Integrin α _v β ₃ is overexpressed in various tumor cells and angiogenesis. To date, no drug has been proven to target it for therapy. A first-in-human study was designed to investigate the safety, pharmacokinetics, and dosimetry of ¹⁷⁷Lu-AB-3PRGD2, a novel integrin α _v β ₃-targeting radionuclide drug with an albumin-binding motif to optimize the pharmacokinetics. Ten patients (3 men, 7 women; aged 45 ± 16 years) with integrin α _v β ₃-avid tumors were recruited to accept ¹⁷⁷Lu-AB-3PRGD2 injection in a dosage of 1.57 ± 0.08 GBq (42.32 ± 2.11 mCi), followed by serial scans to obtain its dynamic distribution in the body. Safety tests were performed before and every 2 weeks after the treatment for 6-8 weeks. No adverse event over grade 3 was observed. ¹⁷⁷Lu-AB-3PRGD2 was excreted mainly through the urinary system, with intense radioactivity in the kidneys and bladder. Moderate distribution was found in the liver, spleen, and intestines. The estimated blood half-life was 2.85 ± 2.17 h. The whole-body effective dose was 0.251 ± 0.047 mSv/MBq. The absorbed doses were 0.157 ± 0.032 mGy/MBq in red bone marrow and 0.684 ± 0.132 mGy/MBq in kidneys. This first-in-human study of ¹⁷⁷Lu-AB-3PRGD2 treatment indicates its promising potential for targeted radionuclide therapy of integrin α _v β ₃-avid tumors. It merits further studies in more patients with escalating doses and multiple treatment courses.

BACKGROUND:Based on different algorithms of machine learning,how to carry out clinical research on lumbar disc herniation with the help of various algorithmic models has become a trend and hot spot in the development of intelligent medicine at present. OBJECTIVE:To review the characteristics of different algorithmic models of machine learning in the diagnosis and treatment of lumbar disc herniation,and summarize the respective advantages and application strategies of algorithmic models for the same purpose. METHODS:The computer searched PubMed,Web of Science,EMBASE,CNKI,WanFang,VIP and China Biomedical(CBM)databases to extract the relevant articles on machine learning in the diagnosis and treatment of lumbar disc herniation.Finally,96 articles were included for analysis. RESULTS AND CONCLUSION:(1)Different algorithm models of machine learning provide intelligent and accurate application strategies for clinical diagnosis and treatment of lumbar disc herniation.(2)Traditional statistical methods and decision trees in supervised learning are simple and efficient in exploring risk factors and establishing diagnostic and prognostic models.Support vector machine is suitable for small data sets with high-dimensional features.As a nonlinear classifier,it can be applied to the recognition,segmentation and classification of normal or degenerative intervertebral discs,and to establish diagnostic and prognostic models.Ensemble learning can make up for the shortcomings of a single model.It has the ability to deal with high-dimensional data and improve the precision and accuracy of clinical prediction models.Artificial neural network improves the learning ability of the model,and can be applied to intervertebral disc recognition,classification and making clinical prediction models.On the basis of the above uses,deep learning can also optimize images and assist surgical operations.It is the most widely used model with the best performance in the diagnosis and treatment of lumbar disc herniation.The clustering algorithm in unsupervised learning is mainly used for disc segmentation and classification of different herniated segments.However,the clinical application of semi-supervised learning is relatively less.(3)At present,machine learning has certain clinical advantages in the identification and segmentation of lumbar intervertebral discs,classification and grading of the degenerative intervertebral discs,automatic clinical diagnosis and classification,construction of the clinical predictive model and auxiliary operation.(4)In recent years,the research strategy of machine learning has changed to the neural network and deep learning,and the deep learning algorithm with stronger learning ability will be the key to realizing intelligent medical treatment in the future.

Objective:To evaluate the efficacy and safety of θ short burst rapid pulse stimulation(TBS)in treating schizophrenia by meta-analysis.Methods:Randomized controlled trials(RCTS)on TBS in the treatment of schizophrenia were searched from CNKI,Wanfang,VIP,China Biomedicine,Web of science,PubMed,Embase and Cochrane Library databases to December 2022.The main study indicator was the Positive and Negative Symptoms Scale(PANSS).Risk quality assessment of the included literatures was performed by two reviewers and statistical analysis was performed using RevMan5.3.Results:A total of 13 RCTS with 641 patients were included.Meta-anal-ysis showed that TBS targeting the left dorsolateral prefrontal cortex(DLPFC)with intervention duration longer than 2 weeks decreased the PANSS total scores(WMD=-4.63,95％CI:-5.75--3.51,P＜0.001),positive symptom scores(WMD=-1.13,95％CI:-2.00--0.26,P＜0.05),negative symptom scores(WMD=-2.51,95％CI:-2.77--1.53,P＜0.001)and general psychopathological symptom scores(WMD=-1.20,95％CI:-1.80--0.60,P＜0.001).The adverse reactions of TBS included dizziness,and no serious adverse e-vents were reported.Conclusion:TBS has high safety,and stimulation of left dorsolateral prefrontal cortex targets for more than 2 weeks could effectively improve psychiatric symptoms in patients with schizophrenia.

Objective To investigate the expression and role of the DNA repair and recombination protein RAD54-like(RAD54L)in oral squamous cell carcinoma(OSCC).Methods Using OSCC-related data from The Cancer Genome Atlas(TCGA)database,the difference in RAD54L expression between OSCC and control samples was analysed using the Mann-Whitney rank sum test,and the potential value of RAD54L mRNA in OSCC diagnosis was assessed using the receiver operator characteristic curve.The correlation between RAD54L expression levels and clinicopathological data of OSCC patients was analysed using the chi-square test.Once OSCC samples were divided into two groups of high and low expression based on the median value of RAD54L mRNA expression,Cox regression analysis was used to compare the prognostic differences between the two groups.The differentially expressed genes between the groups were subse-quently screened using the DESeq2 package,and KEGG pathway enrichment analysis was performed using the cluster-Profiler package.The correlation between RAD54L mRNA and gene expression in the homologous recombination repair pathway was demonstrated by Spearman correlation analysis.After clarifying the bioinformatics significance of RAD54L,RAD54L knockdown experiments were performed in human oral squamous carcinoma cell line HSC-3,and the knock-down efficiency was verified through real-time quantitative polymerase chain reaction.After transfection,the changes in proliferation,migration,apoptosis,and cycle of HSC-3 cells were assessed by CCK-8,5-ethynyl-2'-deoxyuridine(EdU)staining,wound healing,apoptosis,and cell cycle assays.Results Bioinformatics analysis showed that the expression of RAD54L mRNA was higher in OSCC than in normal controls(P＜0.001)and had a high value in predicting poor prognosis(AUC=0.927).The high RAD54L expression group was associated with an increased proportion of male pa-tients(P=0.032),having a higher T-stage(P=0.040),clinical stage(P=0.027),and pathological grading(P=0.013).Once OSCC samples were divided into two groups of high and low expression using the median value of RAD54L mRNA expression,the prognosis of the group with high expression of RAD54L was poorer than that of the group with low expression(P=0.049).The differentially expressed genes between the high and low RAD54L expression groups two groups were mainly enriched in neuroactive ligand-receptor interactions,cytokine-cytokine receptor interactions,calci-um signaling pathway,cell cycle,gastric cancer,extracellular matrix receptor interactions,chemical carcinogenesis-DNA adducts,DNA replication,homologous recombination,and mismatch repair pathways(P＜0.05).In the homolo-gous recombination repair pathway,the expression of RAD54L was positively correlated with the expression of BRCA1,BLM,EME1,XRCC2,POLD1,TOPBP1,RAD51,BRIP1,RAD54B,BRCA2,and SYCP3(P＜0.05),and was strongly positively correlated with the expression of BRCA1,BLM,and EME1(R＞0.8,P＜0.05).The results of in vitro experi-ments showed that RAD54L expression was knocked down to approximately 25％in HSC-3 cells(P＜0.001).Compared with the control group,the RAD54L knockdown group showed a lower proliferation rate(P＜0.05),a lower proportion of EdU-positive cells(P＜0.001),a lower proportion of wound closure(P＜0.001),a higher proportion of G1-phase cells(P＜0.001),a lower proportion of S-phase cells(P＜0.001),and a higher proportion of apoptotic cells(P＜0.001).Conclusion RAD54L is highly expressed in OSCC and correlates with poor prognosis.Down-regulation of RAD54L expression inhibits the proliferation and migration of HSC-3 cells,promotes apoptosis,and impedes cell cycle progres-sion.

Objective:To explore the feasibility of the post process of computed tomography angiography(CTA)on head and neck based on artificial intelligence(AI)deep learning on stenosis assessment.Methods:A total of 108 patients who underwent CTA on head and neck at Shunyi Hospital of Beijing Traditional Chinese Medicine Hospital from January 2022 to June 2023 were selected,and they were divided into an AI group(54 cases)and a manual group(54 cases)based on different diagnostic methods.Dual source CT was used to conduct examination,and data was transmitted to"Shenrui Dr.Wise Head and Neck CTA Intelligent Assistance System"and"Siemens Syngo View Post Process Workstation".The image evaluation was conducted on a 5-point scale.The time-consuming of post process and diagnosis of CTA images of the artery of head and neck between two groups were observed and compared,and the quality of CTA images of the artery of head and neck,and the diagnostic results of the degree of the artery stenosis of head and neck also were observed and compared between two groups.Results:The differences of the time-consuming of post process of images and the time-consuming of diagnosis between two groups were all statistically significant(t=52.315,24.509,P<0.05),respectively.The intra-group correlation coefficient(ICC)of each branch of the artery of head and neck was 0.996 between two physicians.In AI group,the score of common carotid artery was(4.77±0.12),and the score of internal carotid artery was(4.56±0.13),and the score of vertebral artery was(4.55±0.16),and the score of middle cerebral artery was(4.78±0.16).In manual group,the score of common carotid artery was(3.02±0.12),and the score of internal carotid artery was(3.02±0.12),and the score of vertebral artery was(3.02±1.14),and the score of middle cerebral artery was(3.11±1.09).The differences of the image scores of each main branch of the artery of head and neck between two groups were significant(t=107.165,94.590,13.812,15.753,P<0.05),respectively,and scores of AI group all higher than these of manual group.The result of digital subtraction angiography(DSA)was used as the"gold standard".A total of 44 stenosis arteries were included for comparison,and the DSA results indicated that there were 12 cases with mild stenosis,12 cases with moderate stenosis and 10 cases with severe stenosis in AI group,and there were 12 cases with mild stenosis,8 cases with moderate stenosis and 7 cases with severe stenosis in manual group.There was a favorable diagnostic consistency in AI group(Kappa=0.898,P<0.05).The compliance rate of each stenosis of AI group was higher than that of manual group.The sensitivity(96.80%)and specificity(66.52%)of AI group were all higher than those(68.36 and 14.75%)of manual group,and the difference of specificity was significant.Conclusion:The time-consuming of post process,the time-consuming of diagnosis and the quality of CTA image of the artery of head and neck in AI mode are better than those in manual mode,and the consistency of diagnostic efficacy between two modes is favorable.

Objective In this paper,the harmful effects and mechanisms induced by traditional Chinese medicine were expounded by combining the mechanism of programmed cell death and inflammatory reaction.It is expected to provide data support and theoretical reference for the rational use of traditional Chinese medicine and toxicology research.Methods By systematically analyzing the correlation between cell death and inflammatory response,the molecular mechanisms of pyroptosis,programmed cell necrosis and ferroptosis at home and abroad were summarized,and the harmful outcomes induced by traditional Chinese medicine were further discussed.Results Different toxic traditional Chinese medicines and their active ingredients have different tolerances to biological organisms.Programmed cell death is an important molecular mechanism for the toxicity of traditional Chinese medicines.Its signaling pathways are complex and diverse and are often accompanied by inflammatory reactions.Both of them have a certain effect on the toxic effects of traditional Chinese medicine.Conclusion Traditional Chinese medicine can provide inflammatory mediators for inflammatory response pathways through cell death or change the physiological balance of cells,thereby inducing inflammatory cascade reactions and promoting harmful outcomes in various systems of the body under the dual effects of cell death and inflammatory response.

Objective To investigate the distribution and drug resistance characteristics of pathogens in donors and recipients undergoing simultaneous pancreas-kidney transplantation (SPK). Methods Clinical data of 231 pairs of donors and recipients undergoing SPK were analyzed retrospectively. The pathogens of samples from donors and recipients were identified by VITEK-2 analyzer, and drug sensitivity test was performed by K-B method. The source distribution and composition ratio of pathogens in donor and recipient samples, distribution characteristics of multi-drug resistant organism, infection of recipients and drug resistance characteristics of pathogens were analyzed. Results A total of 395 strains of pathogens were cultured from 1 294 donor samples, and the detection rate was 30.53%. Gram-negative bacteria mainly consisted of klebsiella pneumoniae, Gram-positive bacteria mainly comprised staphylococcus aureus, and fungi primarily included candida albicans, respectively. In total, 2 690 strains of pathogens were cultured from 10 507 recipient samples, and the detection rate was 25.60%. Gram-negative bacteria mainly consisted of pseudomonas maltophilia, Gram-positive bacteria primarily comprised enterococcus faecalis, and fungi mainly included candida albicans, respectively. Among 395 pathogens of donors, 15 strains of methicillin-resistant staphylococcus aureus (MRSA), 16 strains of extended-spectrum β-lactamase (ESBL) positive drug-resistant bacteria, 8 strains of carbapenem-resistant pseudomonas aeruginosa (CR-PA), 21 strains of carbapenem-resistant acinetobacter baumannii (CR-AB), 2 strains of carbapenem-resistant enterobacteriaceae (CRE) and 1 strain of multiple-drug/pan-drug resistant pseudomonas aeruginosa (MDR/PDR-PA) were identified. Among 2 690 strains of recipient pathogens, 73 strains of ESBL positive drug-resistant bacteria, 44 strains of CR-PA, 31 strains of CR-AB and 3 strains of MDR/PDR-PA were detected. One recipient developed donor-derived infection, 69 cases of pneumonia, 52 cases of urinary tract infection, 35 cases of abdominal infection and 2 cases of hematogenous infection were reported within postoperative 1 year. Gram-negative bacteria were resistant to certain antibiotics. Gram-positive bacteria were sensitive to vancomycin. Fungi were sensitive to amphotericin B. Conclusions Gram-negative bacteria are the main pathogens of SPK recipients, which are resistant to certain antibiotics. Empirical use of antibiotics can be delivered before culture results are obtained. Subsequently, sensitive antibiotics should be chosen according to the culture results to improve the survival rate of SPK recipients.

Objective:To investigate COVID-19 vaccination status and relevant adverse reactions in patients with psoriasis treated with biological agents, and to explore the effect of COVID-19 vaccination on psoriatic lesions.Methods:Clinical data were collected from 572 psoriasis patients aged 18 - 60 years, who were registered in the management system of psoriasis patients treated with biological agents in the University of Hong Kong-Shenzhen Hospital from May 2019 to June 2021. The COVID-19 vaccination status was investigated by telephone interviews, and the vaccination-related information was obtained by fixed healthcare workers during a fixed time period according to a predesigned questionnaire. Measurement data were compared between two groups by using t test, and enumeration data were compared by using chi-square test or Fisher′s exact test. Results:The COVID-19 vaccination coverage rate was 43.13% (226 cases) among the 524 patients who completed the telephone interview, and was significantly lower in the biological agent treatment group (30.79%, 105/341) than in the traditional drug treatment group (66.12%, 121/183; χ2 = 60.60, P < 0.001) . The main reason for not being vaccinated was patients′ fear of vaccine safety (49.66%, 148/298) , followed by doctors′ not recommending (26.51%, 79/298) . In the biological agent treatment group after vaccination, the exacerbation of psoriatic lesions was more common in patients receiving prolonged-interval treatment (42.86%, 6/14) compared with those receiving regular treatment (4.40%, 4/91; Fisher′s exact test, P < 0.001) . Skin lesions were severely aggravated in two patients after COVID-19 vaccination, who ever experienced allergic reactions and whose skin lesions did not completely subside after the treatment with biological agents. Conclusions:The COVID-19 vaccination coverage rate was relatively low in the psoriasis patients treated with biological agents, and no serious adverse reaction was observed after vaccination. Prolonged-interval treatment due to COVID-19 vaccination ran the risk of exacerbation of skin lesions.

Peptides that are composed of dextrorotary (d)-amino acids have gained increasing attention as a potential therapeutic class. However, our understanding of the in vivo fate of d-peptides is limited. This highlights the need for whole-body, quantitative tracking of d-peptides to better understand how they interact with the living body. Here, we used mouse models to track the movement of a programmed death-ligand 1 (PD-L1)-targeting d-dodecapeptide antagonist (DPA) using positron emission tomography (PET). More specifically, we profiled the metabolic routes of [⁶⁴Cu]DPA and investigated the tumor engagement of [⁶⁴Cu/⁶⁸Ga]DPA in mouse models. Our results revealed that intact [⁶⁴Cu/⁶⁸Ga]DPA was primarily eliminated by the kidneys and had a notable accumulation in tumors. Moreover, a single dose of [⁶⁴Cu]DPA effectively delayed tumor growth and improved the survival of mice. Collectively, these results not only deepen our knowledge of the in vivo fate of d-peptides, but also underscore the utility of d-peptides as radiopharmaceuticals.

Drug metabolism and pharmacokinetics (DMPK) is an important branch of pharmaceutical sciences. The nature of ADME (absorption, distribution, metabolism, excretion) and PK (pharmacokinetics) inquiries during drug discovery and development has evolved in recent years from being largely descriptive to seeking a more quantitative and mechanistic understanding of the fate of drug candidates in biological systems. Tremendous progress has been made in the past decade, not only in the characterization of physiochemical properties of drugs that influence their ADME, target organ exposure, and toxicity, but also in the identification of design principles that can minimize drug-drug interaction (DDI) potentials and reduce the attritions. The importance of membrane transporters in drug disposition, efficacy, and safety, as well as the interplay with metabolic processes, has been increasingly recognized. Dramatic increases in investments on new modalities beyond traditional small and large molecule drugs, such as peptides, oligonucleotides, and antibody-drug conjugates, necessitated further innovations in bioanalytical and experimental tools for the characterization of their ADME properties. In this review, we highlight some of the most notable advances in the last decade, and provide future perspectives on potential major breakthroughs and innovations in the translation of DMPK science in various stages of drug discovery and development.