BACKGROUND:Eucommia ulmoides has a certain osteogenic effect,which can promote the proliferation and differentiation of osteoblasts.However,it is unclear whether Eucommia ulmoides has effects on alveolar bone formation and Wnt/β-Catenin signaling pathway. OBJECTIVE:To investigate the mechanism by which Eucommia ulmoides promotes alveolar bone formation in ovariectomized rats based on the Wnt/β-Catenin signaling pathway. METHODS:Sixty female Sprague-Dawley rats were selected and randomly divided into five groups:blank control group,sham-operation group,model group,low-dose group Eucommia ulmoides group,and high-dose Eucommia ulmoides group,with twelve rats in each group.Osteoporosis animal models were constructed by bilateral oophorectomy in the model group and the low-dose and high-dose Eucommia ulmoides groups.The sham-operation group underwent the same method to remove adipose tissue of equal mass around the bilateral ovaries.Three months after surgery,the low-and high-dose Eucommia ulmoides groups were given 2.1 g/kg/d and 4.2 g/kg/d Eucommia ulmoides by gavage,respectively.The sham-operation group and model group were given the same amount of physiological saline by gavage.After 12 weeks of drug intervention,the changes in alveolar bone mass of rats in each group were observed through Micro-CT;hematoxylin-eosin staining was used to observe the pathological structural changes of alveolar bone in rats;enzyme linked immunosorbent assay was used to detect the expression levels of alkaline phosphatase and osteocalcin in the serum of rats;western blot was used to detect the expression levels of β-Catenin and Frizzled9 receptor proteins in the alveolar bone of rats;and real-time fluorescence quantitative PCR was used to detect the expression of osteocalcin,Runt-related transcription factor 2(Runx2),alkaline phosphatase,β-catenin,and frizzled9 mRNAs in alveolar bone tissues of rats. RESULTS AND CONCLUSION:Compared with the blank control group,bone volume fraction,trabecular number,trabecular thickness,and bone mineral density were reduced in the model group(P＜0.05),and trabecular separation was elevated(P＜0.05).Pathological observation showed that the arrangement of trabeculae was disordered and irregular,the trabeculae were thinned or broken,and the marrow cavity was enlarged in the model group,with a significant reduction in bone volume;the level of alkaline phosphatase in the serum was increased(P＜0.05),and the level of osteocalcin was decreased(P＜0.05);mRNA expression of alkaline phosphatase,osteocalcin,Runx2,β-catenin,and frizzled9 were decreased(P＜0.05);protein expression of β-Catenin and Frizzled9 was decreased(P＜0.05).Compared with the model group,the low-and high-dose Eucommia ulmoides groups showed an increase in bone volume fraction,trabecular number,trabecular thickness,and bone mineral density(P＜0.05)and a decrease in trabecular separation(P＜0.05).In the low-and high-dose Eucommia ulmoides groups,bone trabeculae were slightly aligned and thickened,with a significant increase in bone mass.Compared with the model group,the serum level of alkaline phosphatase was reduced(P＜0.05)and the serum level of osteocalcin was elevated(P＜0.05)in the low-and high-dose Eucommia ulmoides groups.Compared with the model group,the mRNA expression of alkaline phosphatase,osteocalcin,Runx2,β-catenin,and frizzled9 were increased in the low-and high-dose Eucommia ulmoides groups(P＜0.05).Compared with the model group,the protein expression of Frizzled9 was increased in the low-dose Eucommia ulmoides group(P＜0.05),while the protein expression of β-Catenin and Frizzled9 was increased in the high-dose Eucommia ulmoides group(P＜0.05).Compared with the low-dose Eucommia ulmoides group,the high-dose Eucommia ulmoides group had a more significant improvement in the above indexes.To conclude,Eucommia ulmoides can effectively promote the alveolar bone formation,and its mechanism of action might be related to the activation of the Wnt/β-catenin signaling pathway.

In recent years, with the improvement of people's awareness of physical examination and the more accurate detection equipment, the detection rate of pulmonary nodules is getting higher and higher. Surgical resection is the first choice for the treatment of malignant pulmonary nodules, but multiple pulmonary nodules, nodules in complex areas and those with surgical contraindications are not suitable for surgery. As an effective, less invasive and low-cost treatment, ablation has developed rapidly in the treatment of multiple pulmonary nodules. This article introduces the progress of several common ablation techniques (radiofrequency ablation, microwave ablation, cryoablation) in the treatment of multiple pulmonary nodules, the indications and contraindications of ablation techniques, the efficacy evaluation and complications after ablation therapy, and the prospects of ablation techniques in the treatment of multiple pulmonary nodules.

ObjectiveObesity has been identified as one of the most important risk factors for cognitive dysfunction. Physical exercise can ameliorate learning and memory deficits by reversing synaptic plasticity in the hippocampus and cortex in diseases such as Alzheimer’s disease. In this study, we aimed to determine whether 8 weeks of treadmill exercise could alleviate hippocampus-dependent memory impairment in high-fat diet-induced obese mice and investigate the potential mechanisms involved. MethodsA total of sixty 6-week-old male C57BL/6 mice, weighing between 20-30 g, were randomly assigned to 3 distinct groups, each consisting of 20 mice. The groups were designated as follows: control (CON), high-fat diet (HFD), and high-fat diet with exercise (HFD-Ex). Prior to the initiation of the treadmill exercise protocol, the HFD and HFD-Ex groups were fed a high-fat diet (60% fat by kcal) for 20 weeks. The mice in the HFD-Ex group underwent treadmill exercise at a speed of 8 m/min for the first 10 min, followed by 12 m/min for the subsequent 50 min, totally 60 min of exercise at a 0° slope, 5 d per week, for 8 weeks. We employed Y-maze and novel object recognition tests to assess hippocampus-dependent memory and utilized immunofluorescence, Western blot, Golgi staining, and ELISA to analyze axon length, dendritic complexity, number of spines, the expression of c-fos, doublecortin (DCX), postsynaptic density-95 (PSD95), synaptophysin (Syn), interleukin-1β (IL-1β), and the number of major histocompatibility complex II (MHC-II) positive cells. ResultsMice with HFD-induced obesity exhibit hippocampus-dependent memory impairment, and treadmill exercise can prevent memory decline in these mice. The expression of DCX was significantly decreased in the HFD-induced obese mice compared to the control group (P<0.001). Treadmill exercise increased the expression of c-fos (P<0.001) and DCX (P=0.001) in the hippocampus of the HFD-induced obese mice. The axon length (P<0.001), dendritic complexity (P<0.001), the number of spines (P<0.001) and the expression of PSD95 (P<0.001) in the hippocampus were significantly decreased in the HFD-induced obese mice compared to the control group. Treadmill exercise increased the axon length (P=0.002), dendritic complexity(P<0.001), the number of spines (P<0.001) and the expression of PSD95 (P=0.001) of the hippocampus in the HFD-induced obese mice. Our study found a significant increase in MHC-II positive cells (P<0.001) and the concentration of IL-1β (P<0.001) in the hippocampus of HFD-induced obese mice compared to the control group. Treadmill exercise was found to reduce the number of MHC-II positive cells (P<0.001) and the concentration of IL-1β (P<0.001) in the hippocampus of obese mice induced by a HFD. ConclusionTreadmill exercise led to enhanced neurogenesis and neuroplasticity by increasing the axon length, dendritic complexity, dendritic spine numbers, and the expression of PSD95 and DCX, decreasing the number of MHC-II positive cells and neuroinflammation in HFD-induced obese mice. Therefore, we speculate that exercise may serve as a non-pharmacologic method that protects against HFD-induced hippocampus-dependent memory dysfunction by enhancing neuroplasticity and neurogenesis in the hippocampus of obese mice.

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.

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.

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.

Modulating Tankyrases (TNKS), interactions with USP25 to promote TNKS degradation, rather than inhibiting their enzymatic activities, is emerging as an alternative/specific approach to inhibit the Wnt/β-catenin pathway. Here, we identified UAT-B, a novel neoantimycin analog isolated from Streptomyces conglobatus, as a small-molecule inhibitor of TNKS-USP25 protein-protein interaction (PPI) to overcome multi-drug resistance in colorectal cancer (CRC). The disruption of TNKS-USP25 complex formation by UAT-B led to a significant decrease in TNKS levels, triggering cell apoptosis through modulation of the Wnt/β-catenin pathway. Importantly, UAT-B successfully inhibited the CRC cells growth that harbored high TNKS levels, as demonstrated in various in vitro and in vivo studies utilizing cell line-based and patient-derived xenografts, as well as APC^min/+ spontaneous CRC models. Collectively, these findings suggest that targeting the TNKS-USP25 PPI using a small-molecule inhibitor represents a compelling therapeutic strategy for CRC treatment, and UAT-B emerges as a promising candidate for further preclinical and clinical investigations.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.