Most chemical medicines have polymorphs. The difference of medicine polymorphs in physicochemical properties directly affects the stability, efficacy, and safety of solid medicine products. Polymorphs is incomparably important to pharmaceutical chemistry, manufacturing, and control. Meantime polymorphs is a key factor for the quality of high-end drug and formulations. Polymorph prediction technology can effectively guide screening of trial experiments, and reduce the risk of missing stable crystal form in the traditional experiment. Polymorph prediction technology was firstly based on theoretical calculations such as quantum mechanics and computational chemistry, and then was developed by the key technology of machine learning using the artificial intelligence. Nowadays, the popular trend is to combine the advantages of theoretical calculation and machine learning to jointly predict crystal structure. Recently, predicting medicine polymorphs has still been a challenging problem. It is expected to learn from and integrate existing technologies to predict medicine polymorphs more accurately and efficiently.

Objective To analyze the metabolomics characteristics of chronic atrophic gastritis(CAG)patients with liver-stomach qi stagnation and spleen-stomach weakness syndromes based on non-targeted metabolomics technology,and to identify the serum differentiated metabolites related to traditional Chinese medicine(TCM)syndrome of CAG patients,so as to provide a reference for the objectification of syndrome differentiation.Methods Sixty patients with CAG were included,including 30 cases of liver-stomach qi stagnation syndrome and 30 cases of spleen-stomach weakness syndrome.Fasting blood of 5 mL was collected from the cubital vein of patients in the two groups,and the serum levels of metabolites were detected by ultra-high-performance liquid chromatography-mass spectrometry(UPLC-MS)methods.The principal component analysis(PCA),orthogonal partial least squares-discriminant analysis(OPLS-DA),and cluster analysis were used to screen the differentiated metabolites of CAG patients with liver-stomach qi stagnation syndrome and spleen-stomach weakness syndrome.Finally,metabolite pathway analysis was performed for the obtained differentiated metabolites using the KEGG database.Results The results for the screening of differentiated metabolites showed that significant differences of amino acid derivatives and small peptide metabolites were presented between CAG patients with liver-stomach qi stagnation syndrome and CAG patients with spleen-stomach weakness syndrome.The amino acid derivatives consisted of N-acetylglycine,histamine,O-phosphoserine,selenomethylselenocysteine,and methyl-tyrosine.And the small peptide metabolites consisted of tyrosine-leucine-phenylalanine,histidine-alanine-glutamate-lysine,L-asparagine-L-proline-L-serine,and L-isoleucine-L-isoleucine.Conclusion Differences in amino acid metabolism exist between CAG patients with liver-stomach qi stagnation syndrome and those with spleen-stomach weakness syndrome,and metabolites such as N-acetylglycine,intermethyltyrosine,and O-phosphoserine may be the potential biomarkers for distinguishing liver-stomach qi stagnation syndrome from spleen-stomach weakness syndrome in CAG patients.

Gut microbiota participates in numerous physiological and metabolic processes in the human body,directly affecting human health.The imbalance of gut microbiota may lead to many diseases.This article reviews the types of gut microbiota,the impact of gut microbiota on different populations,and the relationship between gut microbiota abnormalities and diseases,in order to better explain the important role of gut microbiota in human health and diseases,and provide the theoretical basis for further understanding the relationship between gut microbiota and human health.

A major impedance to neuronal regeneration after peripheral nerve injury(PNI)is the activation of various programmed cell death mechanisms in the dorsal root ganglion.Ferroptosis is a form of pro-grammed cell death distinguished by imbalance in iron and thiol metabolism,leading to lethal lipid peroxidation.However,the molecular mechanisms of ferroptosis in the context of PNI and nerve regeneration remain unclear.Ferroportin(Fpn),the only known mammalian nonheme iron export protein,plays a pivotal part in inhibiting ferroptosis by maintaining intracellular iron homeostasis.Here,we explored in vitro and in vivo the involvement of Fpn in neuronal ferroptosis.We first delineated that reactive oxygen species at the injury site induces neuronal ferroptosis by increasing intracellular iron via accelerated UBA52-driven ubiquitination and degradation of Fpn,and stimulation of lipid peroxidation.Early administration of the potent arterial vasodilator,hydralazine(HYD),decreases the ubiquitination of Fpn after PNI by binding to UBA52,leading to suppression of neuronal cell death and significant ac-celeration of axon regeneration and motor function recovery.HYD targeting of ferroptosis is a promising strategy for clinical management of PNI.

DNA genetic markers have always played important roles in individual identification, kinship analysis, ancestry inference and phenotype characterization in the field of forensic medicine. DNA methylation has unique advantages in biological age inference, body fluid identification and prediction of phenotypes. The majority of current studies independently examine DNA and DNA methylation markers using various workflows, and they use various analytical procedures to interpret the biological information these two markers present. Integrated methods detect DNA and DNA methylation markers simultaneously through a single experimental workflow using the same preparation of sample. Therefore, they can effectively reduce consumption of time and cost, streamline experimental procedures, and preserve valuable DNA samples taken from crime scenes. In this paper, the integrated detection approaches of DNA and DNA methylation markers on different detection platforms were reviewed. In order to convert methylation modifications to detectable forms, several options were available for pretreatment of genomic DNA, including digestion with methylation-sensitive restriction enzyme, affinity enrichment of methylated fragments, conversion of methylated or unmethylated cytosine. Multiplexed primers can be designed for DNA markers and converted DNA methylation markers for co-amplification. The schemes of using capillary electrophoresis platform for integrated detection add the pretreatment of genomic DNA on the basis of detecting DNA genetic markers. DNA and DNA methylation markers are then integrated by co-amplification. But the limited number of fluorescent options available and the length of amplicons restrict the type and quantity of markers that can be integrated into a panel. Pyrophosphate sequencing also supports integrated detection of DNA and DNA methylation markers. On this platform, due to the conversion of unmethylated cytosine to thymine after treatment with bisulfite, the methylation level of CpG site can be directly calculated using the peak height ratio of cytosine bases and thymine bases. Therefore, the methylation levels and SNP typing can be simultaneously obtained. However, due to the limited read length of sequencing, the detection of markers with longer amplicons is restricted. It is not conducive to fully interpret the complete information of the target sequence. Next-generation sequencing also supports integrated detection of DNA and DNA methylation markers. A preliminary experimental process including DNA extraction, pretreatment of genomic DNA, co-preparation of DNA and DNA methylation library and co-sequencing, has been formed based on the next-generation sequencing platform. It confirmed the feasibility of next-generation sequencing technology for integrated detection of DNA and DNA methylation markers. In field of biomedicine, various integrated detection schemes and corresponding data analysis approaches of DNA and DNA genetic markers developed based on the above detection process.Co-analysis can simultaneously obtain the genomic genetic and epigenetic information through a single analytic process. These schemes suggest that next-generation sequencing may be an effective method for achieving more accurate and highly integrated detection, helping to explore the potential for application in forensic biological samples. We finally explore the impact of interactions between sites and different pretreatment methods on the integrated detection of DNA and DNA methylation markers, and also propose the challenge of applying third-generation sequencing for integrated detection in forensic samples.

Objective To establish a scoring model for predicting the prognosis and drug sensitivity of colorectal cancer(CRC)based on the expression of disulfidptosis-related genes by bioinformatics analyses combined with the validation with CRC patient-derived organoids(CRC-PDOs).Methods NMF(non-negative Matrix Factorization)algorithm,Cox and LASSO regression analyses were used to identify disulfidptosis-related genes with predictive value for CRC prognosis,and disulfidptosis-related risk scoring formula was constructed.The differential genes and enrichment pathways among different clusters were analyzed by GO(Gene Ontology)and KEGG(Kyoto Encyclopedia of Genes and Genomes).The sensitivity of the high/low-risk clusters of CRC patients to chemotherapy drugs was predicted using the GDSC database and validated using CRC-PDOs.Results The results of NMF algorithm showed that CRC patients could be grouped into two clusters based on the disulfidptosis-related genes.COX regression analysis demonstrated that LRPPRC and SLC7A11 were the only two genes with significance to predict the prognosis of CRC patients(P=0.047,0.033).Low expression of SLC7A11 or high expression of LRPPRC in tumors of CRC patients was significantly correlated with overall survival(OS)(P=0.004,0.003).Based on LASSO regression analysis,the mortality risk scoring formula for disulfidptosis was as follows:Risk score=LRPPRC×(-0.670 5)+SLC7A11×0.311 2,and the GSE161158 dataset could be re-grouped into high-risk and low-risk clusters accordingly.There were 125 differentially expressed genes(DEGs)between the two clusters.According to the GO and KEGG results,the up-regulated genes in high-risk cluster were mainly enriched in immune regulation,such as leukocyte chemotaxis,granulocyte migration and toll-like receptor binding.Low-risk cluster was characterized by pathways associated with sulfide metabolism,such as sulfur compound transmembrane transporter activity.Based on the GDSC database,the expression level of SLC7A11 and LRPPRC could predict chemotherapy drug sensitivity.As a representative,the efficacy of chemotherapy drug(irinotecan)on inhibiting the growth of CRC-PDOs was shown to be linearly correlated with the relative gene expression levels of SLC7A11 and LRPPRC in CRC tissues of patients(P=0.007,0.040).Conclusion According to the results based on the bioinformatics analyses and drug sensitivity testing on CRC-PDOs,disulfidptosis risk score could predict the prognosis and drug sensitivity of CRC patients,with potential clinical application prospect.

Objective To study the trend of stroke mortality in Minhang District,Shanghai from 2012 to 2022 and to predict stroke mortality from 2023 to 2027.Methods Annual percentage change(APC)of stroke deaths in Minhang District,Shanghai from 2012 to 2022 was calculated,and then Joinpoint linear regression model was used to analyze the time trend of stroke deaths.A grey GM(1,1)model was constructed based on the stroke mortality rate in Minhang District,Shanghai from 2012 to 2022.The model was used to predict and analyze the stroke mortality rate in Minhang District,Shanghai from 2023 to 2027.The fitting effect of the model was evaluated using relative error and grade deviation.Results From 2012 to 2022,the overall mortality rate of stroke in Minhang District,Shanghai was on the rise for both males and females(total population:APC=2.50%,P<0.001;male:APC=3.41%,P<0.001;female:APC=1.46%,P=0.008).The grey GM(1,1)model was used to predict the increasing trend of stroke mortality rate in Minhang District from 2023 to 2027.The crude mortality rate of stroke in the entire population in 2027 would be 97.55/100000,with 112.31/100000 for males and 83.33/100000 for females.The fitting effect of the model was tested and evaluated to meet high requirements.Conclusion In the past decade,the mortality rate of stroke in Minhang District,Shanghai has shown a significant upward trend.The 5-year prediction results showed that the mortality rate will still on the rise year by year.

Objective To explore the influential factors and predictive value of early femoral head collapse progression following allogeneic fibula grafting(AFG)surgery.Methods Clinical and radiological data of 68 patients(75 hips)with osteonecrosis of the femoral head(ONFH)who underwent AFG between January 2008 and December 2022 at the Orthopedics and Traumatology Department,Affiliated Hospital of Nanjing University of Chinese Medicine were retrospectively analyzed.Seventy-five hips were divided into stable(n=40)and progressive(n=35)groups based on the presence or absence of postoperative collapse progression.Age,gender,etiology,location of the lesion,Association Research Circulation Osseous(ARCO)stage,Japanese Committee of Osteonecrosis Investigation(JIC)classification,China-Japan Friendship Hospital(CJFH)classification,and Hounsfield units(HU)value of anterolateral sclerosis rim(ⅠSHU)were collected.Univariate and multivariate logistic regression analyses were used to identify the factors influencing early collapse progression after AFG.Receiver operating characteristic(ROC)curve was used to analyze the predictive value of the identified factors influencing postoperative early collapse progression.Results Of the 75 hips,35(46.7%)had postoperative collapse progression.Univariate logistic regression analysis showed that age,ARCO stage,JIC classification,and ⅠSHU were in fluencing factors for early femoral head collapse progression after AFG(P<0.05).Multivariate logistic regression analysis showed that ARCO stage ⅢA and JIC classification C2 were independent risk factors for early femoral head collapse progression after AFG,while ⅠSHU was identified as an independent protective factor(P<0.05).The ROC curve analysis showed that the sensitivities of ARCO stage,JIC classification,ⅠSHU,and the combined predictive model were 0.850,0.725,0.800,and 0.775,the specificities were 0.486,0.657,0.743,and 0.914,and the area under the ROC curve(AUC)were 0.668,0.725,0.811,and 0.896,respectively.Conclusions ⅠSHU is associated with early collapse progression after AFG in patients with ONFH.ARCO stage ⅢA,JIC classification C2,and ⅠSHU are independent factors influencing postoperative early collapse progression and have a certain predictive value.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.