Background Methicillin-resistant Staphylococcus aureus (MRSA) is an important pathogen for both human bloodstream infections and mastitis in cows. However, little attention has been paid to the cross-host transmission of MRSA from cows to high-risk groups in China. Objective To determine the MRSA colonization rates among dairy cows and dairy farm workers in Xinjiang, identify the antibiotic resistance profiles and molecular characteristics of the isolates, and provide scientific evidence for the formulation of targeted infection control strategies. Method A cross-sectional survey combined with laboratory pathogen analysis was conducted. From June to August 2024, large-scale dairy farms in Xinjiang region were selected as study sites. Nasal swabs (n=96) and skin swabs (n=39) were collected from workers, and bovine nasal swab samples (n=109) were collected simultaneously. All samples were subjected to MRSA isolation, cultivation, and identification, followed by antibiotic susceptibility testing to characterize resistance phenotypes. Staphylococcus aureus protein A (Spa) typing was performed to determine strain genotypes and elucidate MRSA colonization rates and molecular epidemiological patterns. Results A total of 35 MRSA strains was successfully isolated from 244 samples. The MRSA colonization rates among dairy farm workers and dairy cows were 20.83% (20/96) and 12.84% (14/109), respectively, with an overall isolation rate of 14.34% (35/244). Among the workers, the nasal colonization rate was 16.67% (16/96), and the skin colonization rate was 12.82% (5/39). One worker exhibited MRSA colonization at multiple body sites. All MRSA strains were resistant to cefoxitin (100%, 35/35). The resistance rates to erythromycin and clindamycin were 42.86% (15/35) and 34.29% (12/35), respectively. Thirteen strains showed a multidrug-resistant phenotype, whereas all strains were susceptible to vancomycin. The MRSA isolates exhibited high genetic diversity, with 13 Spa types identified, among which t441 was the most prevalent (8 strains). Both t441 and t034 types were detected in samples from both the dairy cows and their handlers. These two Spa types also carried and stably inherited specific resistance combinations, including erythromycin–clindamycin–cefoxitin and ciprofloxacin–erythromycin–clindamycin–gentamicin–cefoxitin–tetracycline, and a statistically significant association was also observed between the two resistance profiles and the bacterial types (P < 0.001). In addition, one novel Spa type strain was identified. Conclusion MRSA colonization rates among dairy cows and dairy farm workers in Xinjiang are relatively high, with evidence of multi-site colonization. The isolates exhibit high levels of multidrug resistance and genetic diversity, indicating a potential risk of cross-host transmission.

Background Under intensive dairy farming conditions, Enterococcus spp. can be transmitted between animals, farm workers, and the environment via multiple vectors such as feces, soil, water, air, and farming equipment, posing a potential threat to public health. Objective To elucidate the prevalence, distribution, and antimicrobial resistance profiles of Enterococcus faecalis (E. faecalis) and Enterococcus faecium (E. faecium) among farm workers, dairy cattle, and the farm environment in Xinjiang, and to assess the risk of their cross-host transmission. Methods From May 2024 to January 2025, a total of 317 samples were collected from 11 large-scale dairy farms in Xinjiang, China, including feces from farm workers (n=130) and dairy cattle (n=154), and environmental samples (n=33). E. faecalis and E. faecium were isolated and identified, followed by antimicrobial susceptibility testing and multilocus sequence typing (MLST) to analyze their molecular characteristics. Results A total of 183 Enterococcus isolates were obtained (66 E. faecalis and 117 E. faecium isolated). The isolation rates of both species showed statistically significant differences among the three sources (χ²=29.21, P=0.003). Antimicrobial resistance analysis revealed that E. faecalis generally exhibited higher resistance rates across multiple antibiotic classes than E. faecium. High resistance to rifampicin was observed across all sources (50.00%–81.25%), with statistical variation among origins (χ²=8.03, P=0.024). Multidrug-resistant strains accounted for 69.10% of the isolates. Multidrug resistance patterns in E. faecium varied significantly by source (χ²=27.19, P=0.014), and one isolate displayed resistance to eight antibiotic classes. MLST indicated high genetic diversity; E. faecalis was dominated by ST472 and ST227 of which the distrubution was significantly different among sources, while E. faecium primarily clustered into clonal complexes CC94 (centered on ST94) and CC17 (centered on ST22). Conclusion Resistant Enterococcus strains exhibit cross-transmission among farm workers, animals, and the environment. Under the "One Health" framework, standardized farming protocols and prudent antimicrobial use are essential to disrupt the transmission chain of resistant clones and mitigate the spread of antimicrobial resistance at its source.

Background Under intensive dairy farming conditions, Enterococcus spp. can be transmitted between animals, farm workers, and the environment via multiple vectors such as feces, soil, water, air, and farming equipment, posing a potential threat to public health. Objective To elucidate the prevalence, distribution, and antimicrobial resistance profiles of Enterococcus faecalis (E. faecalis) and Enterococcus faecium (E. faecium) among farm workers, dairy cattle, and the farm environment in Xinjiang, and to assess the risk of their cross-host transmission. Methods From May 2024 to January 2025, a total of 317 samples were collected from 11 large-scale dairy farms in Xinjiang, China, including feces from farm workers (n=130) and dairy cattle (n=154), and environmental samples (n=33). E. faecalis and E. faecium were isolated and identified, followed by antimicrobial susceptibility testing and multilocus sequence typing (MLST) to analyze their molecular characteristics. Results A total of 183 Enterococcus isolates were obtained (66 E. faecalis and 117 E. faecium isolated). The isolation rates of both species showed statistically significant differences among the three sources (χ²=29.21, P=0.003). Antimicrobial resistance analysis revealed that E. faecalis generally exhibited higher resistance rates across multiple antibiotic classes than E. faecium. High resistance to rifampicin was observed across all sources (50.00%–81.25%), with statistical variation among origins (χ²=8.03, P=0.024). Multidrug-resistant strains accounted for 69.10% of the isolates. Multidrug resistance patterns in E. faecium varied significantly by source (χ²=27.19, P=0.014), and one isolate displayed resistance to eight antibiotic classes. MLST indicated high genetic diversity; E. faecalis was dominated by ST472 and ST227 of which the distrubution was significantly different among sources, while E. faecium primarily clustered into clonal complexes CC94 (centered on ST94) and CC17 (centered on ST22). Conclusion Resistant Enterococcus strains exhibit cross-transmission among farm workers, animals, and the environment. Under the "One Health" framework, standardized farming protocols and prudent antimicrobial use are essential to disrupt the transmission chain of resistant clones and mitigate the spread of antimicrobial resistance at its source.

ObjectiveTo investigate the therapeutic effect of paeoniflorin on metabolic dysfunction-associated fatty liver disease （MASLD） combined with insulin resistance （IR）， and to elucidate its regulatory mechanisms on the Toll-like receptor 4 （TLR4）/nuclear transcription factor （NF）-κB-insulin receptor substrate 1 （IRS1） inflammation-insulin signaling axis. MethodsMASLD mouse model was established using a 60% high-fat diet. Mice were randomly assigned to a normal control group， a MASLD model group， and paeoniflorin groups （low dose： 25 mg·kg^-1·d^-1， medium dose： 50 mg·kg^-1·d^-1， high dose： 100 mg·kg^-1·d^-1）， receiving intragastric administration for consecutive 12 weeks. Concurrently， a palmitic acid/oleic acid （PA/OA）-induced lipid deposition model was established in HepG2 cells. Cell counting kit-8 （CCK-8） assay was performed to determine the optimal concentrations of PA/OA and paeoniflorin for intervention. Mice body weight， liver index， and serum levels of alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， triglycerides （TG）， and total cholesterol （TC） were measured. Fasting blood glucose （FBG） and fasting insulin （FINS） levels were measured， and the homeostatic model assessment of insulin resistance （HOMA-IR） was calculated， while an oral glucose tolerance test （OGTT） was performed to evaluate glucose metabolism. Hematoxylin and eosin （HE） staining was used to observe pathological changes and inflammatory cell infiltration in liver tissue， and oil red O staining was used to evaluate lipid droplet deposition in liver tissue and HepG2 cells. Potential targets were screened using network pharmacology and molecular docking. Western blot analysis was performed to detect the expression of HSP90AA1， TLR4， p-NF-κB p65， p-IRS1， and p-Akt proteins in liver tissue and HepG2 cells. ResultsCompared with the normal control group， mice in the MASLD model group exhibited significantly increased body weight， liver index， and serum levels of ALT， AST， TG， and TC， as well as markedly elevated FBG， FINS， and HOMA-IR， and impaired glucose tolerance （P<0.01）. HE staining revealed marked hepatic steatosis and inflammatory cell infiltration， while oil red O staining showed a significant increase in lipid droplet deposition. Compared with the MASLD model group， after intervention with various doses of paeoniflorin， the increase in body weight and liver index was reduced， serum ALT， AST， TG， and TC levels decreased， and FBG， FINS， and HOMA-IR were significantly lowered， with glucose tolerance markedly improved （P<0.05， P<0.01）， showing a certain dose-dependent trend. HE and oil red O staining results showed a marked reduction in hepatic steatosis and lipid deposition. In vitro experiments demonstrated that， compared with the control group， PA/OA treatment significantly induced increased lipid deposition in HepG2 cells. Compared with the model group， paeoniflorin intervention significantly reduced intracellular lipid droplets， and lipid deposition showed a dose-dependent decreasing trend. Mechanism studies indicated that， compared with the normal control group， the MASLD model group exhibited significantly elevated expression of TLR4， HSP90AA1， and p-NF-κB p65， while p-IRS1 （Ser307） expression was elevated and p-Akt （Ser473） expression was reduced （P<0.01）. Compared with the model group， the expression of the aforementioned proteins was significantly reversed in all treatment groups following intervention （P<0.05， P<0.01）. ConclusionPaeoniflorin significantly alleviates lipid deposition and insulin resistance in MASLD mice. Its mechanism of action may involve targeting HSP90AA1， TLR4， and NF-κB1 to regulate the TLR4/NF-κB-IRS1 inflammation-insulin signaling axis. This regulation suppresses inflammatory responses and restores insulin signaling， thereby ameliorating abnormalities in glucose and lipid metabolism.

ObjectiveThis study aimed to investigate whether dexmedetomidine （Dex） alleviates stress-induced mammary tumor progression in mice by inhibiting the TLR4/NF‑κB signaling pathway， and to examine its effects on anxiety‑depression‑like behaviors and stress hormone levels. MethodsAn orthotopic EMT6 mammary tumor model was established in mice， and chronic mild stress （CMS） was applied to induce anxiety‑depression‑like states. The mice were divided into six groups： naive， tumor， CMS， CMS+tumor， CMS+tumor+Dex， and CMS+tumor+Vehicle groups. Behavioral changes were evaluated using the open field test and tail suspension test. Plasma stress hormone levels were measured by high‑performance liquid chromatography. Western blot and RT‑qPCR were performed to detect the expression of TLR4， p‑NF‑κB p65， p‑IκBα， and inflammatory cytokines （IL‑6， IL‑1β， TNF‑α） in tumor tissues. In vitro， EMT6 cells were treated with cortisol to mimic the stress-related microenvironment， and the effects of Dex on the TLR4/NF‑κB pathway were assessed by CCK‑8， Western blot， and RT-qPCR. ResultsTumor‑bearing mice exhibited significant anxiety‑depression‑like behaviors （P＜0.05）， along with markedly elevated plasma levels of norepinephrine， epinephrine， and cortisol （P＜0.05）. Chronic stress further aggravated these behavioral abnormalities and promoted tumor growth （P＜0.05）. Dexmedetomidine intervention significantly improved anxiety‑depression‑like behaviors （P＜0.05） and lowered peripheral stress hormone levels （P＜0.05） in stress‑exposed tumor‑bearing mice. In vitro experiments demonstrated that cortisol treatment activated the TLR4/NF‑κB pathway （P＜0.001） and upregulated the expression of inflammatory cytokines （P＜0.05 in EMT6 cells， whereas dexmedetomidine effectively suppressed this activation （P＜0.001）. In the in vivo model， dexmedetomidine treatment downregulated the expression of TLR4， p‑NF‑κB p65， p‑IκBα， and pro‑inflammatory cytokines in tumor tissues （P＜0.001） and significantly inhibited tumor growth （P＜0.05）. ConclusionDexmedetomidine inhibits the TLR4/NF‑κB signaling pathway， alleviates stress‑induced inflammatory responses， improves anxiety- and depression‑ like behaviors， reduces stress hormone levels， and suppresses mammary tumor progression. These findings provide an experimental basis for understanding anxiety- and depression- associated breast tumor progression and suggest that Dexmedetomidine and the TLR4/NF-κB pathway may serve as potential therapeutic targets.

ObjectiveTo investigate the therapeutic effect of paeoniflorin on metabolic dysfunction-associated fatty liver disease （MASLD） combined with insulin resistance （IR）， and to elucidate its regulatory mechanisms on the Toll-like receptor 4 （TLR4）/nuclear transcription factor （NF）-κB-insulin receptor substrate 1 （IRS1） inflammation-insulin signaling axis. MethodsMASLD mouse model was established using a 60% high-fat diet. Mice were randomly assigned to a normal control group， a MASLD model group， and paeoniflorin groups （low dose： 25 mg·kg^-1·d^-1， medium dose： 50 mg·kg^-1·d^-1， high dose： 100 mg·kg^-1·d^-1）， receiving intragastric administration for consecutive 12 weeks. Concurrently， a palmitic acid/oleic acid （PA/OA）-induced lipid deposition model was established in HepG2 cells. Cell counting kit-8 （CCK-8） assay was performed to determine the optimal concentrations of PA/OA and paeoniflorin for intervention. Mice body weight， liver index， and serum levels of alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， triglycerides （TG）， and total cholesterol （TC） were measured. Fasting blood glucose （FBG） and fasting insulin （FINS） levels were measured， and the homeostatic model assessment of insulin resistance （HOMA-IR） was calculated， while an oral glucose tolerance test （OGTT） was performed to evaluate glucose metabolism. Hematoxylin and eosin （HE） staining was used to observe pathological changes and inflammatory cell infiltration in liver tissue， and oil red O staining was used to evaluate lipid droplet deposition in liver tissue and HepG2 cells. Potential targets were screened using network pharmacology and molecular docking. Western blot analysis was performed to detect the expression of HSP90AA1， TLR4， p-NF-κB p65， p-IRS1， and p-Akt proteins in liver tissue and HepG2 cells. ResultsCompared with the normal control group， mice in the MASLD model group exhibited significantly increased body weight， liver index， and serum levels of ALT， AST， TG， and TC， as well as markedly elevated FBG， FINS， and HOMA-IR， and impaired glucose tolerance （P<0.01）. HE staining revealed marked hepatic steatosis and inflammatory cell infiltration， while oil red O staining showed a significant increase in lipid droplet deposition. Compared with the MASLD model group， after intervention with various doses of paeoniflorin， the increase in body weight and liver index was reduced， serum ALT， AST， TG， and TC levels decreased， and FBG， FINS， and HOMA-IR were significantly lowered， with glucose tolerance markedly improved （P<0.05， P<0.01）， showing a certain dose-dependent trend. HE and oil red O staining results showed a marked reduction in hepatic steatosis and lipid deposition. In vitro experiments demonstrated that， compared with the control group， PA/OA treatment significantly induced increased lipid deposition in HepG2 cells. Compared with the model group， paeoniflorin intervention significantly reduced intracellular lipid droplets， and lipid deposition showed a dose-dependent decreasing trend. Mechanism studies indicated that， compared with the normal control group， the MASLD model group exhibited significantly elevated expression of TLR4， HSP90AA1， and p-NF-κB p65， while p-IRS1 （Ser307） expression was elevated and p-Akt （Ser473） expression was reduced （P<0.01）. Compared with the model group， the expression of the aforementioned proteins was significantly reversed in all treatment groups following intervention （P<0.05， P<0.01）. ConclusionPaeoniflorin significantly alleviates lipid deposition and insulin resistance in MASLD mice. Its mechanism of action may involve targeting HSP90AA1， TLR4， and NF-κB1 to regulate the TLR4/NF-κB-IRS1 inflammation-insulin signaling axis. This regulation suppresses inflammatory responses and restores insulin signaling， thereby ameliorating abnormalities in glucose and lipid metabolism.

ObjectiveTo establish a rapid analytical method for identifying the differential components in Poria cocos medicinal materials based on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， combined with mass defect filtering（MDF） and molecular network integration techniques. MethodsUPLC-Q-Orbitrap-MS was used for MS data acquisition and identification of P. cocos medicinal materials， with the help of MDF for the study of cleavage behavior and structural identification of triterpenoids. According to the similarity of MS/MS fragmentation patterns of each component， global natural product social molecular network（GNPS） was established， and Cytoscape 3.6.1 was used to screen molecular clusters with similar structures and the the structure of main compound classes were identified and confirmed. Multivariate statistical analyses such as principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were used to screen the differential components of the five P. cocos medicinal materials with the variable importance in the projection（VIP） value>1 and P<0.05 as the criteria. ResultsA total of 66 compounds were identified by database comparison， 8 compounds were newly identified by MDF， 28 compounds were newly identified by GNPS， and a total of 102 chemical compounds were identified， including 43 triterpenoids， 16 saccharides， 26 amino acids and peptides， 3 nucleosides， and 14 other compounds. Triterpenoids were predominant in Poriae Cutis and wild Fushen， amino acids and peptides were the most abundant in Poria and cultivated Fushen， carbohydrates were the most abundant in Poriae Cutis. Type Ⅰ and Ⅱ triterpenoids had higher amounts in Poria and cultivated Fushen， type Ⅲ triterpenoids were more abundant in Poriae Cutis， all four types of triterpenoids were higher in Fushenmu， and type Ⅰ， Ⅱ， and Ⅳ triterpenoids were higher in wild Fushen. A total of 12 common differential chemical constituents were screened， including serine， guanosine， gallic acid， 2-octenal， maltotriose， trametenolic acid， dehydroeburicoic acid， dehydrotrametenolic acid， poricoic acid A， poricoic acid B， poricoic acid E and G， but the relative contents of them varied significantly among different medicinal materials. ConclusionAmong the five P. cocos medicinal materials， the types of constituents are generally similar， but their relative contents differed significantly among these medicinal materials， especially in the distribution of triterpenoids. The integration of UPLC-Q-Orbitrap-MS， MDF and GNPS can provide a reference for the rapid qualitative analysis of other Chinese medicines.

ObjectiveTo establish a rapid analytical method for identifying the differential components in Poria cocos medicinal materials based on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， combined with mass defect filtering（MDF） and molecular network integration techniques. MethodsUPLC-Q-Orbitrap-MS was used for MS data acquisition and identification of P. cocos medicinal materials， with the help of MDF for the study of cleavage behavior and structural identification of triterpenoids. According to the similarity of MS/MS fragmentation patterns of each component， global natural product social molecular network（GNPS） was established， and Cytoscape 3.6.1 was used to screen molecular clusters with similar structures and the the structure of main compound classes were identified and confirmed. Multivariate statistical analyses such as principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were used to screen the differential components of the five P. cocos medicinal materials with the variable importance in the projection（VIP） value>1 and P<0.05 as the criteria. ResultsA total of 66 compounds were identified by database comparison， 8 compounds were newly identified by MDF， 28 compounds were newly identified by GNPS， and a total of 102 chemical compounds were identified， including 43 triterpenoids， 16 saccharides， 26 amino acids and peptides， 3 nucleosides， and 14 other compounds. Triterpenoids were predominant in Poriae Cutis and wild Fushen， amino acids and peptides were the most abundant in Poria and cultivated Fushen， carbohydrates were the most abundant in Poriae Cutis. Type Ⅰ and Ⅱ triterpenoids had higher amounts in Poria and cultivated Fushen， type Ⅲ triterpenoids were more abundant in Poriae Cutis， all four types of triterpenoids were higher in Fushenmu， and type Ⅰ， Ⅱ， and Ⅳ triterpenoids were higher in wild Fushen. A total of 12 common differential chemical constituents were screened， including serine， guanosine， gallic acid， 2-octenal， maltotriose， trametenolic acid， dehydroeburicoic acid， dehydrotrametenolic acid， poricoic acid A， poricoic acid B， poricoic acid E and G， but the relative contents of them varied significantly among different medicinal materials. ConclusionAmong the five P. cocos medicinal materials， the types of constituents are generally similar， but their relative contents differed significantly among these medicinal materials， especially in the distribution of triterpenoids. The integration of UPLC-Q-Orbitrap-MS， MDF and GNPS can provide a reference for the rapid qualitative analysis of other Chinese medicines.

Background Animal farming may affect the structure and diversity of gut microbiota of farm workers, but it needs more studies to provide solid evidence. Objective To analyze the diversity characteristics of gut microbiota in dairy farm workers, dairy cows, and the control population (non-animal contact occupational group), and to assess the impact of dairy farming on the gut microbiota of workers. Methods The 16S rRNA full-length amplicon sequencing technology was used to sequence 60 fecal samples from dairy farm workers, 89 from dairy cows, and 50 from the general population. The gut microbiota structure characteristics, including operational taxonomic units (OTUs), alpha diversity, beta diversity, and the composition of species at the phylum, family, and genus levels were analyzed. The differences in gut microbiota among the three groups of samples were compared to explore the impact of occupational exposure on the gut microbiota structure of dairy farm workers. Results A total of 50478 OTUs were identified in the gut microbiota of farm workers, dairy cows, and the general population, with 23613, 42723, and 16592 OTUs, respectively. The number of shared OTUs between the dairy cows and the general population was 12674 (27.17%), between the general population and the farm workers was 10099 (33.54%), and between the dairy cows and the farm workers was 17690 (36.36%). Compared with the general population, the farm workers and dairy cows showed more shared gut microbiota (P<0.01). The abundance of Firmicutes in the gut of the farm workers was higher than that of the general population (P<0.01), while Actinobacteriota and Proteobacteria were the opposite (P<0.01). The alpha diversity of gut microbiota in the farm workers was different from that of the general population. The ACE index of the farm workers was slightly lower than that of the general population and much lower than that of dairy cows (P<0.05), while their Shannon index was higher than that of the general population but lower than that of dairy cows (P<0.01). The linear discriminant analysis effect size (LefSe) showed that the abundances of Lachnospiraceae and Ruminococcaceae in the gut microbiota of the farm workers were significantly higher than those of the general population, while Streptococcaceae, Lactobacillaceae, Bifidobacteriaceae, Enterobacteriaceae, and Erysipelatoclostridiaceae were lower than those of the general population. Conclusion The dairy farm workers shares a certain proportion of common bacterial communities with dairy cows. Dairy farming operations can affect the structure and diversity of the gut microbiota of workers by increasing the abundances of Lachnospiraceae and Ruminococcaceae, while decreasing the abundances of Streptococcaceae, Lactobacillaceae, Bifidobacteriaceae, Enterobacteriaceae, and Erysipelatoclostridiaceae. The study results provide reference data for further exploring the cross-host transmission of pathogens related to occupational exposure in dairy farming.

Objective To analyze the external radiation dose rate and radiation protection measures during treatment of a patient with hepatocellular carcinoma (HCC) who underwent ⁹⁰Y selective internal radiotherapy (⁹⁰Y-SIRT). Methods A male HCC patient who received ⁹⁰Y-SIRT with an activity of 4.65×10⁹ Bq was selected as the research subject using retrospective analysis. External radiation dose rate meters were used to detect ambient dose equivalent rates around the radiation worker, the HCC patient, and the workplace during treatment. Surface contamination meters were used to detect surface contamination levels of the radiation worker and the workplace. Results The ambient dose equivalent rate around the interventional radiology staff during treatment ranged from 3.7 to 39.0 μSv/h. The patient's ambient dose equivalent rate of surgical site at distances of 30, 100, and 200 cm ranged from 45.0 to 5.6, 4.4 to 0.4, and 0.4 to 0.1 μSv/h respectively without protection, and 14.0 to 3.4, 3.2 to 0.3, and 0.4 to 0.1 μSv/h respectively when the surgical site was covered with a 1.0 mmPb lead rubber drape after 0.0 to 161.0 hours of the surgery. In the nuclear medicine department, ambient dose equivalent rate of the workplace ranged from 0.4 to 740.0 μSv/h. The ambient dose equivalent rate around all monitoring points in the digital subtraction angiography operating room accounted at 0.1 μSv/h, and the observation ward ranged from 0.1 to 0.2 μSv/h. The β surface contamination levels of the radiation worker and workplace were below the minimum detection limit (0.16 Bq/cm²). Conclusion Radiation doses for both HCC patients and radiation worker remained within acceptable limits when appropriate protective equipment was used. A well-designed workplace layout is essential to ensure effective implementation of radiation protection.