This study explores the effect and mechanism of Banxia Xiexin Decoction(BXD) in inhibiting colon cancer progression by reshaping tryptophan metabolism. Balb/c mice were assigned into control, model, low-dose BXD(BXD-L), and high-dose BXD(BXD-H) groups. Except the control group, the other groups were subcutaneously injected with CT26-Luc cells for the modeling of colon cancer, which was followed by the intervention with BXD. Small animal live imaging was employed to monitor tumor growth, and the tumor volume and weight were measured. Hematoxylin-eosin(HE) staining was used to observe the pathological changes in mouse tumors. Immunohistochemistry was used to detect Ki67 expression in tumors. Immunofluorescence and flow cytometry were used to detect the infiltration and number changes of CD3~+/CD8~+ T cells in the tumor tissue. Enzyme-linked immunosorbent assay(ELISA) was employed to measure the levels of interferon-gamma(IFN-γ) and interleukin-2(IL-2) in tumors. Targeted metabolomics was employed to measure the level of tryptophan(Trp) in the serum, and the Trp content in the tumor tissue was measured. Western blot and RT-qPCR were employed to determine the protein and mRNA levels, respectively, of indoleamine 2,3-dioxygenase 1(IDO1), MYC proto-oncogene, and solute carrier family 7 member 5(SLC7A5) in the tumor tissue. Additionally, a co-culture model with CT26 cells and CD8~+ T cells was established in vitro and treated with the BXD-containing serum. The cell counting kit-8(CCK-8) assay was used to examine the viability of CT26 cells. The content of Trp in CT26 cells and CD8~+ T cells, as well as the secretion of IFN-γ and IL-2 by CD8~+ T cells, was measured. RT-qPCR was used to determine the mRNA levels of MYC and SLC7A5 in CT26 cells. The results showed that BXD significantly inhibited the tumor growth, reduced the tumor weight, and decreased the tumor volume in the model mice. In addition, the model mice showed sparse arrangement of tumor cells, varying degrees of patchy necrosis, and downregulated expression of Ki67 in the tumor tissue. BXD elevated the levels of IFN-γ and IL-2 in the tumor tissue, while upregulating the ratio of CD3~+/CD8~+ T cells and lowering the levels of Trp, IDO1, MYC, and SLC7A5. The co-culture experiment showed that BXD-containing serum reduced Trp uptake by CT26 cells, increased Trp content in CD8~+T cells, enhanced IL-2 and IFN-γ secretion of CD8~+T cells, and down-regulated the mRNA levels of MYC and SLC7A5 in CT26 cells. In summary, BXD can inhibit the MYC/SLC7A5 pathway to reshape Trp metabolism and adjust Trp uptake by CD8~+ T cells to enhance the cytotoxicity, thereby inhibiting the development of colon cancer.
Animals ; Tryptophan/metabolism* ; Colonic Neoplasms/pathology* ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Mice, Inbred BALB C ; Humans ; Cell Line, Tumor ; Indoleamine-Pyrrole 2,3,-Dioxygenase/metabolism* ; Female ; Disease Progression ; Cell Proliferation/drug effects* ; Proto-Oncogene Mas ; Male

Current ambient mass spectrometry ionization often requires external auxiliary equipment such as high-voltage power supply,gas cylinder,and syringe pump.Moreover,the process of sample preparation is cumbersome,and the experimental operations are complex,which makes it difficult to adapt to real-time on-site detection.In this work,a novel method was proposed,in which direct sampling of raw samples,online extraction of interest analytes,and ionization of target molecules were integrated into a single unit.With the developed method,the in-situ extraction and nano-electrospray ionization for both liquid and solid raw samples were achieved.Also,a handheld ion source and its pose adjustment device were developed,and the position and angle parameters were subsequently optimized.The performance of the ionization device was tested using standard solutions of caffeine and reserpine.The limits of detection(LODs)were 0.08 μg/L and 0.14 μg/L,with relative standard deviations(RSDs)≤3.7% and≤5.6%,respectively,indicating that the device possessed high sensitivity and stability.Using this device,three different concentrations of reserpine standard solutions were continuously tested for five days.The intra-day RSDs were consistently≤4.7% and the inter-day RSDs were all≤10.3%,showing the good working stability of the device.Without any pretreatment,a rapid qualitative detection of medicinal components including astragaloside II and cycloastragenol in five traditional Chinese medicines was carried out,with RSDs≤8.0% and≤7.1%,respectively.Additionally,rapid qualitative detection of gallic acid,a medicinal component,in white peony roots,and hypaphorine as well as quercetin in cowherb seeds were carried out,with RSDs≤7.0%,≤6.4% and≤6.1%,respectively.These results demonstrated that the ionization technology and device exhibited good stability during qualitative detection of raw samples.

AIM To study the chemical constituents from Dictamni Cortex.METHODS The 70％ethanol extract from Dictamni Cortex was isolated and purified by HP-20 macroporous resin,silica gel,MCI,ODS and preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Thirty-three compounds were isolated and identified as rutin(1),apigenin(2),catechin(3),hesperetin(4),leonuriside A(5),androsin(6),2-methoxy-4-acetylphenol-O-α-rhamnopyranosyl-(1"-6')-β-glucopyranoside(7),vanillic acid(8),gallic acid(9),4-hydroxybenzoic acid(10),benzoic acid(11),involcranoside B(12),benzyl β-D-glucopyranoside(13),bphenylethyl-rutinoside(14),1-bromonaphthalene(15),cimifugin(16),9(S),12(S),13(S)-trihydroxyoctadeca-10(E),15(Z)-dienoic acid(17),methyl-9,12,13-trihydroxyoctadeca-10,15-dienoate(18),7,8-dihydroxy-9,12(Z,Z)-octadecadienoic acid(19),vernolic acid(20),9,10(erythro)-dihydroxy-11 E-octadecadienoic acid methyl ester(21),(7Z,9E,13Z)-11-hydroxyhexadeca-7,9,13-trienoic acid(22),(7Z,10Z,14E,16Z,19Z)-13-hydroxydocosa-7,10,14,16,19-pentaenoic acid(23),(9E)-8,11,12-trihydroxyoctadecenoic acid methyl ester(24),n-hexanol-O-rutinoside(25),hexyl β-sophoroside(26),3-pentyl 6'-(3-hydroxy-3-methylglutaryl)-β-D-glucopyranoside(27),3-methylbut-3-enyl-6-O-β-D-glucopyranosyl-β-D-glucopyranoside(28),3-methyl-but-2-en-1-yl β-D-glucopyranoside(29),3-methylbutan-1-ol-β-D-glucopyranoside(30),pregnenolone(31),2-butoxytetrahydrofuran(32),psydrin(33).CONCLUSION Compounds 2-4,8-13,15-16,25-28 and 32-33 are isolated from Rutaceae family for the first time.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To investigate the relationship between adiponectin (ADPN), the ratio of high-sensitivity C-reactive protein (hs-CRP) to albumin (ALB), and the progression of acute cerebral infarction (ACI).Methods:This case-control study involved 147 patients with ACI who were treated at Xingyuan Hospital of Yulin between January 2023 and March 2024. The National Institutes of Health Stroke Scale (NIHSS) was used to evaluate disease progression. Based on the progression of the disease, the patients were divided into two groups: the progressive group ( n = 38) and the non-progressive group ( n = 109). ADPN level and the hs-CRP/ALB ratio were compared between the two groups. Additionally, multivariate logistic regression analysis was conducted to identify risk factors for disease progression in ACI patients. The predictive value of ADPN and the hs-CRP/ALB ratio for ACI was assessed using receiver operating characteristic curve analysis. Results:In the progressive group, hs-CRP level and hs-CRP/ALB ratio were (14.38 ± 3.27) mg/L and (0.43 ± 0.13), respectively, both of which were significantly higher than those in the non-progressive group [(8.92 ± 2.73) mg/L, (0.20 ± 0.07), t = 9.22, 10.37, both P < 0.001]. In contrast, the levels of ADPN and albumin in the progressive group were (2.71 ± 0.59) mg/L and (33.54 ± 8.66) g/L, respectively, both of which were significantly lower than those in the non-progressive group [(5.36 ± 1.42) mg/L, (45.05 ± 10.42) g/L, t = -15.99, -6.68, both P < 0.001]. The progressive group had higher admission NIHSS scores, a higher proportion of patients with diabetes, higher white blood cell counts, higher hemoglobin A1c (HbA1c) and fibrinogen levels compared with the non-progressive group ( t = 8.43, 2.88, 5.79, 2.77, χ2 = 4.40, all P < 0.05). Multivariate logistic regression analysis results indicated that higher admission NIHSS scores, HbA1c levels, and hs-CRP/ALB ratios were independent risk factors for disease progression in ACI patients ( OR = 2.438, 1.600, 2.971, all P < 0.05), while higher levels of ADPN were identified as a protective factor against disease progression ( OR = 0.321, P < 0.05). The receiver operating characteristic curve analysis showed that the area under the curve for predicting disease progression after admission for ACI patients using serum ADPN and hs-CRP/ALB ratio alone were 0.730 (95% CI: 0.658-0.800) and 0.758 (95% CI: 0.685-0.826), respectively. The area under the curve for the combined prediction of serum ADPN and the hs-CRP/ALB ratio was 0.895 (95% CI: 0.845-0.940), demonstrating higher predictive efficacy ( Z = 1.80, 2.13, both P < 0.05). Conclusions:ADPN level and hs-CRP/ALB ratio are closely related to the progression of ACI and demonstrate good predictive efficacy for disease progression.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

AIM To study the chemical constituents from Dictamni Cortex.METHODS The 70％ethanol extract from Dictamni Cortex was isolated and purified by HP-20 macroporous resin,silica gel,MCI,ODS and preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Thirty-three compounds were isolated and identified as rutin(1),apigenin(2),catechin(3),hesperetin(4),leonuriside A(5),androsin(6),2-methoxy-4-acetylphenol-O-α-rhamnopyranosyl-(1"-6')-β-glucopyranoside(7),vanillic acid(8),gallic acid(9),4-hydroxybenzoic acid(10),benzoic acid(11),involcranoside B(12),benzyl β-D-glucopyranoside(13),bphenylethyl-rutinoside(14),1-bromonaphthalene(15),cimifugin(16),9(S),12(S),13(S)-trihydroxyoctadeca-10(E),15(Z)-dienoic acid(17),methyl-9,12,13-trihydroxyoctadeca-10,15-dienoate(18),7,8-dihydroxy-9,12(Z,Z)-octadecadienoic acid(19),vernolic acid(20),9,10(erythro)-dihydroxy-11 E-octadecadienoic acid methyl ester(21),(7Z,9E,13Z)-11-hydroxyhexadeca-7,9,13-trienoic acid(22),(7Z,10Z,14E,16Z,19Z)-13-hydroxydocosa-7,10,14,16,19-pentaenoic acid(23),(9E)-8,11,12-trihydroxyoctadecenoic acid methyl ester(24),n-hexanol-O-rutinoside(25),hexyl β-sophoroside(26),3-pentyl 6'-(3-hydroxy-3-methylglutaryl)-β-D-glucopyranoside(27),3-methylbut-3-enyl-6-O-β-D-glucopyranosyl-β-D-glucopyranoside(28),3-methyl-but-2-en-1-yl β-D-glucopyranoside(29),3-methylbutan-1-ol-β-D-glucopyranoside(30),pregnenolone(31),2-butoxytetrahydrofuran(32),psydrin(33).CONCLUSION Compounds 2-4,8-13,15-16,25-28 and 32-33 are isolated from Rutaceae family for the first time.

Objective:To investigate the relationship between adiponectin (ADPN), the ratio of high-sensitivity C-reactive protein (hs-CRP) to albumin (ALB), and the progression of acute cerebral infarction (ACI).Methods:This case-control study involved 147 patients with ACI who were treated at Xingyuan Hospital of Yulin between January 2023 and March 2024. The National Institutes of Health Stroke Scale (NIHSS) was used to evaluate disease progression. Based on the progression of the disease, the patients were divided into two groups: the progressive group ( n = 38) and the non-progressive group ( n = 109). ADPN level and the hs-CRP/ALB ratio were compared between the two groups. Additionally, multivariate logistic regression analysis was conducted to identify risk factors for disease progression in ACI patients. The predictive value of ADPN and the hs-CRP/ALB ratio for ACI was assessed using receiver operating characteristic curve analysis. Results:In the progressive group, hs-CRP level and hs-CRP/ALB ratio were (14.38 ± 3.27) mg/L and (0.43 ± 0.13), respectively, both of which were significantly higher than those in the non-progressive group [(8.92 ± 2.73) mg/L, (0.20 ± 0.07), t = 9.22, 10.37, both P < 0.001]. In contrast, the levels of ADPN and albumin in the progressive group were (2.71 ± 0.59) mg/L and (33.54 ± 8.66) g/L, respectively, both of which were significantly lower than those in the non-progressive group [(5.36 ± 1.42) mg/L, (45.05 ± 10.42) g/L, t = -15.99, -6.68, both P < 0.001]. The progressive group had higher admission NIHSS scores, a higher proportion of patients with diabetes, higher white blood cell counts, higher hemoglobin A1c (HbA1c) and fibrinogen levels compared with the non-progressive group ( t = 8.43, 2.88, 5.79, 2.77, χ2 = 4.40, all P < 0.05). Multivariate logistic regression analysis results indicated that higher admission NIHSS scores, HbA1c levels, and hs-CRP/ALB ratios were independent risk factors for disease progression in ACI patients ( OR = 2.438, 1.600, 2.971, all P < 0.05), while higher levels of ADPN were identified as a protective factor against disease progression ( OR = 0.321, P < 0.05). The receiver operating characteristic curve analysis showed that the area under the curve for predicting disease progression after admission for ACI patients using serum ADPN and hs-CRP/ALB ratio alone were 0.730 (95% CI: 0.658-0.800) and 0.758 (95% CI: 0.685-0.826), respectively. The area under the curve for the combined prediction of serum ADPN and the hs-CRP/ALB ratio was 0.895 (95% CI: 0.845-0.940), demonstrating higher predictive efficacy ( Z = 1.80, 2.13, both P < 0.05). Conclusions:ADPN level and hs-CRP/ALB ratio are closely related to the progression of ACI and demonstrate good predictive efficacy for disease progression.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*