Objective: To investigate the distribution frequency and molecular mechanism of the rare blood type Lu(a-b-) in Shenzhen, and to compare the polymorphisms of the Lutheran blood group system encoding gene LU and the In (Lu) phenotype-related gene KLF1 among Han Chinese, Indian, and Uyghur populations in Xinjiang. Methods: Serological methods were used to screen the Lu(a-b-) phenotype of blood donors in Shenzhen. Third-generation sequencing was employed to sequence the full-length of the LU and KLF1 genes in Lu (a-b-) phenotype samples as well as the samples from the Han Chinese, Indians, and Uyghur population, followed by analysis of gene haplotypes frequencies. Results: Ten individuals with the Lu(a-b-) phenotype were screened out of 14 367 blood donors in Shenzhen, yielding a frequency of approximately 0.07%. Only 2 cases showed mutations in the coding region of the LU gene, while all individuals showed heterozygous mutations in the coding region of the KLF1 gene. The highest mutation frequencies of the LU and KLF1 genes were observed in the Uyghur population in Xinjiang and the Han Chinese in Shenzhen, respectively. Conclusion: All Lu(a-b-) phenotypes are of the In (Lu) type, and their formation mechanism is mainly related to KLF1 gene mutations. Both the LU and KLF1 genes exhibit significant polymorphism in the Han Chinese, Indians, and Uyghur populations.

Objective To study the photodynamic performance and the killing effect of photodynamic therapy on lung cancer of novel chlorin compounds 2-（4-（5,15,20-triphenyl-7H,8H-porphyrin-10-yl） phenoxy） acetic acid（D1）and 4-（4-（5,15,20-triphenyl-7H,8H-porphyrin-10-yl） phenoxy） butanoic acid （D2）. Methods The ultraviolet visible absorption spectrum and fluorescence spectrum of D1 and D2 were determined. The singlet oxygen generation capacity of D1 and D2 was measured by using DPBF as singlet oxygen capture agent. Fluorescence assay was used to detect the cellular phagocytosis rate of the compounds in A549 cells, and MTT assay was used to detect their dark toxicity and phototoxicity. A nude mouse model of lung cancer was established to investigate the antitumor activity of the compounds mediated photodynamic action in vivo, and the blood concentration of D2 in nude mice, its distribution in tumor tissue and skin tissue were further detected. Results D1 and D2 had strong absorption at 652 nm with the best excitation wavelength at 429 nm and 427 nm, and the optimal emission wavelength was at about 659 nm. They also had a higher singlet oxygen generation rate than the control drug m-THPC. D1 and D2 had no dark toxicity at concentrations below 10 μmol/L, and could be ingested by A549 cells, basically reaching saturation in 18~24 hours. After laser irradiation at 650 nm wavelength, D1 and D2 showed significant antitumor activity in vivo and in vitro （P<0.01）. However, D2 could selectively accumulate in tumor tissues after administration, and the optimal treatment time was less than 30 min after administration. Conclusion D2 had excellent photodynamic antitumor activity and could selectively aggregate in tumor tissues, which had the potential to be a candidate drug for photosensitizer and treatment of lung cancer with independent intellectual property rights, and was worth further research.

ObjectiveTo investigate the value of predictive models established based on machine learning methods in predicting the risk of metabolic associated fatty liver disease （MAFLD）， and to analyze its key risk factors. MethodsA retrospective analysis was performed for the 50 variables of 2 168 healthy individuals who underwent physical examination in Department of Health Assessment， Xiyuan Hospital， China Academy of Chinese Medical Sciences， from January 2021 to December 2024， including body composition， past history， and laboratory tests， and according to whether they were diagnosed with MAFLD or not， they were divided into MAFLD group with 265 individuals and non-MAFLD group with 1 903 individuals. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Randomly split the research data into a training set and a validation set in a 70% to 30% ratio. Predictive factors were screened from the training set data using univariate analysis， LASSO regression， and multivariate Logistic regression analysis. Predictive models were then constructed using seven machine learning methods： Logistic regression， decision tree， random forest （RF）， eXtreme gradient boosting， light gradient boosting machine， support vector machine， and artificial neural network. Model performance was evaluated by plotting receiver operating characteristic curve for the validation set and calculating the area under the curve （AUC）， sensitivity， specificity， and Youden index for each model. Furthermore， the SHapley Additive exPlanation （SHAP） method was used to analyze the contribution of variables in the optimal model. ResultsThe prevalence rate of MAFLD among the 2 168 subjects was 12.22% （265/2 168）. Smoking， diastolic blood pressure， phase angle， visceral fat area， muscle fat ratio， waist-to-hip ratio， aspartate aminotransferase， non-HDL-C/HDL-C ratio， triglyceride-glucose index， and gallstones were independent risk factors for MAFLD （all P<0.05）. The seven predictive models of support vector machine， eXtreme gradient boosting， decision tree， light gradient boosting machine， artificial neural network， RF， and Logistic regression had an AUC of 0.738， 0.754， 0.757， 0.786， 0.795， 0.796， and 0.815， respectively， in the validation set， among which the RF model had the best discriminatory ability （AUC=0.796， 95% confidence interval： 0.754 — 0.839）， with a sensitivity of 81.01%， a specificity of 63.16%， and a Youden index of 44.17%. The SHAP analysis showed that visceral fat area， waist-to-hip ratio， and diastolic blood pressure were the top three predictive factors in terms of importance. ConclusionThe RF model， constructed based on body composition and clinical indicators， has a good performance in predicting the risk of MAFLD， and its interpretability can help to identify high-risk individuals in the early stage in clinical practice.

Objective: To investigate the distribution characteristics of Kidd blood group antigens, phenotypes and genotypes in Xinjiang and their influence on the risk of coronary heart disease. Methods: Samples from 7 981 patients treated at People's Hospital of Xinjiang Uygur Autonomous Region from August 1, 2023 to May 31, 2024 were collected for Jk(a-b-) phenotype screening via urea hemolysis test, followed by the third-generation sequencing (TGS). Kidd blood group Jk and Jk antigens in 1 081 patients with coronary heart disease and 1 021 healthy people were detected, and their phenotype frequency distribution was analyzed and corresponding gene frequencies were calculated. Correlation analysis and logistic regression were used to evaluate the influence of Kidd blood group antigen expression on coronary heart disease risk. Results: Two Jk(a-b-) phenotype samples were detected, both resulting from novel gene mutation combinations. Comparative analysis of two groups revealed a higher proportion of the Jk(a-b+) phenotype in the case group (22.5%, 243/1 081) than in the control group (18.5%, 189/1 021). Moreover, Kidd blood group phenotype distribution varied significantly across all ethnic groups in the case group (P<0.05). In the control group, the Hui ethnic group exhibited the highest JK JK genotype frequency 64.15% (34/53). In the case group, the highest JK allele frequency was observed in Mongol ethnic group 56.31% (125/222), and the lowest in Han patients 45.71% (341/746). The expression of Jk antigen was negatively correlated with coronary heart disease (P<0.05). Conclusion: The distribution of Kidd blood group system varied across ethnic groups in Xinjiang. The expression of Jk antigen may have protective effect on coronary heart disease, which provides a basis for future clinical blood transfusion treatment and the mechanism study of the correlation between Kidd blood group and coronary heart disease.

Objective: To evaluate the suitability of the existing hemolysis rate standards for locally processed red blood cell components by retrospectively analyzing 5-year hemolysis rate data at the end of storage. Methods: A total of 720 blood samples of three types of red blood cell components from our blood station from January 2019 to December 2023 were collected. Parameters included hemoglobin concentration (Hb), hematocrit (Hct), and free hemoglobin concentration (fHb). Hemolysis rate were taken as the control standard of 0.8% in accordance with the national standard. The hemolysis rates were compared against the national standard threshold of 0.8% (GB18469-2012), and annual trends of the detection parameters were observed. Results: The hemolysis rates (x-+s,%) of leukocyte-depleted whole blood at the end of storage were (0.038±0.023 8) in 2019, (0.049±0.039 5) in 2020, (0.043±0.040 7) in 2021, (0.049±0.030 7) in 2022, and (0.058±0.054 8) in 2023, respectively; The hemolysis rates (x-+s" />,%) of leukocyte-depleted suspended red blood cells at the end of storage were (0.093±0.050 2) in 2019, (0.086±0.049 5) in 2020, (0.123±0.072 3) in 2021, (0.122±0.052 1) in 2022, and (0.106±0.058 6) in 2023, respectively; The hemolysis rates (x-+s,%) of washed red blood cells at the end of storage were (0.127±0.038 2) in 2019, (0.150±0.066 5) in 2020, (0.121±0.052 2) in 2021, (0.124±0.038 9) in 2022, and (0.128±0.044 3) in 2023, respectively. Conclusion: Hemolysis rates at the end of blood storage of three red blood cell components were significantly lower than the limits specified in Quality Requirements for Whole Blood and Components (GB18469-2012), as well as standards from the EU, AABB and the United States. The results demonstrate excellent product quality control. A regional internal control standard of <0.2% is proposed for hemolysis rates at the end of storage.

Objective To explore the value of oral contrast-enhanced ultrasonography (OCEUS) combined with contrast-enhanced CT in predicting preoperative T staging in patients with gastric cancer. Methods A retrospective analysis was conducted on 80 patients with gastric cancer confirmed via endoscopic biopsy or postoperative pathology at the First People’s Hospital of Jining from January 2021 to November 2024. The cohort included 56 males and 24 females, aged 38-79 years, with a median age of 55.9 years. All patients underwent both OCEUS and contrast-enhanced CT within one week prior to surgery. T staging of gastric cancer was determined using OCEUS, contrast-enhanced CT, or their combination. The results were compared with pathological T staging, and statistical differences in accuracy were analyzed. Results Pathological T staging identified T1 in 9 cases, T2 in 16 cases, T3 in 42 cases, and T4 in 13 cases. OCEUS indicated T1 in 6 cases, T2 in 14 cases, T3 in 50 cases, and T4 in 10 cases, with an accuracy rate of 80.0%. Contrast-enhanced CT indicated T1 in 4 cases, T2 in 12 cases, T3 in 52 cases, and T4 in 12 cases, with an accuracy rate of 75.0%. The combination of OCEUS and contrast-enhanced CT indicated T1 in 6 cases, T2 in 15 cases, T3 in 47 cases, and T4 in 12 cases, with an accuracy rate of 87.5%. The combined approach demonstrated significantly higher accuracy in preoperative T staging compared to either method alone (P < 0.05). Conclusion The combination of OCEUS and contrast-enhanced CT improves the accuracy of preoperative T staging in gastric cancer patients, providing valuable support for their diagnosis and treatment.

ObjectiveTo investigate the triglyceride-glucose (TyG) index and the level of serum homocysteine (Hcy) in association with the incidence of stroke in type 2 diabetes mellitus (T2DM) patients. MethodsBased on the chronic disease risk factor surveillance cohort in Pudong New Area, Shanghai, excluding those with stroke in baseline survey, T2DM patients who joined the cohort from January 2016 to October 2020 were selected as the research subjects. During the follow-up period, a total of 318 new-onset ischemic stroke patients were selected as the case group, and a total of 318 individuals matched by gender without stroke were selected as the control group. The Cox proportional hazards regression model was used to adjust for confounding factors and explore the serum TyG index and the Hcy biochemical indicator in association with the risk of stroke. ResultsThe Cox proportional hazards regression results showed that after adjusting for confounding factors, the risk of stroke in T2DM patients with 10 μmol·L⁻¹-¹ and Hcy>15 μmol·L⁻¹ was 1.532 times (95%CI: 1.017‒2.309 times, P=0.041) and 1.738 times (95%CI: 1.119‒2.699 times, P=0.014) higher respectively, compared to T2DM patients with Hcy≤10 μmol·L⁻¹. T2DM patients with TyG>9.074 had 1.396 times higher risk of stroke (95%CI: 1.091‒1.787, P=0.008) compared to those with TyG≤9.074. The study found that urea and α1-antitrypsin (α1-AT) were independent risk factors for the incidence of stroke in T2DM patients. For every unit increase in urea andα1-AT, the risk of stroke in T2DM patients increased by 233.6% (HR=3.336, 95%CI: 1.588‒7.009, P=0.001) and 11.3% (HR=1.113, 95%CI: 1.028‒1.205, P=0.008), respectively. Cumulative risk curves showed that Hcy>10 μmol·L⁻¹ and TyG>9.074 accelerated the time to stroke occurrence in T2DM patients. ConclusionElevated levels of Hcy>10 μmol·L⁻¹ and a higher TyG index are risk factors for stroke in T2DM patients. Effective interventions for Hcy and TyG should be conducted for diabetic patients to reduce the incidence of stroke.

Dormant tumor cells constitute a population of cancer cells that reside in a non-proliferative or low-proliferative state, typically arrested in the G0/G1 phase and exhibiting minimal mitotic activity. These cells are commonly observed across multiple cancer types, including breast, lung, and ovarian cancers, and represent a central cellular component of minimal residual disease (MRD) following surgical resection of the primary tumor. Dormant cells are closely associated with long-term clinical latency and late-stage relapse. Due to their quiescent nature, dormant cells are intrinsically resistant to conventional therapies—such as chemotherapy and radiotherapy—that preferentially target rapidly dividing cells. In addition, they display enhanced anti-apoptotic capacity and immune evasion, rendering them particularly difficult to eradicate. More critically, in response to microenvironmental changes or activation of specific signaling pathways, dormant cells can re-enter the cell cycle and initiate metastatic outgrowth or tumor recurrence. This ability to escape dormancy underscores their clinical threat and positions their effective detection and elimination as a major challenge in contemporary cancer treatment. Hypoxia, a hallmark of the solid tumor microenvironment, has been widely recognized as a potent inducer of tumor cell dormancy. However, the molecular mechanisms by which tumor cells sense and respond to hypoxic stress—initiating the transition into dormancy—remain poorly defined. In particular, the lack of a systems-level understanding of the dynamic and multifactorial regulatory landscape has impeded the identification of actionable targets and constrained the development of effective therapeutic strategies. Accumulating evidence indicates that hypoxia-induced dormancy tumor cells are accompanied by a suite of adaptive phenotypes, including cell cycle arrest, global suppression of protein synthesis, metabolic reprogramming, autophagy activation, resistance to apoptosis, immune evasion, and therapy tolerance. These changes are orchestrated by multiple converging signaling pathways—such as PI3K-AKT-mTOR, Ras-Raf-MEK-ERK, and AMPK—that together constitute a highly dynamic and interconnected regulatory network. While individual pathways have been studied in depth, most investigations remain reductionist and fail to capture the temporal progression and network-level coordination underlying dormancy transitions. Systems biology offers a powerful framework to address this complexity. By integrating high-throughput multi-omics data—such as transcriptomics and proteomics—researchers can reconstruct global regulatory networks encompassing the key signaling axes involved in dormancy regulation. These networks facilitate the identification of core regulatory modules and elucidate functional interactions among key effectors. When combined with dynamic modeling approaches—such as ordinary differential equations—these frameworks enable the simulation of temporal behaviors of critical signaling nodes, including phosphorylated AMPK (p-AMPK), phosphorylated S6 (p-S6), and the p38/ERK activity ratio, providing insights into how their dynamic changes govern transitions between proliferation and dormancy. Beyond mapping trajectories from proliferation to dormancy and from shallow to deep dormancy, such dynamic regulatory models support topological analyses to identify central hubs and molecular switches. Key factors—such as NR2F1, mTORC1, ULK1, HIF-1α, and DYRK1A—have emerged as pivotal nodes within these networks and represent promising therapeutic targets. Constructing an integrative, systems-level regulatory framework—anchored in multi-pathway coordination, omics-layer integration, and dynamic modeling—is thus essential for decoding the architecture and progression of tumor dormancy. Such a framework not only advances mechanistic understanding but also lays the foundation for precision therapies targeting dormant tumor cells during the MRD phase, addressing a critical unmet need in cancer management.

AIM To establish an HPLC-MS/MS method for the simultaneous content determination of gallic acid,protocatechuic acid,oxypaeoniflorin,catechin,epicatechin,albiflorin,paeoniflorin,rutin,calycosin-7-glucoside,syringaldehyde,ferulic acid,coumarin,ononin,calycosin,cinnamic alcohol,cinnamic acid,benzoylpaeoniflorin,cinnamaldehyde,astragaloside,astragaloside Ⅲ,6-gingerol in Huangqi Guizhi Wuwu Decoction.METHODS The analysis was performed on a 30 ℃ thermostatic Thermo Scientific Hypersil GOLD column(150 mmx4.6 mm,3 μm),with the mobile phase comprising of 0.015％formic acid-acetonitrile flowing at 0.4 mL/min in a gradient elution manner,and electrospray ionization source was adopted in positive and negative ion modes with multiple reaction monitoring.RESULTS Twenty-one constituents showed good linear relationships within their own ranges(r＞0.990 5),whose average recoveries were 93.99％-108.52％with the RSDs of 1.04％-5.97％.CONCLUSION This simple,feasible,stable and reliable method can be used for the quality control of Huangqi Guizhi Wuwu Decoction.