Background: Adrenocortical hormones, particularly 11-oxygenated androgens, are pivotal in female reproductive health and fertility. Standardized detection kits and population-specific reference intervals are lacking in China, hindering related clinical applications. Methods: A HPLC-tandem mass spectrometry (HPLC-MS/MS) pipeline was developed, rigorously validated, and applied to simultaneously quantify corticosterone, cortisone, cortisol, 18-OH cortisol, androstenedione (A4), 11β-hydroxyandrostenedione (11-OH A4), dehydroepiandrosterone, and dehydroepiandrosterone sulfate in serum samples from 455 reproductive-aged women (18–45 yrs) in Guangxi, China. Age-dependent concentration trends were analyzed, and reference intervals stratified by age (2.5th to 97.5th percentiles) were established. Correlations with body-composition metrics, ethnicity, and the menstrual cycle were investigated. Results: The HPLC-MS/MS method demonstrated high precision (intra- and inter-assay CVs < 15%), accuracy, and sensitivity. All eight hormones exhibited significant age-related declines (P < 0.001 for seven hormones; P = 0.001 for 11-OH A4). Notably, 11-OH A4 levels were significantly lower in the 35–45-yr (3.05 nmol/L) and 25–34-yr (3.09 nmol/L) age groups than in the 18–24-yr (3.57 nmol/L) age group, whereas no significant difference was observed between the 35–45-yr and 25–34-yr age groups. Weak negative correlations were observed between the body mass index and corticosterone and cortisone levels, whereas ethnicity and the menstrual cycle showed no significant associations with hormone levels. Conclusions We developed an HPLC-MS/MS-based method for simultaneously quantifying eight adrenocortical hormones, including 11-OH A4, and defined age-specific reference intervals for reproductive-aged Chinese women. These findings advance the clinical utility of adrenocortical hormones in diagnosing and managing reproductive disorders.

Although cancer immunotherapy has made great strides in the clinic, it is still hindered by the tumor immunosuppressive microenvironment (TIME). The stimulator of interferon genes (STING) pathway which can modulate TIME effectively has emerged as a promising therapeutic recently. However, the delivery of most STING agonists, specifically cyclic dinucleotides (CDNs), is performed intratumorally due to their insufficient pharmacological properties, such as weak permeability across cell membranes and vulnerability to nuclease degradation. To expand the clinical applicability of CDNs, a novel pH-sensitive polycationic polymer-modified lipid nanoparticle (LNP-B) system was developed for intravenous delivery of CDNs. LNP-B significantly extended the circulation of CDNs and enhanced the accumulation of CDNs within the tumor, spleen, and tumor-draining lymph nodes compared with free CDNs thereby triggering the STING pathway of dendritic cells and repolarizing pro-tumor macrophages. These events subsequently gave rise to potent anti-tumor immune reactions and substantial inhibition of tumors in CT26 colon cancer-bearing mouse models. In addition, due to the acid-sensitive property of the polycationic polymer, the delivery system of LNP-B was more biocompatible and safer compared with lipid nanoparticles formulated with an indissociable cationic DOTAP (LNP-D). These findings suggest that LNP-B has great potential in the intravenous delivery of CDNs for tumor immunotherapy.

OBJECTIVES: To explore the active components that mediate the therapeutic effect of Centella asiatica on psoriasis and their therapeutic mechanisms. METHODS: TCMSP, TCMIP, PharmMapper, Swiss Target Prediction, GeneCards, OMIM and TTD databases were searched for the compounds in Centella asiatica and their targets and the disease targets of psoriasis. A drug-active component-target network and the protein-protein interaction network were constructed, and DAVID database was used for pathway enrichment analysis. In a RAW264.7 macrophage model of LPS-induced inflammation, the anti-inflammatory effect of 7.5, 15, 30, and 60 μmol/L quercetin, asiaticoside, and asiatic acid, which were identified as the main active components in Centella asiatica, were tested by measuring cellular production of NO, TNF‑α and IL-6 using Griess method and ELISA and by detecting mRNA expressions of IL-23, IL-17A, TNF-α and IL-6 and protein expressions of p-STAT3 (Tyr705) and p-STAT3 (Ser727) with RT-qPCR and Western blotting. RESULTS: A total of 139 targets of Centella asiatica and 4604 targets of psoriasis were obtained, and among them CASP3, EGFR, PTGS2, and ESR1 were identified as the core targets. KEGG analysis suggested that quercetin, asiaticoside, and asiatic acid in Centella asiatica were involved in cancer and IL-17 and MAPK signaling pathways. In the RAW264.7 macrophage model of inflammation, treatment with quercetin significantly reduced cellular production of NO, TNF‑α and IL-6, and lowered mRNA expressions of IL-23, IL-17A, TNF‑α and IL-6 and protein expressions of p-STAT3 (Tyr705) and p-STAT3 (Ser727). CONCLUSIONS Quercetin, asiaticoside and asiatic acid are the main active components in Centella asiatica to mediate the therapeutic effect against psoriasis, and quercetin in particular is capable of suppressing cellular production of NO, TNF‑α and IL-6 and regulating the IL-23/IL-17A inflammatory axis by mediating STAT3 phosphorylation to inhibit inflammatory response.
Quercetin/pharmacology* ; Psoriasis/metabolism* ; STAT3 Transcription Factor/metabolism* ; Mice ; Animals ; Centella/chemistry* ; Triterpenes/pharmacology* ; Phosphorylation ; Interleukin-17/metabolism* ; Interleukin-23/metabolism* ; RAW 264.7 Cells ; Pentacyclic Triterpenes/pharmacology* ; Macrophages/drug effects* ; Signal Transduction ; Plant Extracts

OBJECTIVE: To investigate the biomechanical characteristics of Schatzker type Ⅱ tibial plateau fracture fixed by different bone grafting methods and internal fixations. METHODS: Twenty-four embalmed specimens of adult knee joint were selected to make Schatzker type Ⅱ tibial plateau fracture models, which were randomly divided into 8 groups (groups A1-D1 and groups A2-D2, n=3). After all the fracture models were restored, non-structural iliac crest bone grafts were implanted in group A1-D1, and structural iliac crest bone grafts in groups A2-D2. Following bone grafting, group A was fixed with a lateral golf locking plate, group B was fixed with lateral golf locking plate combined compression bolt, group C was fixed with lateral tibial "L"-shaped locking plate, and group D was fixed with lateral tibial "L"-shaped locking plate combined compression bolt. Compression and cyclic loading tests were performed on a biomechanical testing machine. A distal femur specimen or a 4-cm-diameter homemade bone cement ball were used as a pressure application mould for each group of models. The specimens were loaded with local compression at a rate of 10 N/s and the mechanical loads were recorded when the vertical displacement of the split bone block reached 2 mm. Then, compressive and cyclic loading tests were conducted on the fixed models of each group. The specimens were compression loaded to 100, 400, 700, and 1 000 N at a speed of 10 N/s to record the vertical displacement of the split bone block. The specimens were also subjected to cyclic loading at 5 Hz and 10 N/s within the ranges 100-300, 100-500, 100-700, and 100-1 000 N to record the vertical displacement of the split bone block at the end of the entire cyclic loading test. The specimens were subjected to cyclic loading tests and the vertical displacement of the split bone block was recorded at the end of the test. RESULTS: When the vertical displacement of the collapsed bone block reached 2 mm, the mechanical load of groups A2-D2 was significantly greater than that of groups A1-D1 ( P<0.05). The mechanical load of groups B and D was significantly greater than that of group A under the two bone grafting methods ( P<0.05); the local mechanical load of group D was significantly greater than that of groups B and C under the structural iliac crest bone grafts ( P<0.05). There was no significant difference ( P>0.05) in the vertical displacement of the split bone blocks between the two bone graft methods when the compressive load was 100, 400, 700 N and the cyclic load was 100-300, 100-500, 100-700 N in groups A-D. However, the vertical displacement of bone block in groups A1-D1 was significantly greater than that in groups A2-D2 ( P<0.05) when the compressive loading was 1 000 N and the cyclic load was 100-1 000 N. The vertical displacement of bone block in group B was significantly smaller than that in group A, and that in group D was significantly smaller than that in group C under the same way of bone graft ( P<0.05). CONCLUSION Compared with non-structural iliac crest bone grafts implantation, structural iliac crest bone grafts is more effective in preventing secondary collapse of Schatzker type Ⅱ tibial plateau fracture, and locking plate combined with compression bolt fixation can provide better articular surface support and resistance to axial compression, and the lateral tibial "L"-shaped locking plate can better highlight its advantages of "raft" fixation and show better mechanical stability.
Humans ; Bone Transplantation/methods* ; Tibial Fractures/physiopathology* ; Fracture Fixation, Internal/instrumentation* ; Biomechanical Phenomena ; Bone Plates ; Ilium/transplantation* ; Adult ; Tibia/surgery* ; Bone Cements ; Knee Joint/surgery* ; Male ; Tibial Plateau Fractures

Radiotherapy can cause varying degrees of damage to surrounding normal tissues while treating tumors. In recent years, single-cell RNA sequencing (scRNA-Seq), an emerging technology in modern biology, has gradually played a significant role in research on radiation-induced injuries. Researchers have delved into a variety of radiation-induced brain injuries, including radiation-induced brain injury (RIBI), cardiovascular injury, lung injury, intestinal injury, skin injury, and hematopoietic injury. Their studies provide novel perspectives for revealing the mechanisms behind radiation-induced injuries, assessing the degree of injury, and exploring potential therapies. This study reviews the advances in the application of scRNA-seq to research on radiation-induced injuries.

Objective:To preliminarily establish a sample clot warning model for coagulation screening tests using 5 machine learning methods.Methods:This cross-sectional study collected 7 401 routine screening test samples from Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, from January 1st, 2015, to August 18th, 2024, including 4 786 clotted (positive) and 2 615 qualified (negative) samples for model development. The dataset was divided into Dataset 1 and Dataset 2 based on a reagent change for APTT in December 2018, with separate models developed for each. An additional 2 493 samples (October 31st to November 8th, 2024) were used to evaluate consistency between the model and manual assessment, while 23 200 samples (October 17th to December 31st, 2024) were used for assessing real-world predictive performance. Five machine learning algorithms were employed to develop the clot prediction model: logistic regression (LR), random forest (RF), extreme gradient boosting (XGBoost), naive bayes (NB), and artificial neural network (ANN), with the ANN model constructed using two different hidden layer and neuron parameter settings. Model selection was based on AUC, accuracy, sensitivity, specificity, F1-score, PPV, and NPV, with the optimal model integrated into the LIS for validation.Results:Among the six models using 5 machine learning algorithms, XGBoost demonstrated the highest performance (AUC=0.961, sensitivity=0.945, F1-score=0.934) and robustness to reagent changes ( Z=-1.333, P=0.113). When deployed, the differences between the model's predictions and manual pre-judgment were statistically significant ( Z=-5.289 to 8.933, all P<0.01). The predictive efficacy indices AUC (95% CI), sensitivity, specificity, and accuracy of the XGBoost model deployed in real-world operation of the LIS were 0.939 (0.918—0.960), 0.958, 0.921, and 0.921 respectively. Conclusion:In this study, a clot warning model for coagulation screening samples was established based on the XGBoost algorithm, and its prediction efficacy is good, providing a foundation for intelligent pre-analytical quality control for coagulation screening tests.

AIM:To investigate the value of optical coherence tomography angiography(OCTA)indicators in the diagnosis of diabetic retinopathy(DR), and to provide patients with diabetic nephropathy(DN)with more sensitive OCTA screening indicators to detect concurrent DR at an early stage.METHODS: A total of 200 patients who treated in the ophthalmology department of the Seventh Affiliated Hospital, Sun Yat-sen University from 2022 to 2023 were included, including 95 first-diagnosed DR patients and 105 patients without DR, and all patients underwent OCTA examination and a collection of demographics and renal function parameters. After a quality check, automated measurements of the foveal avascular zone area, vessel density(VD), and perfusion density(PD)of both 3 mm×3 mm and 6 mm×6 mm windows were obtained.RESULTS: Using random forest and multivariate Logistic regression methods, we developed a diagnostic model for DR based on 12 variables(age, FBG, SBP, DBP, HbA1c, ALT, ALP, urea/Scr, DM duration, HUA, DN, and CMT). Adding specific OCTA parameters enhanced the efficacy of the existing diagnostic model for DR(outer vessel density in 6 mm×6 mm window, AUC=0.837 vs 0.819, P=0.03). In the study of DN patients, the parameters in the 6 mm×6 mm window improved the diagnostic efficacy of DR(inner VD; outer VD; full VD; outer PD; full PD).CONCLUSION:The outer VD in the 6 mm×6 mm window can enhance the efficacy of the traditional DR diagnostic model. Meanwhile, compared with the 3 mm×3 mm window, the microvascular parameters in the 6 mm× 6 mm window focusing on DN patients can be more sensitive to diagnosing the occurrence of DR.

Radiotherapy can cause varying degrees of damage to surrounding normal tissues while treating tumors. In recent years, single-cell RNA sequencing (scRNA-Seq), an emerging technology in modern biology, has gradually played a significant role in research on radiation-induced injuries. Researchers have delved into a variety of radiation-induced brain injuries, including radiation-induced brain injury (RIBI), cardiovascular injury, lung injury, intestinal injury, skin injury, and hematopoietic injury. Their studies provide novel perspectives for revealing the mechanisms behind radiation-induced injuries, assessing the degree of injury, and exploring potential therapies. This study reviews the advances in the application of scRNA-seq to research on radiation-induced injuries.

Objective To investigate the role and possible mechanism of celastrol(Cel)in sodium oxalate(NaOx)-induced acute kidney injury(AKI)and crystal deposition in the kidney tissues in mice.Methods Male C57BL/6 mice(aged 8～12 weeks,weighing 22～24 g)were randomly divided into 3 groups.Saline group(control group,intraperitoneal injection with normal saline and drinking water freely),NaOx group(injured group,intraperitoneal injection of 75 mg/kg NaOx,and drinking water containing 50 μmol/L NaOx),and NaOx+Cel group(treatment group,intraperitoneal injection of 1 mg/kg Cel firstly and then 75 mg/kg NaOx in 24 h later,drinking water containing 50 μmol/L NaOx).All specimens were collected in 24 h after NaOx injection.HK-2 cells were randomly divided into 4 groups:Medium group(no treatment),NaOx group(500 μmol/L NaOx),NaOx+Cel group(400 nmol/L Cel pre-treatment for 2 h followed by 500 μmol/L NaOx treatment),and NaOx+Cel+BA group[8 μmol/L betulinic acid(BA,NF-κB agonist)after the interventions as the NaOx+Cel group].Cells of each group were collected in 24 h after corresponding treatments.Von Koosa and cell adhesion assays were used to observe crystal deposition.HE staining was employed to observe renal histopathology and score the damage.CCK-8 assay was utilized to detect cell viability to obtain the optimal concentrations of NaOx and Cel.Serum urea and creatinine levels were detected.Immunohisotochemical assay was conducted to detect the expression of OPN,CD44,KIM-1,NGAL,p65,IL-1β,BAX,and Caspase-3,and Western blotting was performed for protein levels of OPN,CD44,KIM-1,p65,P-p65 and IL-1β.Results The mice in the NaOx+Cel group showed reduced crystal deposition(P<0.0001),attenuated renal tubular damage(P<0.01),decreased serum urea and creatinine levels(P<0.05),and declined expression levels of the renal adhesion molecules OPN and CD44,the kidney injury molecules KIM-1 and NGAL,the inflammation-associated molecules p65 and IL-1β,and the apoptosis related molecules BAX and Caspase-3 when compared with the NaOx group(P<0.05).In in vitro study,the NaOx+Cel group showed reduced crystal adhesion(P<0.0001),decreased expression of the adhesion molecules OPN and CD44(P<0.05),down-regulation of the inflammatory molecule IL-1β and P-p65/p65 ratio(P<0.05),and down-regulation of the renal injury molecule KIM-1(P<0.05)when compared with the NaOx group.In the NaOx+Cel+BA group,crystal adhesion was significantly increased(P<0.0001),the inflammatory molecule IL-1β and the ratio of P-p65/p65 were increased(P<0.05),and the kidney injury molecule KIM-1 was increased when compared with the NaOx+Cel group(P<0.05).Conclusion Cel may reduce NaOx-induced crystal deposition and AKI by inhibiting NF-κB activation.

Objective:To preliminarily establish a sample clot warning model for coagulation screening tests using 5 machine learning methods.Methods:This cross-sectional study collected 7 401 routine screening test samples from Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, from January 1st, 2015, to August 18th, 2024, including 4 786 clotted (positive) and 2 615 qualified (negative) samples for model development. The dataset was divided into Dataset 1 and Dataset 2 based on a reagent change for APTT in December 2018, with separate models developed for each. An additional 2 493 samples (October 31st to November 8th, 2024) were used to evaluate consistency between the model and manual assessment, while 23 200 samples (October 17th to December 31st, 2024) were used for assessing real-world predictive performance. Five machine learning algorithms were employed to develop the clot prediction model: logistic regression (LR), random forest (RF), extreme gradient boosting (XGBoost), naive bayes (NB), and artificial neural network (ANN), with the ANN model constructed using two different hidden layer and neuron parameter settings. Model selection was based on AUC, accuracy, sensitivity, specificity, F1-score, PPV, and NPV, with the optimal model integrated into the LIS for validation.Results:Among the six models using 5 machine learning algorithms, XGBoost demonstrated the highest performance (AUC=0.961, sensitivity=0.945, F1-score=0.934) and robustness to reagent changes ( Z=-1.333, P=0.113). When deployed, the differences between the model's predictions and manual pre-judgment were statistically significant ( Z=-5.289 to 8.933, all P<0.01). The predictive efficacy indices AUC (95% CI), sensitivity, specificity, and accuracy of the XGBoost model deployed in real-world operation of the LIS were 0.939 (0.918—0.960), 0.958, 0.921, and 0.921 respectively. Conclusion:In this study, a clot warning model for coagulation screening samples was established based on the XGBoost algorithm, and its prediction efficacy is good, providing a foundation for intelligent pre-analytical quality control for coagulation screening tests.