[Objective] To explore the strategy of blood management in patients with massive transfusion in the frigid plateau region. [Methods] The treatment process of a patient with liver rupture in the frigid plateau region was analyzed, and the blood management strategy of the frigid plateau region was discussed in combination with the difficulties of blood transfusion and literature review. [Results] The preoperative complete blood count (CBC) test results of the patient were as follows: RBC 3.14×10¹²/L, Hb 10⁶ g/L, HCT 30.40%, PLT 115.00×10⁹/L; coagulation function: PT 18.9 s, FiB 1.31 g/L, DD > 6 μg/mL, FDP 25.86 μg/mL; ultrasound examination and imaging manifestations suggested liver contusion and laceration / intraparenchymal hematoma, splenic contusion and laceration, and massive blood accumulation in the abdominal cavity; it was estimated that the patient's blood loss was ≥ 2 000 mL, and massive blood transfusion was required during the operation; red blood cell components were timely transfused during the operation, and the blood component transfusion was guided according to the patient's CBC and coagulation function test results, providing strong support and guarantee for the successful treatment of the patient. The patient recovered well after the operation, and the CBC test results were as follows: RBC 4.32×10¹²/L, Hb 144 g/L, HCT 39.50%, PLT 329.00×10⁹/L; coagulation function: APTT 29.3 s, PT 12.1 s, FiB 2.728 g/L, DD>6 μg/mL, FDP 25.86 μg/mL. The patient was discharged after 20 days, and regular follow-up reexamination showed no abnormal results. [Conclusion] Individualized blood management strategy should comprehensively consider the patient’s clinical symptoms, the degree of hemoglobin decline, dynamic coagulation test results and existing treatment conditions. Efficient and reasonable patient blood management strategies can effectively improve the clinical outcomes of massive transfusion patients in the frigid plateau region.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Background: The immune system plays a critical role in the development and progression of osteoporosis and fractures. However, the causal relationships between antibody immune responses, immune cells, and these bone conditions remain unclear. This study aimed to explore these relationships using Mendelian randomization (MR) analysis. Methods: We collected complete blood count data from patients with fractures and healthy individuals and analyzed their differences. Then, we conducted a 2-sample, 2-step MR analysis to investigate the causal effects of antibody immune responses on osteoporosis and fractures, using inverse-variance weighted (IVW) as the primary method. We also explored whether immune cells mediate the pathway between antibodies and osteoporosis or fractures. Finally, we analyzed the functions and expression levels of key genes involved. Results: Overall, the fracture group exhibited increased white blood cell count, absolute neutrophil count, absolute monocyte count, platelet count, and their respective proportions, while absolute lymphocyte count, absolute eosinophil count, absolute basophil count, red blood cell count, and their proportions were decreased. We identified 44 causal relationships between antibodies and osteoporosis or fractures, with 7 supported by multiple MR methods, and 5 showing odds ratios significantly deviating from 1 in the IVW analysis. Epstein-Barr virus-related antibodies had a notable impact on osteoporosis and fractures. The human leukocyte antigen (HLA) gene family, particularly HLA-DPB1, emerged as a significant risk factor. However, immune cells were not found to mediate these effects. Conclusions This study elucidated the causal relationships between antibody immune responses, immune cells, and osteoporosis or fractures. The HLA gene family plays a crucial role in the interaction between antibodies and these bone conditions, with HLA-DPB1 identified as a key risk gene. Immune cells do not serve as mediators in this process. These findings provide valuable insights for future research.

Objective To establish a high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS)for the simultaneous determination of gefitinib,erlotinib,nillotinib and imatinib plasma concentrations and analyze the results.Methods The plasma samples were treated with acetonitrile precipitation and separated by Diamonsil C18 column(150 mm ×4.6 mm,3.5 μm)with mobile phase of 0.1％formic acid water(A)-0.1％formic acid acetonitrile(B).The flow rate of gradient elution was 0.7 mL·min-1,and the column temperature was 40 ℃ and the injection volume was 3 μL.Using arotinib as the internal standard,the scanning was carried out by using electrospray ionization source in positive ionization mode with multi-reaction monitoring.The specificity,standard curve,lower limit of quantitation,precision,accuracy,recovery rate,matrix effect and stability of the method were investigated.The concentrations of imatinib and erlotinib in 20 patients with chronic myelogenous leukemia(CML)and gefitinib and erlotinib in 3 patients with non-small cell lung cancer were measured.Results The standard curves of the four drugs were as follows,gefitinib:y=2.536 × 10-3x+9.362 × 10-3(linear range 20-2 000 ng·mL-1,R2=0.996 6);erlotinib:y=3.575× 10-3x+7.406 × 10-3(linear range 50-5 000 ng·mL-1,R2=0.994 9);nilotinib:y=1.945 x 10-3x+0.015 643(linear range 50-5 000 ng·mL-1,R2=0.990 6);imatinib:y=4.56 x 10-3x+0.010 451(linear range 100～104 ng·mL-1,R2=0.9963).RSD of intra-day and inter-day were less than 10％,and the accuracy ranged from 90％to 110％,and the recovery rates were 91.35％to 98.93％(RSD＜10％);the matrix effect ranged from 91.64％to 107.50％(RSD＜10％).Determination of 23 patients showed that the blood concentration of nilotinib ranged from 623.76 to 2 934.13 ng·mL-1,and the blood concentration of imatinib ranged from 757.77 to 2 637.71 ng·mL-1,and the blood concentration of gefitinib ranged from 214.76 to 387.40 ng·mL-1.The serum concentration of erlotinib was 569.57 ng·mL-1.Conclusion The method of this research is simple,fast,sensitive and dedicated,which can be monitored by the concentration of clinical blood.

Objective To analyze the spatiotemporal distribution characteristics of respiratory bacterial infections in Sanmenxia City from 2012 to 2022, and explore key areas for respiratory infection prevention and control. Methods Respiratory bacterial infection cases admitted to our hospital from 2012 to 2022 was collected, use OpenGeoDal software for spatial autocorrelation analysis, and SaTScan software for spatiotemporal scanning analysis. Results From 2012 to 2022, 8762 cases of respiratory bacterial infection were reported in Sanmenxia , with an average annual incidence of 173.47/100 000 and a standardized incidence of 132.63/100 000，and the overall incidence showed a downward trend (χ²=48.093，P<0.01). The incidence of respiratory tract bacterial infection has gender characteristics,the incidence of respiratory tract bacterial infection is the highest among people aged 50 years and above (P<0.05). There was no global spatial autocorrelation, and local autocorrelation results showed that the "high-high" clustering area was mainly located in Yima City. The spatiotemporal scanning results showed that the first level aggregation area was located in Yima City, with a time span of 2020-2022 and a radiation radius of 4.57 km (LLR=40.19, RR=3.27, P<0.001). Conclusion The overall trend of respiratory bacterial infections in Sanmenxia City is decreasing, and Yima City is a ^“high- high^” gathering area, which is a key region to prevention and control.