSJXYF)on Hashimoto's thyroiditis(HT)by modulating thyroid cell-derived exosomes to provide experi-mental evidence for its immunomodulatory mechanisms.Methods:Nthy-ori-3-1 thyroid cells were treated with QGSJXYF-medicated serum,with untreated cells serving as controls.Exosomes from both groups were extracted and analyzed using nanoparticle tracking analysis(NTA),transmission electron microscopy(TEM),and Western blot to assess concentration,size distribution,morphology,and the expression of characteristic exosomal markers.An inflammatory model of human T lymphocytes(H9)was established and co-incubated with normal exosomes(EXO-C group)or QGSJXYF-treated exosomes(EXO-T group).The levels of inflammatory cytokines in H9 cells were measured using Western blot(WB)and ELISA.Results:Exosome characterization showed that the particle concentration of Nthy-ori-3-1 cell-derived exosomes in both the control and QGSJXYF groups ranged from 1×109 to 1×1011/mL,with particle diameters between 80～300 nm.The exosomes exhibited a typical spherical or cup-shaped morphology with positive expression of TSG101,CD63,and HSP70.Compared with the inflammation model group and the EXO-C group,the EXO-T group significantly reduced the intracellular expression of IL-17A protein in H9 cells(P<0.05)and suppressed IL-17 and IL-6 levels in the cell supernatant(P<0.01).Conclusion:QGSJXYF may exert its anti-inflammatory and thyroid-protective effects by modulating the functional state of thyroid cell-derived exosomes,regulating the inflamma-tory microenvironment,and inhibiting the expression of inflammatory cytokines associated with Hashimoto's thyroiditis.

Human non-histone lysine crotonylation plays crucial roles in biological activities.However,traditional wet-lab experiments are time-consuming and labor-intensive,making computational prediction methods increasingly popular in recent years.Despite the biological importance of lysine crotonylation,there are relatively few studies on human non-histone proteins.In this study,we developed an ensemble deep learning predictor named iHNHC-RsFPN by constructing a Residual Pyramid Network(RsFPN).First,three feature extraction methods were employed to encode sequence samples.Next,weak classifi-ers based on RsFPN were individually trained for different feature types.Finally,these weak classifiers were integrated to build a robust final predictor.Independent test results demonstrated that iHNHC-RsF-PN achieved outstanding performance across four key metrics:sensitivity(Sn=0.8580),specificity(Sp=0.7463),accuracy(Acc=0.7798),and Matthews correlation coefficient(MCC=0.5586).Comparative experiments revealed that iHNHC-RsFPN significantly improved prediction accuracy for hu-man non-histone crotonylation sites over existing methods.Additionally,we established a user-friendly web server(http://www.lzzzlab.top/ihnc/)that provides straightforward prediction services without complex calculations,facilitating further research for experts in related fields.

Aim To investigate the mechanism of Guanxinning injection regulating cardiac immune mi-croenvironment to improve myocardial infarction in mice.Methods In this study,MI model was estab-lished by permanent ligation of left anterior descending coronary artery in mice.The mice were divided into five groups:sham operation group,model group,Guanxinning injection low dose group,Guanxinning in-jection high dose group and positive drug captopril group.Hearts were weighed,heart tissues were collect-ed,and Masson staining was used for pathological anal-ysis of heart tissues;immunofluorescence staining was used to detect apoptosis and CCL21 expression in the infarct border zone;flow cytometry was used to detect the proportion of immune cells in myocardial ischemia tissues and lymph nodes;PCR was used to detect CCL21 expression in heart and in vitro human lymphat-ic endothelial cells(HLEC).Results Compared with the model group,the low and high dose groups of Guanxinning injection significantly improved cardiac hypertrophy.Apoptosis in the border zone of myocardi-al infarction was reduced in the low and high dose groups of Guanxinning injection and captopril group.Compared with the model group,the proportion of leu-kocytes in the infarct border zone was dreduced and the proportion of CD4+T cells,Treg cells,and CD8+T cells in the mediastinal lymph nodes and infarct border zone of the heart was regulated in the low and high dose groups of Guanxinning injection;CCL21 secretion by the heart and lymphatic vessels increased.Conclu-sions Guanxinning injection can significantly improve cardiac hypertrophy and fibrosis in MI mice,reduce ap-optosis in the infarct border zone,and play a role in an-ti-myocardial ischemia injury by promoting CCL21 ex-pression in lymphatic vessels to regulate the proportion of mediastinal lymph nodes and cardiac T cells after myocardial infarction.