From the perspective of transfusion medicine and based on the vision and framework of patient blood management, this article combines the advances in basic science, blood transfusion, laboratory, and clinical medicine. It aims to systematically review the key elements and characteristics of patient fibrinogen management by maintaining and optimizing patients' hemostatic function while reducing blood transfusions. This review enriches the connotation of transfusion medicine, especially patient blood management, and provides valuable insights for clinical practice.

Objective: To conduct screening for rare blood types within important blood group systems for the Chinese population, such as Rh, Duffy, Kidd, P1Pk, Diego, and MNS, in the Guangzhou region, and to establish a corresponding rare blood type database and physical repository. Methods: The saline medium microplate method was used to screen blood donors with the ccDEE phenotype combined with either Jk(a-) or Jk(b-). The polybrene microplate method was employed to screen for donors with Fy(a-), s(-), Lu(b-), Di(b-), k(-), and p phenotypes. The urea lysis microplate method was applied to screen for the Jk(a-b-) phenotype. A high-resolution melting (HRM) curve method was established for screening some donors with the Di(b-) phenotype. Subsequently, expanded phenotyping of antigens in the Rh, Kidd, MNS, Duffy, P1Pk, Lewis, Kell, and Lutheran blood group systems was performed on identified rare blood type donors using monoclonal antibodies. The test results are entered into the Rare Blood Type Bank Management System of the Guangzhou Blood Center, enabling functions such as confirmation reminders and cryopreservation storage when the donor donates again. Red blood cells of rare blood types are processed into frozen red blood cells for long-term storage. Results: Among voluntary blood donors, 16 cases of the ccDEE combined with Jk(a-) phenotype were identified (0.221 7%, 16/7 216); 10 cases of the ccDEE combined with Jk(b-) phenotype (0.138 6%, 10/7 216); 78 cases of the Fy(a-) phenotype (0.169 5%, 78/46 012); 39 cases of the Lu(b-) phenotype (0.138 2%, 39/28 214); 31 cases of the s(-) phenotype (0.081 8%, 31/37 913); 22 cases of the Di(b-) phenotype (0.029 9%, 22/73 691); 30 cases of the Jk(a-b-) phenotype (0.010 1%, 30/298 250); and 1 case of the k(-) phenotype (0.001 3%, 1/77 382), which was further identified as KELnull phenotype (K0). No p phenotype donors were identified (0/88 528). A total of 228 units of frozen red blood cells were prepared. The screening results were compared and analyzed with rare blood type data from other regions. Conclusion: This study, through a combination of different screening methods, significantly improved the efficiency of rare blood type screening while remaining cost-effective. By conducting large-scale screening and performing data informatization processing, a database and physical repository of rare blood types in the Guangzhou region were successfully established. This provides a strong guarantee for the timely supply of blood to patients with difficult-to-match and rare blood types in the region, effectively enhances the level of transfusion safety in the region, and offers a practical paradigm for constructing a comprehensive blood transfusion support system.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Background/Aims: Anti-reflux mucosal ablation (ARMA) is a promising endoscopic intervention for proton pump inhibitor (PPI)-dependent gastroesophageal reflux disease (GERD). However, the effect of ARMA on esophageal motility remains unclear. Methods: Twenty patients with PPI-dependent GERD receiving ARMA were prospectively enrolled. Comprehensive self-report symptom questionnaires, endoscopy, 24-hour impedance-pH monitoring, and high-resolution impedance manometry were performed and analyzed before and 3 months after ARMA. Results: All ARMA procedures were performed successfully. Symptom scores, including GerdQ (11.16 ± 2.67 to 9.11 ± 2.64, P = 0.026) and reflux symptom index (11.63 ± 5.62 to 6.11 ± 3.86, P = 0.001), improved significantly, while 13 patients (65%) reported discontinuation of PPI. Total acid exposure time (5.84 ± 4.63% to 2.83 ± 3.41%, P = 0.024) and number of reflux episodes (73.05 ± 19.34 to 37.55 ± 22.71, P < 0.001) decreased significantly after ARMA. Improved esophagogastric junction (EGJ) barrier function, including increased lower esophageal sphincter resting pressure (13.89 ± 10.78 mmHg to 21.68 ± 11.5 mmHg, P = 0.034), 4-second integrated relaxation pressure (5.75 ± 6.42 mmHg to 9.99 ± 5.89 mmHg, P = 0.020), and EGJ-contractile integral(16.42 ± 16.93 mmHg · cm to 31.95 ± 21.25 mmHg · cm, P = 0.016), were observed. Esophageal body contractility also increased significantly (distal contractile integral, 966.85 ± 845.84 mmHg · s · cm to 1198.8 ± 811.74 mmHg · s · cm, P = 0.023). Patients with symptom improvement had better pre-AMRA esophageal body contractility. Conclusions ARMA effectively improves symptoms and reflux burden, EGJ barrier function, and esophageal body contractility in patients with PPIdependent GERD during short-term evaluation. Longer follow-up to clarify the sustainability of ARMA is needed.

Methods: This retrospective study analyzed 32 consecutive IDS patients who underwent UEDD surgery. Clinical features, laboratory data (erythrocyte sedimentation rate and C-reactive protein), and treatment outcomes were analyzed. Results: Definite microorganisms were identified in 27 patients (84.3%), with 24 (88.9%) meeting cure criteria. The cure rate was significantly higher in the detected pathogen group compared to the undetected pathogen group (88.9% vs. 80%; χ²=19.36, p<0.0001). Metagenomic next generation sequencing (mNGS) provided faster diagnosis (41.72±6.81 hours) compared to tissue culture (95.74±35.47 hours, p<0.05). The predominant causative pathogen was Mycobacterium tuberculosis, followed by Staphylococcus aureus. Significant improvements were observed in Visual Analog Scale pain scores, from a mean of 7.9 preoperatively to 1.06 at 1 year postoperatively. The Oswestry Disability Index revealed a similar trend, showing significant improvement (p<0.05). Conclusions UEDD is a viable alternative to traditional open surgery for managing IDS in high-risk patients. UEDD offers a dual therapeutic-diagnostic advantage during the initial admission phase, enabling simultaneous debridement, neurological decompression, and targeted biopsy in a single intervention. Compared with traditional tissue culture, mNGS enables rapid microbiological diagnosis and extensive pathogen coverage.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Acute lung injury (ALI) is a severe disease caused by viral infection that triggers an uncontrolled inflammatory response. This study investigated the capacity of jasurolignoside (JO), a natural compound, to bind to Toll-like receptor 4 (TLR4) and treat ALI. The anti-inflammatory properties of JO were evaluated in vitro through Western blotting, enzyme-linked immunosorbent assay (ELISA), immunofluorescence staining, and co-immunoprecipitation. The investigation utilized a lipopolysaccharide (LPS)-induced ALI animal model to examine the therapeutic efficacy and mechanism of JO in vivo. JO attenuated inflammatory symptoms in infected cells and tissues by modulating the NOD-like receptor family pyrin domain containing protein 3 (NLRP3) inflammasome and the nuclear factor κB (NF-κB)/mitogen-activated protein kinase (MAPK) pathway. Molecular docking simulations revealed JO binding to TLR4 active sites, confirmed by cellular thermal shift assay. Surface plasmon resonance (SPR) demonstrated direct interaction between JO and TLR4 with a Kd value of 35.1 μmol·L^-1. Moreover, JO inhibited tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), and IL-6 secretion and reduced leukocyte, neutrophil, lymphocyte, and macrophage infiltration in ALI-affected mice. JO also enhanced lung function and reduced ALI-related mortality. Immunohistochemical staining demonstrated JO's ability to suppress TLR4 expression in ALI-affected mouse lung tissue. This study establishes that JO can bind to TLR4 and effectively treat ALI, indicating its potential as a therapeutic agent for clinical applications.
Toll-Like Receptor 4/chemistry* ; Animals ; Acute Lung Injury/chemically induced* ; Mice ; Humans ; Ilex/chemistry* ; Molecular Docking Simulation ; Male ; NF-kappa B/immunology* ; Mice, Inbred C57BL ; NLR Family, Pyrin Domain-Containing 3 Protein/immunology* ; Tumor Necrosis Factor-alpha/genetics* ; Interleukin-1beta/genetics* ; RAW 264.7 Cells ; Disease Models, Animal

OBJECTIVE: The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks. METHODS: A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). RESULTS: During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43). CONCLUSION Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans ; China/epidemiology* ; Male ; Female ; Stroke/etiology* ; Middle Aged ; Prospective Studies ; Incidence ; Aged ; Animals ; Fishes ; Risk Factors ; Diet ; Seafood ; Adult ; Cohort Studies

Methods: This retrospective study analyzed 32 consecutive IDS patients who underwent UEDD surgery. Clinical features, laboratory data (erythrocyte sedimentation rate and C-reactive protein), and treatment outcomes were analyzed. Results: Definite microorganisms were identified in 27 patients (84.3%), with 24 (88.9%) meeting cure criteria. The cure rate was significantly higher in the detected pathogen group compared to the undetected pathogen group (88.9% vs. 80%; χ²=19.36, p<0.0001). Metagenomic next generation sequencing (mNGS) provided faster diagnosis (41.72±6.81 hours) compared to tissue culture (95.74±35.47 hours, p<0.05). The predominant causative pathogen was Mycobacterium tuberculosis, followed by Staphylococcus aureus. Significant improvements were observed in Visual Analog Scale pain scores, from a mean of 7.9 preoperatively to 1.06 at 1 year postoperatively. The Oswestry Disability Index revealed a similar trend, showing significant improvement (p<0.05). Conclusions UEDD is a viable alternative to traditional open surgery for managing IDS in high-risk patients. UEDD offers a dual therapeutic-diagnostic advantage during the initial admission phase, enabling simultaneous debridement, neurological decompression, and targeted biopsy in a single intervention. Compared with traditional tissue culture, mNGS enables rapid microbiological diagnosis and extensive pathogen coverage.