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.

ObjectiveMagnetoencephalography (MEG), a non-invasive neuroimaging technique, meticulously captures the magnetic fields emanating from brain electrical activity. Compared with MEG based on superconducting quantum interference devices (SQUID), MEG based on optically pump magnetometer (OPM) has the advantages of higher sensitivity, better spatial resolution and lower cost. However, most of the current studies are clinical studies, and there is a lack of animal studies on MEG based on OPM technology. Pain, a multifaceted sensory and emotional phenomenon, induces intricate alterations in brain activity, exhibiting notable sex differences. Despite clinical revelations of pain-related neuronal activity through MEG, specific properties remain elusive, and comprehensive laboratory studies on pain-associated brain activity alterations are lacking. The aim of this study was to investigate the effects of inflammatory pain (induced by Complete Freund’s Adjuvant (CFA)) on brain activity in a rat model using the MEG technique, to analysis changes in brain activity during pain perception, and to explore sex differences in pain-related MEG signaling. MethodsThis study utilized adult male and female Sprague-Dawley rats. Inflammatory pain was induced via intraplantar injection of CFA (100 μl, 50% in saline) in the left hind paw, with control groups receiving saline. Pain behavior was assessed using von Frey filaments at baseline and 1 h post-injection. For MEG recording, anesthetized rats had an OPM positioned on their head within a magnetic shield, undergoing two 15-minute sessions: a 5-minute baseline followed by a 10-minute mechanical stimulation phase. Data analysis included artifact removal and time-frequency analysis of spontaneous brain activity using accumulated spectrograms, generating spectrograms focused on the 4-30 Hz frequency range. ResultsMEG recordings in anesthetized rats during resting states and hind paw mechanical stimulation were compared, before and after saline/CFA injections. Mechanical stimulation elevated alpha activity in both male and female rats pre- and post-saline/CFA injections. Saline/CFA injections augmented average power in both sexes compared to pre-injection states. Remarkably, female rats exhibited higher average spectral power 1 h after CFA injection than after saline injection during resting states. Furthermore, despite comparable pain thresholds measured by classical pain behavioral tests post-CFA treatment, female rats displayed higher average power than males in the resting state after CFA injection. ConclusionThese results imply an enhanced perception of inflammatory pain in female rats compared to their male counterparts. Our study exhibits sex differences in alpha activities following CFA injection, highlighting heightened brain alpha activity in female rats during acute inflammatory pain in the resting state. Our study provides a method for OPM-based MEG recordings to be used to study brain activity in anaesthetized animals. In addition, the findings of this study contribute to a deeper understanding of pain-related neural activity and pain sex differences.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

A high-performance liquid chromatography method using pre-column derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate was developed to determine the content of 15 amino acids in the medicinal snakes Bungarus Parvus, Agkistrodon, and Zaocys. The results showed that the total amino acid(TAA) content ranged from 277.13 to 515.05 mg·g~(-1), with the top four amino acids in all three species being glutamic acid(Glu), glycine(Gly), aspartic acid(Asp), and lysine(Lys). The essential amino acid(EAA) content ranged from 74.56 to 203.94 mg·g~(-1), with Agkistrodon exhibiting the highest content. The non-essential amino acid(NEAA), semi-essential amino acid(semi-EAA), and medicinal amino acid(MAA) content ranged from 189.06 to 318.23, 12.89 to 33.53, and 179.83 to 342.33 mg·g~(-1), respectively, with Zaocys having the highest content in these categories. Amino acid nutritional value was evaluated using the amino acid ratio(RAA), amino acid ratio coefficient(RCAA), and amino acid ratio coefficient score(SRCAA), and the results indicated that all three medicinal snakes possessed good nutritional value. The amino acid composition was similar across the species, though significant differences in content were observed. Based on these differences, an orthogonal partial least squares-discriminant analysis(OPLS-DA) model was established, which could clearly distinguish between the three medicinal snake species. The key differences in amino acid content included Gly, tyrosine(Tyr), Glu, and serine(Ser), which may be related to the observed clinical application differences among the species. Further research into the mechanisms of these differential amino acids is expected to provide more insights into the clinical application disparities of these three medicinal snake species.
Amino Acids/chemistry* ; Animals ; Nutritive Value ; Chromatography, High Pressure Liquid ; Snakes/classification* ; Bungarus

This paper aimed to use non-targeted urine metabolomics to reveal the potential biomarkers of toxicity in rats with hepatic injury induced by aqueous extracts of Dictamni Cortex(ADC). Forty-eight SD rats were randomly assigned to a blank group and high-dose, medium-dose, and low-dose ADC groups, with 12 rats in each group(half male and half female), and they were administered orally for four weeks. The hepatic injury in SD rats was assessed by body weight, liver weight/index, biochemical index, L-glutathione(GSH), malondialdehyde(MDA), and pathological alterations. The qPCR was utilized to determine the expression of metabolic enzymes in the liver and inflammatory factors. Differential metabolites were screened using principal component analysis(PCA) and partial least squares-discriminant analysis(PLS-DA), followed by a metabolic pathway analysis. The Mantel test was performed to assess differential metabolites and abnormally expressed biochemical indexes, obtaining potential biomarkers. The high-dose ADC group showed a decrease in body weight and an increase in liver weight and index, resulting in hepatic inflammatory cell infiltration and hepatic steatosis. In addition, this group showed elevated levels of MDA, cytochrome P450(CYP) 3A1, interleukin-1β(IL-1β), and tumor necrosis factor-α(TNF-α), as well as lower levels of alanine transaminase(ALT) and GSH. A total of 76 differential metabolites were screened from the blank and high-dose ADC groups, which were mainly involved in the pentose phosphate pathway, tryptophan metabolism, purine metabolism, pentose and glucuronic acid interconversion, galactose metabolism, glutathione metabolism, and other pathways. The Mantel test identified biomarkers of hepatotoxicity induced by ADC in SD rats, including glycineamideribotide, dIDP, and galactosylglycerol. In summary, ADC induced hepatotoxicity by disrupting glucose metabolism, ferroptosis, purine metabolism, and other pathways in rats, and glycineamideribotide, dIDP, and galactosylglycerol could be employed as the biomarkers of its toxicity.
Animals ; Male ; Rats, Sprague-Dawley ; Rats ; Metabolomics ; Biomarkers/metabolism* ; Liver/metabolism* ; Drugs, Chinese Herbal/adverse effects* ; Female ; Chemical and Drug Induced Liver Injury/metabolism* ; Glutathione/metabolism* ; Humans

The study aims to elucidate the existence forms(original constituents and metabolites) of Notoginseng Radix et Rhizoma in rats and reveal its metabolic pathways. After Notoginseng Radix et Rhizoma was administered orally once a day for seven consecutive days to rats, all urine and feces samples were collected for seven days, while the blood samples were obtained 6 h after the last administration. Using the ultra high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technique, this study identified 6, 73, and 156 existence forms of Notoginseng Radix et Rhizoma in the rat plasma, urine, and feces samples, respectively. Among them, 101 compounds were identified as new existence forms, and 13 original constituents were identified by comparing with reference compounds. The metabolic reactions of constituents from Notoginseng Radix et Rhizoma were mainly deglycosylation, dehydration, hydroxylation, hydrogenation, dehydrogenation, acetylation, and amino acid conjugation. Furthermore, the possible in vivo metabolic pathways of protopanaxatriol(PPT) in rats were proposed. Through comprehensive analysis of the liquid chromatography-mass spectrometry(LC-MS) data, isomeric compounds were discriminated, and the planar chemical structures of 32 metabolites were clearly identified. According to the literature, 48 original constituents possess antitumor and cardiovascular protective bioactivities. Additionally, 32 metabolites were predicted to have similar bioactivities by SuperPred. This research lays the foundation for further exploring the in vivo effective forms of Notoginseng Radix et Rhizoma.
Animals ; Rats ; Drugs, Chinese Herbal/pharmacokinetics* ; Rhizome/metabolism* ; Male ; Rats, Sprague-Dawley ; Chromatography, High Pressure Liquid ; Panax notoginseng/chemistry* ; Tandem Mass Spectrometry ; Feces/chemistry*

The aim of this investigation was to determine the optimal storage medium for testicular hypothermic transportation and identify the ideal concentration for the application of the protective agent 5-aminolevulinic acid (5-ALA). Furthermore, this study aimed to explore the underlying mechanism of the protective effects of 5-ALA. First, we collected and stored mouse testicular fragments in different media, including Hank's balanced salt solution (HBSS; n = 5), Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 (DMEM/F12; n = 5), and alpha-minimum essential medium (αMEM; n = 5). Storage of testicular tissue in HBSS preserved the integrity of testicular morphology better than that in the DMEM/F12 group ( P < 0.05) and the αMEM group ( P < 0.01). Testicular fragments were subsequently placed in HBSS with various concentrations of 5-ALA (0 [control], 1 mmol l -1 , 2 mmol l -1 , and 5 mmol l -1 ) to determine the most effective concentration of 5-ALA. The 2 mmol l -1 5-ALA group ( n = 3) presented the highest positive rate of spermatogonial stem cells compared with those in the control, 1 mmol l -1 , and 5 mmol l -1 5-ALA groups. Finally, the tissue fragments were preserved in HBSS with control ( n = 3) and 2 mmol l -1 5-ALA ( n = 3) under low-temperature conditions. A comparative analysis was performed against fresh testes ( n = 3) to elucidate the underlying mechanism of 5-ALA. Gene set enrichment analysis (GSEA) for WikiPathways revealed that the p38 mitogen-activated protein kinase (MAPK) signaling pathway was downregulated in the 2 mmol l -1 5-ALA group compared with that in the control group (normalized enrichment score [NES] = -1.57, false discovery rate [FDR] = 0.229, and P = 0.019). In conclusion, these data suggest that using 2 mmol l -1 5-ALA in HBSS effectively protected the viability of spermatogonial stem cells upon hypothermic transportation.
Male ; Animals ; Testis/cytology* ; Aminolevulinic Acid/pharmacology* ; Mice ; Organ Preservation/methods* ; Organ Preservation Solutions/pharmacology* ; Cryopreservation/methods*

BACKGROUND: Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN). METHODS: This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models. RESULTS: The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability. CONCLUSIONS The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
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Humans ; Male ; Female ; Lung Neoplasms/pathology* ; Middle Aged ; Retrospective Studies ; Artificial Intelligence ; Aged ; Tomography, X-Ray Computed ; Adult ; Solitary Pulmonary Nodule/diagnostic imaging* ; ROC Curve

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Objective: To investigate the effects of Zuogui Jiangtang Jieyu Formula (ZGJTJYF) on histone H3 lysine 18 lactylation (H3K18la) in the hippocampus of rats with diabetes mellitus complicated with depression (DD) and predict the regulatory genes of H3K18la. Methods: Male Sprague-Dawley rats were divided into control, model, and positive drug (metformin [0.18 g/kg] and fluoxetine [1.8 mg/kg]) groups, and the three groups were treated with high, medium, and low ZGJTJYF doses (20.52, 10.26, and 5.13 g/kg, respectively), with 10 rats per group. After treatment, the forced swimming and water maze tests were performed to assess depressive-like behaviors and cognitive function. An enzyme-linked immunosorbent assay was used to measure blood insulin, glycosylated hemoglobin, lactate levels, and lactate content in the hippocampus. Western blotting was used to detect H3K18la expression in the hippocampus. Cleavage Under Targets and lagmentation(CUT&Tag) experiments targeted hippocampal H3K18la epigenetic modification regions to analyze the transcription factors bound by H3K18la. Kyoto Encyclopedia of Genes and Genomes and Protein-Protein Interaction networks were constructed to identify key pathways and target genes regulated by H3K18la. Results: Compared with the normal group, the model group rats showed prolonged immobility time in the forced swim test, increased escape latency in the water maze experiment, decreased target quadrant distance ratio (P<0.01), increased serum lactate content, and decreased lactate content in hippocampal homogenate (P<0.01), as well as decreased H3K18la protein expression in the hippocampus (P<0.01). Compared with the model group, ZGJTJYF reduced the immobility time in the forced swim test and the escape latency in the water maze test (P<0.01), while the distance ratio in the target quadrant increased (P<0.01) in model rats. Lowered fasting blood glucose, insulin, and glycosylated hemoglobin levels (P<0.05, P<0.01) were also observed. ZGJTJYF also increased the lactate content and H3K18la protein expression in hippocampal homogenate (P<0.05, P<0.01). The DNA sequences bound by H3K18la were predominantly enriched at the transcription start sites. ZGJTJYF modulated H3K18la-associated pathways, including cell adhesion junctions, tumor growth factor-beta (TGF-β) signaling, stem cell pluripotency regulation, mitogen-activated protein kinase(MAPK) signaling pathway, and insulin resistance, leading to the identification of 12 target genes. Conclusion ZGJTJYF enhances hippocampal lactate levels and H3K18la modification in DD rats, which may regulate neural cell interactions, neurogenic stem cell function, TGF-β signaling, MAPK signaling, and insulin resistance pathways.