ObjectiveThe malaria parasites remodel the host erythrocyte structure by exporting parasite proteins that interact with the membrane skeleton proteins of red blood cells (RBCs), facilitating their intracellular survival and pathogenicity. Skeleton-binding protein 1 (SBP1) is a conserved exported protein across Plasmodium species. In Plasmodium falciparum, SBP1 has been reported to interact with erythrocyte membrane skeleton proteins 4.1R and spectrin, while its contribution to erythrocyte remodeling and parasite virulence in Plasmodium berghei (Pb) remains unclear. This study aims to determine whether PbSBP1 associates with the host cytoskeletal protein 4.1R and to investigate its role in the remodeling of host RBCs and the pathogenicity of Plasmodium berghei. MethodsIn Plasmodium berghei, the relationship between PbSBP1 and the erythrocyte cytoskeletal protein 4.1R was examined using co-immunoprecipitation. A Pbsbp1 gene knockout mutant of Plasmodium berghei (Pbsbp1∆) was generated based on the principle of double crossover homologous recombination. The deformability of erythrocytes infected with Pbsbp1∆ parasites was assessed using microfluidic methods. Microchannels with an array of cylindrical pillars were used to detect modifications in infected RBC deformability. The infected RBCs were squashed between the rows and recovered between the columns and the transit velocity (μm/s) of infected RBCs travelling through the microchannel was recorded. The component of the erythrocyte membrane skeleton junctional complex, tropomodulin (TMOD), was fluorescently labeled, and the cytoskeletal network of infected erythrocytes was imaged using super-resolution stochastic optical reconstruction microscopy (STORM) to analyze ultrastructural changes in the cytoskeleton of wild-type (WT) and Pbsbp1∆-infected erythrocytes. Actin-based junctional complexes were displayed as individual clusters by the labeled TMOD in the STORM images, and the cluster densities and distances between adjacent clusters of infected RBCs were calculated. Additionally, rodent malaria models (BALB/c mice) and experimental cerebral malaria models (C57BL/6 mice) were employed to monitor the growth of Pbsbp1∆ and WT parasites during the intraerythrocytic stage and their capacity to induce cerebral malaria in mice. ResultsPbSBP1 may participate in the remodeling of infected erythrocytes through direct or indirect interaction with the erythrocyte cytoskeletal protein 4.1R. Microfluidic assays revealed that the deformability of erythrocytes infected with Pbsbp1∆ parasites was significantly enhanced compared to those infected with WT parasites. STORM imaging further demonstrated that the ultrastructure of the erythrocyte cytoskeleton in Pbsbp1∆-infected cells was altered relative to that in WT-infected erythrocytes. The distances between nearest neighbors of clusters had a tendency to increase while the cluster densities were decreased in Pbsbp1∆-infected RBCs compared to WT-infected RBCs. Subsequent phenotypic analysis indicated that the growth rate of Pbsbp1∆ parasites during the intraerythrocytic stage was significantly slower than that of WT parasites, and their ability to induce cerebral malaria in mice was also attenuated. These findings suggest that PbSBP1 is involved in the remodeling of the erythrocyte membrane skeleton, likely through its direct or indirect interaction with protein 4.1R, thereby regulating the deformability of infected erythrocytes and influencing the pathogenicity of the blood-stage parasites. ConclusionThis study establishes a role for PbSBP1 in host erythrocyte remodeling and parasite virulence, providing new research strategies for the prevention and treatment of malaria.

With the rising incidence of colon cancer, several studies have indicated that aquaporin 1 (AQP1) expression is associated with the development of colon cancer. This study aims to elucidate the potential molecular mechanisms between them. Methods: We screened data from The Cancer Genome Atlas (TCGA) database and retrospectively examined AQP1 protein expression in 127 colon cancer patients to analyze the relationship between AQP1 expression and pathological stages, prognosis. We created stable colon cancer cell lines with differential AQP1 expression, the effect of AQP1 expression on the proliferation and migration of colon cancer cells was assessed by in vitro and in vivo studies, and explored potential molecular mechanisms through Western blotting. Results: High AQP1 expression was associated with poorer survival (overall survival [OS], p = .028) in colon cancer patients from the TCGA database. Similarly, retrospective clinical data indicated that high AQP1 expression was associated with reduced disease-free survival and OS (p = .036 and p = .017, respectively). The low-expressing AQP1 colon cancer cells exhibited a decrease in proliferation and migration ability of colon cancer cells compared to the overexpressing AQP1 group (p < .05) in vitro and in vivo. Immunohistochemistry and western blotting experiments validated heightened expression of N-cadherin, vimentin, and claudin- 1 in the tumor tissues of the overexpressing AQP1 group. Conversely, reduced AQP1 expression resulted in decreased expression of claudin- 1. Conclusions: AQP1 correlates with unfavorable prognosis in colon cancer and potentially enhances the proliferation and migration of colon cancer by up-regulating claudin-1 expression.

Lianpo Yin was first recorded in the Revised Treatise on Cholera from Suixi Residence by WANG Mengying. It is composed of seven medicinal herbs： Coptidis Rhizoma， Magnoliae Officinalis Cortex， Sojae Semen Praeparatum， Acori Tatarinowii Rhizoma， Pinelliae Rhizoma， Gardeniae Fructus， and Phragmitis Rhizoma. As one of the classic prescriptions for clearing heat， resolving dampness， regulating Qi， and harmonizing the middle energizer， it has been included in the Catalogue of Ancient Classic Prescriptions （Second Batch： Han Chinese Medicine） published by the National Administration of Traditional Chinese Medicine in 2023. Lianpo Yin is primarily indicated for cholera caused by the accumulation of dampness-heat， and it can promote digestion and eliminate phlegm. By summarizing the ancient literature records， chemical constituents of individual herbs and the compound formula， pharmacological effects， and modern clinical applications of Lianpo Yin， this paper discovers that the understandings of most ancient physicians are consistent with the original text. The pathogenesis treated by this prescription is generally attributed to the accumulation of dampness-heat in the middle energizer and disrupted ascending and descending of Qi. The main chemical components of this prescription include coptisine， trigonelline， genistein， palmatine， berberine， honokiol， and magnolol. Lianpo Yin exhibits pharmacological effects such as anti-inflammatory activity， regulation of apoptosis， modulation of mitochondrial autophagy， regulation of the hypothalamic-pituitary-adrenal （HPA） axis， promotion of gastrointestinal motility， improvement of the gastric mucosal barrier， regulation of intestinal flora and their metabolites， and antimicrobial activity. In modern clinical practice， this prescription is mainly used to treat digestive system diseases such as chronic superficial gastritis and Helicobacter pylori （Hp）-associated gastritis. Additionally， it demonstrates significant therapeutic effects on various diseases affecting the nervous， respiratory， dermatological， and cardiovascular systems. This study provides a detailed review of the ancient literature records， chemical components， pharmacological effects， and clinical applications of Lianpo Yin and its modified formulas， aiming to offer references for the dosage form development and broader clinical application of this classic prescription.

Aim To explore the relationship between serum levels of proprotein convertase subtilisin/kexin type 9(PCSK9),macrophage migration inhibitory factor(MIF)and the severity of coronary artery lesions in patients with coro-nary heart disease(CHD).Methods A cross-sectional study was conducted involving 139 patients with CHD and 69 control subjects who underwent coronary angiography during the same period,all of whom were admitted to the People's Hospital of Xinjiang Uygur Autonomous Region from November 2023 to May 2024.Clinical data and coronary angiography results were collected,and the severity of coronary artery stenosis was quantitatively assessed using the Gensini score.Pa-tients with the Gensini scores＞0 were classified into three groups based on tertiles:the mild stenosis group(1～18 points,54 cases),the moderate stenosis group(19～36 points,54 cases),and the severe stenosis group(＞36 points,54 ca-ses).Serum levels of PCSK9 and MIF were measured by ELISA kit.Results Serum levels of PCSK9 and MIF were significantly higher in the CHD group than those in the control group(P＜0.05).Multivariable Logistic regression analy-sis revealed that high levels of serum PCSK9 and MIF were independent risk factors for CHD.Spearman correlation analy-sis showed that serum PCSK9 and MIF levels were positively correlated with Gensini score(rs=0.619 6 and r,=0.411 4,both P＜0.001).Further subgroup analysis showed that serum total cholesterol and low density lipoprotein cholesterol lev-els were significantly increased in patients with high-level PCSK9,while patients with high-level MIF had higher inflamma-tory coefficients such as systemic inflammatory response index(SIRI)and systemic immune-inflammation index(SII)(all P＜0.05).Conclusion Serum levels of PCSK9 and MIF are positively correlated with the severity of coronary artery stenosis.High levels of serum PCSK9 and MIF are independent risk factors for CHD.

Objective:To investigate the predictive value of machine learning-based CT radiomics model for radioresistance in patients with esophageal squamous cell carcinoma (ESCC).Methods:Clinical data of 185 patients with ESCC treated with radical radiotherapy in the First Affiliated Hospital of Anhui Medical University from December 2015 to July 2022 were retrospectively analyzed, and all patients were randomly divided into a training set ( n=129) and a validation set ( n=56) at a ratio of 7 : 3. The radiomics parameters of the primary lesion of esophageal cancer and the surrounding 5 cm region in the patients' CT arterial phase images were extracted, and 6 machine learning methods were used to screen the optimal radiomics model to obtain the optimal radiomics score (Radscore). Independent prognostic predictors of radioresistance in ESCC were obtained by univariate and multivariate logistic regression analyses, which was used as the basis for constructing the nomogram. The predictive performance of different models was compared by the area under the receiver operating characteristic (ROC) curve (AUC). The predictive efficacy and clinical value of the combined model were evaluated using calibration curve, decision curve analysis and clinical impact curve, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results:The combined intratumoral and peritumoral radiomics model based on naive Bayesian classifier yielded the optimal prediction performance, with AUC of 0.859 and 0.936 in the training set and validation set, respectively. Multivariate logistic regression analysis showed that Radscore and T stage were the independent prognostic predictors of radioresistance in ESCC patients, and the AUC of the combined model constructed based on these predictors in the training and validation sets were 0.942 and 0.959, respectively. Calibration curve, decision curve analysis and clinical impact curve, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) all indicated higher clinical benefit and more consistent predictive efficacy of the combined model.Conclusions:Machine learning-based CT radiomics model is useful for the prediction of radioresistance in ESCC. The nomogram of radiomics and clinical parameters can further improve the prediction accuracy and provide novel reference for individualized treatment of patients with ESCC.

Objective:To explore the predictive value of models based on clinical parameters, deep learning radiomics (DLR) from CT images, and traditional handcrafted radiomics (HCR) in assessing pathological complete response (pCR) after neoadjuvant radiotherapy combined with medical therapy in patients with esophageal cancer.Methods:A retrospective study was conducted on 130 patients with locally advanced esophageal cancer who underwent neoadjuvant radiotherapy combined with medical therapy followed by surgery at the First Affiliated Hospital of the University of Science and Technology of China from August 1, 2018, to August 31, 2024. Patients were randomly divided into a training set ( n=91) and a validation set ( n=39) at a ratio of 7:3. Logistic regression analysis was performed to identify clinical independent risk factors associated with pCR. DLR and HCR features were extracted from the tumor and the 5 mm peritumoral region on planning CT images. Features for modeling were selected using t-test, Mann-Whitney U test or Fisher exact probability method, least absolute shrinkage and selection operator (LASSO) regression to calculate the radiomics score (Rad-score). A nomogram was then constructed by integrating the clinical risk factors. The predictive performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and decision curve analysis (DCA) to assess clinical benefits. Results:Multivariate logistic regression analysis identified body weight ( OR=1.101, 95% CI: 1.029-1.177, P=0.005) and lymph node positivity ( OR=0.100, 95% CI: 0.014-0.727, P=0.023) as independent predictors of pCR. The peritumoral DLR-HCR model showed superior predictive performance, with AUCs of 0.870 (95% CI: 0.799-0.942) in the training set and 0.866 (95% CI: 0.750-0.982) in the validation set. The combined model incorporating clinical parameters achieved the best performance, with AUCs of 0.903 (95% CI: 0.845-0.962) and 0.888 (95% CI: 0.782-0.994) in the training and validation sets, respectively. Conclusions:The combined model integrating peritumoral DLR-HCR features with clinical parameters provides excellent predictive value for pCR after neoadjuvant radiotherapy combined with medical therapy in esophageal cancer and offers valuable guidance for personalized treatment strategies.

Objective To explore the regulatory effect of methyltransferase-like 3(METTL3)on m6A methylation of Sigma-1 receptor(Sigma-1R)mRNA and mitophagy in cerebral microvascular endothelial cells of sepsis mice.Methods Twelve adult male C57BL/6J mice were randomly divided into the Sham group(without cecal ligation or puncture)and the sepsis group(received cecal ligation and puncture),with 6 mice in each group.m6A methylation levels,and relative expression of METTL3 and Sigma-1R mRNA and protein in cerebral micro-vascular tissues were detected by m6A Dot blot,RT-qPCR,and Western blot,respectively.The bEnd.3 cells were cultured in vitro and divided into the control group(normal culture),model group[lipopolysaccharide(LPS)-induced in vitro sepsis],si-NC group(LPS treat-ment combined with si-NC transfection),and si-METTL3 group(LPS treatment combined with si-METTL3 transfection).m6A Dot blot was used to detect m6A methylation levels of cells in each group;RT-qPCR was used to detect the mRNA expression of METTL3 and Sigma-1R;and Western blot was used to detect the expression of METTL3,Sigma-1R,and autophagy-related proteins of Bnip3,LC3B,and Beclin1.m6A chromatin immunoprecipitation-qPCR was used to detect m6A methylation level of Sigma-1R of cells in each group.JC-1 probe was used to detect the mitochondrial membrane potential,and the ATP assay kit was used to detect the mitochondrial ATP content.Results Compared with the Sham group,the sepsis group showed increased m6A methylation level and METTL3 expression(P<0.05),and decreased Sigma-1R expression in cerebral microvascular tissues(P<0.05).Compared with the control group,m6A methylation level,METTL3 expression and m6A methylation level of Sigma-1R mRNA increased,the expression of Sigma-1R,the normal rate and increase rate of mitochondrial membrane potential,and the ATP content decreased,and the protein expression of Bnip3,LC3B and Beclin1 downregulated in the model group and the si-NC group,with statistically significant differences(P<0.05).Compared with the si-NC group,m6A methylation level,METTL3 expression and m6A methylation level of Sigma-1R mRNA decreased,the expression of Sigma-1R,the normal rate and increase rate of mitochondrial membrane potential elevated,the ATP content increased,and the protein expression of Bnip3,LC3B and Beclin1 upregulated in the si-METTL3 group,with statistically significant differences(P<0.05).Conclusion Silencing METTL3 can inhibit m6A methylation of Sigma-1R mRNA and promote the mitophagy in cerebral microvascular endothelial cells of septic mice.

Background:To compare the efficacy and safety of monthly administrations of gonadotropin releasing hormone (GnRH) agonists LY01005 and Zoladex ? in Chinese patients with premenopausal breast cancer. Methods:From October 2020 to November 2021, 188 premenopausal breast cancer patients were enrolled in 34 hospitals and randomized 1:1 to receive either LY01005 or Zoladex ? every 28 days for a total of three injections. All patients concomitantly received oral tamoxifen (TAM). The primary efficacy endpoint was cumulative probability of maintaining menopausal level [oestradiol (E2) ≤30 pg/ml] from day 29 to day 85. The second efficacy endpoint included changes in E2, luteinizing hormone (LH), and follicle-stimulating hormone (FSH) compared with the baseline. Pharmacokinetics (PK), pharmacodynamics (PD), and safety were analyzed. The study also evaluated the pharmacokinetic and pharmacodynamic characteristics of LY01005. Results:A total of 188 patients were randomised and 187 patients received either LY01005 or Zoladex ?. Cumulative probabilities of maintaining menopausal level (E2≤30 pg/ml) from day 29 to day 85 were 93.1% for LY01005 and 86.3% for Zoladex ?. The between-group difference was 6.8% (95% CI: -2.3%, 15.9%) and primary efficacy in the LY01005 group was not inferior to that in the Zoladex ? group. Changes in E2, LH, and FSH levels compared with the baseline were equivalent between the two groups (E2: 89.34% to 90.23% vs. 82.11% to 85.02%; LH: 88.89% to 95.52% vs. 89.70% to 97.02%; FSH: 75.36% to 80.85% vs.73.07% to 80.24%, respectively). After three consecutive doses of LY01005, the LH and FSH levels of the subjects showed a transient increase after the first dose, reached a peak on the second day and then started to decrease. The LH and FSH reached a lower level and remained at or below that level until the 85th day. Both treatments were well-tolerated. Conclusion:LY01005 is as effective as Zoladex ? in suppressing E2 to menopausal levels in Chinese patients with premenopausal breast cancer, with a similar safety profile.

Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P＜0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P＞0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P＜0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P＜0.05),and there was no significant difference in the SNR(P＞0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P＞0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.

Objective:To establish a stable rat model of sequelae of pelvic inflammatory disease(SPID)with clinical characteristics,and to provide a reliable experimental model for the study of the pharmcological effect and mechanism of SPID.Methods:Twenty-four 7-week-old SD rats were divided into sham operation group,model-A(108 cfu/mL mixed bacterial solution,0.2 mL),model-B(109 cfu/mL mixed bacterial solution 0.2 mL),and model-C(108 cfu/mL E.coli 0.2 mL).The weight of the rat's uterine was weighed and the uterine index was calculated.The automatic hematology analyzer was used to detect the blood routine;hematoxylin-eosin staining(HE)and masson staining were used to detect uterine pathlogical changes in rats.Enzyme-linked immunosorbent assay(ELISA)was used to detect interleukin-1β(IL-1β),interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)in rat uterine tissue homogenates.Western blot was used to detect the expression of proteins related to NF-κB signaling pathway.Results:Compared with the sham operation group,the uterine index of model-A,model-B,and model-C were significantly increased(P＜0.05,P＜0.01).The levels of WBC and NE in the model-A increased significantly(P＜0.01).The level of LY in model-B decreased significantly(P＜0.01).The levels of IL-1β,TNF-α in model-A,model-B,and model-C were significantly increased(P＜0.01).The levels of IL-6 in model-A and model-B were significantly increased(P＜0.05,P＜0.01).The collagen volume fraction of model-A and model-B were significantly increased(P＜0.01).Mechanism study indicates that the expression levels of p-IKKβ/IKKβ,p-IκBα/IκBα and p-p65/p65 in model-A were significantly increased(P＜0.01),and the expression levels of IκBα/β-actin were significantly decreased(P＜0.01).The expression level of p-IKKβ/IKKβ in model-B was significantly increased(P＜0.01).Conclusions:A stable rat model of SPID that conforms to clinical characteristics can be successfully constructed by combining 0.2 mL of mixed bacterial solution with a concentration of 108 cfu/mL and mechanical injury.This modeling method intervened in the expression of the NF-κB inflammatory signaling pathway.