Objective To explore the effects of tumor necrosis factor-α stimulated gene-6 (TSG-6) on early inflammation and blood brain barrier (BBB) in mice after ischemic stroke (IS).Methods A total of 90 healthy male C57BL/6j mice were randomly divided into sham-operated group (n=30),vehicle group (n=30) and TSG-6 treatment group (n=30);the middle cerebral artery occlusion models (IS) in the later two groups were established with suture emboli method;50 μg TSG-6 or PBS was immediately injected into mice via tail vein after IS.Neurological function deficits were assessed by modified neurological severity scale (mNSS) one and three days after IS;infraction volume was examined by triphenyl tetrazolium chloride (TTC) staining,the changes of brain water content were examined by wet and dry weight method,evans blue (EB) extravasation was assessed by means of EB fluorescent quantitation,myeloperoxidase (MPO) activity was tested by ultraviolet specterphotometry,and Western blotting was used to detect the expressions of matrix metalloproteinase-9 (MMP-9),high-mobility group protein box 1 (HMGB1) and toll-like receptor 4 (TLR4) three days after IS.Results Three days after IS,the mNSS scores (5.253±1.712),infraction volume ([26.100±5.640]％),EB extravasation ([7.233± 3.434] μg/g),brainwater content ([71.667±6.518]％),MPO activity ([70.383±17.558] mU/g) and HMGB1,TLR4 and MMP-9 expressions (0.503±0.230,0.482±0.159 and 0.611±0.170) in the TSG-6 treatment group were significantly lower or smaller than those in the vehicle group ([7.923±2.138],([36.883±8.553]％),([11.867±4.135] μg/g),([80.467±7.045]％),([112.617±26.782] mU/g),[0.861± 0.137],[0.833 ±0.193] and [0.910 ±0.156]) three days after IS (P＜0.05);the expressions of MMP-9 (0.611±0.170),HMGB1 (0.503±0.230) and TLR4 (0.482±0.159) in mice of TSG-6 treatment group were significantly down-regulated as compared with those in vehicle group those days after IS (P＜0.05).Conclusion TSG-6 can exert neuroprotective effect by protecting BBB from damage and reducing brain edema by reduction of MMP-9 after stroke,which is mediated by downregulation of HMGB 1 and its receptor TLR4 and the infiltration ofneutrophile granulocytes.

Venous thromboembolism(VTE)is a prevalent complication in orthopedics.In recent years,machine learning has been widely applied in orthopedics.The essence of machine learning lies in utilizing algorithms to analyze vast amounts of data and construct risk prediction models that can accurately forecast unknown clinical outcomes.By integrating high-risk factors,machine learning aids medical professionals in precisely identifying and screening individuals with a high risk of VTE and offering them timely individualized interventions.This article reviews the concept and classification of machine learning,the advantages of machine learning in enhancing model prediction ability,and the current application status of machine learning in constructing risk prediction models for patients with VTE.

Using chemoproteomic techniques, we first identified EIF2AK2, eEF1A1, PRDX3 and VPS4B as direct targets of berberine (BBR) for its synergistically anti-inflammatory effects. Of them, BBR has the strongest affinity with EIF2AK2 via two ionic bonds, and regulates several key inflammatory pathways through EIF2AK2, indicating the dominant role of EIF2AK2. Also, BBR could subtly inhibit the dimerization of EIF2AK2, rather than its enzyme activity, to selectively modulate its downstream pathways including JNK, NF-κB, AKT and NLRP3, with an advantage of good safety profile. In EIF2AK2 gene knockdown mice, the inhibitory IL-1β, IL-6, IL-18 and TNF-α secretion of BBR was obviously attenuated, confirming an EIF2AK2-dependent anti-inflammatory efficacy. The results highlight the BBR's network mechanism on anti-inflammatory effects in which EIF2AK2 is a key target, and inhibition of EIF2AK2 dimerization has a potential to be a therapeutic strategy against inflammation-related disorders.

A series of new monobactam sulfonates is continuously synthesized and evaluated for their antimicrobial efficacies against Gram-negative bacteria. Compound 33a (IMBZ18G) is highly effective in vitro and in vivo against clinically intractable multi-drug-resistant (MDR) Gram-negative strains, with a highly druglike nature. The checkerboard assay reveals its significant synergistic effect with β-lactamase inhibitor avibactam, and the MIC values against MDR enterobacteria were reduced up to 4-512 folds. X-ray co-crystal and chemoproteomic assays indicate that the anti-MDR bacteria effect of 33a results from the dual inhibition of the common PBP3 and some class A and C β-lactamases. Accordingly, preclinical studies of 33a alone and 33a‒avibactam combination as potential innovative candidates are actively going on, in the treatment of β-lactamase-producing MDR Gram-negative bacterial infections.