Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

The FDA approved a total of 37 new drugs in 2022, including 22 new molecular entities and 15 new biological products. This is the year with the lowest number of new drugs approved by the FDA since 2017. Among these approved drugs, 21 new drugs belong to the "first-in-class" category, accounting for 56% of the total approved drugs, which is the highest ratio in the past 10 years. Among the drugs approved in 2022, there are 5 small molecule kinase modulators, including the tyrosine kinase 2 (TYK2) allosteric inhibitor deucravacitinib, the first oral pyruvate kinase (PK) activator mitapivat, the Janus kinase 1 (JAK1) selective inhibitor abcrocitinib, the JAK2 selective inhibitor pacritinib and the broad-spectrum fibroblast growth factor receptor (FGFR) inhibitor futibatinib. This review briefly describes the discovery background, research and development process, synthesis routes and clinical efficacy and safety of small molecule kinase modulators approved by the FDA in 2022, hoping to provide ideas and methods for further research on kinase modulators.

Objective To investigate the relationship between correcting abnormal glucose metabolism and mortality risk of malignant tumors of digestive system. Methods A retrospective cohort study was conducted. 1308 patients with abnormal glucose metabolism in our hospital from January 2019 were divided into exposed group (n=777) and non-exposed group (n=531) according to the presence or absence of glucose metabolism correction therapy. The patients were retrospectively followed up until December 2022. The incidence of digestive system tumors and the influencing factors of tumors were compared between the two groups. Results There were 31 patients with digestive system tumor and 9 patients died. The incidence of digestive system tumors was lower in the exposed group (3/777) than in the non-exposed group (28/531). The mortality rate in the exposed group (1/777) was lower than that in the non-exposed group (8/531). Cox regression model analysis showed that correcting abnormal glucose metabolism was a protective factor for the risk of death from malignant tumors of the digestive system in patients (HR value<1, P<0.05) ; increased FBG, combined abnormal lipid metabolism, increased pulse pressure difference, family history of malignant tumors, and alcohol consumption were shown as risk factors for the risk of death from malignant tumors of the digestive system in patients (HR values>1, P<0.05). Conclusion Correcting abnormal glucose metabolism is of positive significance in reducing the risk of death from malignant tumors of digestive system. Patients with increased FBG, abnormal lipid metabolism, increased pulse pressure difference, family history of malignant tumors and alcohol consumption should pay special attention to correct abnormal glucose metabolism in time.

Objective:Utilizing a seven-year panel data set of a targeted admission medical student cohort,this study aims to examine their career development and provide insights for retaining healthcare talent in township health centers and village clinics in the central and western rural areas of China.Method:Starting from 2015,cohorts of targeted and general clinical graduates from four medical colleges in central and western China were selected and tracked for their career progression.Results:The targeted graduates'standardized residency training and medical licensing examination pass rates were similar to those of general clinical graduates.They advanced more quickly in professional titles and positions,with 82.5%becoming attending physicians and 16.2%obtaining positions in the seventh year after graduation.However,their monthly income was significantly lower than that of general clinical graduates,and this income discrepancy expanded annually.As of December 2022,among the 493 targeted graduates who completed their contracts,38.5%stayed in grassroots positions.Of those who left,60%moved to county-level or higher public hospitals,7.9%pursued further studies,and 27.7%were unemployed.Conclusion:Targeted graduates are well-trained and advance rapidly in their careers,but their lower income significantly impacts their willingness to remain at the grassroots level.After completing their service period,about one-third of the targeted graduates choose to stay in grassroots positions.

ObjectiveTriple-negative breast cancer (TNBC) is the breast cancer subtype with the worst prognosis, and lacks effective therapeutic targets. Colony stimulating factors (CSFs) are cytokines that can regulate the production of blood cells and stimulate the growth and development of immune cells, playing an important role in the malignant progression of TNBC. This article aims to construct a novel prognostic model based on the expression of colony stimulating factors-related genes (CRGs), and analyze the sensitivity of TNBC patients to immunotherapy and drug therapy. MethodsWe downloaded CRGs from public databases and screened for differentially expressed CRGs between normal and TNBC tissues in the TCGA-BRCA database. Through LASSO Cox regression analysis, we constructed a prognostic model and stratified TNBC patients into high-risk and low-risk groups based on the colony stimulating factors-related genes risk score (CRRS). We further analyzed the correlation between CRRS and patient prognosis, clinical features, tumor microenvironment (TME) in both high-risk and low-risk groups, and evaluated the relationship between CRRS and sensitivity to immunotherapy and drug therapy. ResultsWe identified 842 differentially expressed CRGs in breast cancer tissues of TNBC patients and selected 13 CRGs for constructing the prognostic model. Kaplan-Meier survival curves, time-dependent receiver operating characteristic curves, and other analyses confirmed that TNBC patients with high CRRS had shorter overall survival, and the predictive ability of CRRS prognostic model was further validated using the GEO dataset. Nomogram combining clinical features confirmed that CRRS was an independent factor for the prognosis of TNBC patients. Moreover, patients in the high-risk group had lower levels of immune infiltration in the TME and were sensitive to chemotherapeutic drugs such as 5-fluorouracil, ipatasertib, and paclitaxel. ConclusionWe have developed a CRRS-based prognostic model composed of 13 differentially expressed CRGs, which may serve as a useful tool for predicting the prognosis of TNBC patients and guiding clinical treatment. Moreover, the key genes within this model may represent potential molecular targets for future therapies of TNBC.

Sustained and controlled release preparation is ideal for reducing the side effects of drugs, improving patient compliance and enhancing efficacy, among which oral sustained-release tablets are the most widely used. The in vitro release of the preparation is closely related to the in vivo absorption of the drug. However, current in vitro release experiments are labor-intensive and destructive, and the lack of big data also makes it difficult to establish good in vivo and in vitro correlations. Computer modeling, as a technical means that can transform objective principles into mathematical models, has great prospects in data prediction. This review explores the existing computer modeling methods that can be used to predict in vitro release profiles of oral sustained-release tablets, and further discusses auxiliary technologies that can improve the accuracy of the models, providing new ideas for drug development.

Objective: To analyze the characteristics of fine particulate matter (PM2.5) pollution in Urumqi City, Xinjiang Uygur Autonomous Region from 2016 to 2023 and establish a prediction model, so as to provide the reference for air pollution prevention and control. Methods: PM2.5 monitoring data of Urumqi City from 2016 to 2023 were collected through the website of Ministry of Ecology and Environment of China. The changing trend of PM2.5 concentration was analyzed using temporal chart and seasonal index. PM2.5 monthly average concentrations from 2016 to 2023 were used to establish an autoregressive integrated moving average (ARIMA) model, and the data in 2023 was fitted and compared with the actual values, using mean absolute percentage error (MAPE) to evaluate the effectiveness of the model, and PM2.5 monthly average concentration from 2024 to 2025 was predicted. Results: PM2.5 daily average concentration in Urumqi City showed a decreasing trend from 2016 to 2023 (rs=-0.239, P<0.001), with high seasonal indexes in January, February and December, indicating certain seasonal characteristics. The optional model was ARIMA (1, 0, 0) (1, 1, 0)12, with the value of Akaike information criterion, corrected Akaike information criterion, and Bayesian information criterion being 727.38, 727.88 and 737.10, respectively. PM2.5 monthly average concentration in 2023 was fitted and compared with the actual values, with an absolute error range of 0.31-7.45 μg/m3, a relative error range of 0.01-0.53, and MAPE of 14.42%. PM2.5 monthly average concentration in Urumqi City from 2024 to 2025 was predicted to be consistent with the trend from 2016 to 2023. Conclusions PM2.5 concentration in Urumqi City showed a tendency towards a decline from 2016 to 2023, and was relatively high in winter. ARIMA (1, 0, 0) (1, 1, 0)12 can be used for short-term prediction of PM2.5 pollution in Urumqi City.

Objective To evaluate the clinical application value of matrix-assisted laser desorption ionization time-of-flight mass spectrometry(MALDI-TOF MS)in analyzing the homology of Acinetobacter baumannii(AB).Methods After excluding repetitive strains from multiple specimens of the same patient or environment,a total of 46 AB strains isolated from patients'sputum and environmental specimens of neurological intensive care unit(ICU)in a tertiary first-class general hospital from May 2020 to February 2021 were collected.Strains were detected by VITEK-MS mass spectrometer.Cluster analysis was performed by SARAMIS Premium software,and verified by multilocus sequence typing(MLST).Results Cluster analysis and comparison of MALDI-TOF MS and MLST found that among the 46 AB strains,39 were the type MS-a of MALDI-TOF MS,of which 22 strains were the clus-ter MT-A of MLST,including ST208(n=3),ST540(n=3),ST195(n=8),ST369(n=5),ST136(n=1),ST436(n=1)and ST1893(n=1);16 strains were MT-B,including type ST381(n=4),type ST469(n=11),and type ST938(n=1);one strain was cluster MT-C(ST1821);one strain of type MS-b was ST381;two strains of type MS-c were ST369;one strain of type MS-d was ST195;two strains of type MS-e were ST540 and ST369,respectively;one strain of type MS-f was STN1.Conclusion As a homology analysis method,MALDI-TOF MS still has certain limitations such as low consistency with MLST results,low resolution and specificity,thus cannot replace MLST technology.

Objective To observe the effectiveness of fluorescence labeling-based assay bundle intervention in the prevention and control of multidrug-resistant organism(MDRO)infection.Methods Patients who were detected MDRO in a hospital from January to December 2022 were selected as the research subjects.MDRO monitoring data and implementation status of prevention and control measures were collected.Fluorescence labeling assay was adopted to monitor the cleaning and disinfection effectiveness of the surrounding object surface of the bed units.Based on the bundled prevention and control measures as well as management mode of the pre-intervention group,the post-intervention group implemented enhanced rectification measures for the problems found by the pre-interven-tion group.Changes in relevant indicators between January-June 2022(before intervention)and July-December 2022(after intervention)were compared.Results There were 136 MDRO-infected patients in the pre-intervention group,208 MDRO strains were detected and 10 healthcare-associated infection(HAI)occurred.There were 128 MDRO-infected patients in the post-intervention group,198 MDRO strains were detected and 9 HAI occurred.Af-ter intervention,the total detection rates of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-re-sistant Acinetobacter baumannii(CRAB),and total MDRO from patients decreased significantly compared to before intervention(all P＜0.05).After intervention,the detection rates of MRSA,carbapenem-resistant Pseudomonas aeruginosa(CRPA),CRAB,and total MDRO from the surrounding object surface were all lower than those before intervention(all P＜0.05).The detection rate of MDRO from surrounding object surface before intervention was 34.52％,which showed a decreased trend after intervention(P＜0.05).The clearance rate of fluorescent labeled markers before intervention was 41.84％,which showed an upward trend after implementing intervention measures(from July to December),and increased to 85.00％at the end of intervention(November-December).The comp-liance rates of issuing isolation medical orders,placing isolation labels,using medical supplies exclusively,and cor-rectly handling medical waste after intervention have all increased compared to before intervention(all P＜0.05).Conclusion Adopting fluorescence labeling-based assay bundle intervention can effectively improve the effectiveness of MDRO infection prevention and control.

Aim To discover the potential active compounds and possible mechanisms in rheumatoid arthritis (RA) treatment with Zhi-Huang-Zhi-Tong powder (ZHZTP) by using network pharmacology and in vitro study. Methods The active ingredient targets and disease targets of Zhihuang Zhitong Powder were searched and screened by database; they intersected to get a common target; and the "drug-component-target" relationship network diagram was constructed for GO and KEGG enrichment analysis of the overlapping genes; then the core components were docked with the core targets. Finally, based on the inflammation model of HUVECs in vitro, the efficacy and mechanism of Zhihuang Zhitong powder were verified by MTT method, plate scratch test and Western blot. Results Active compounds involved in RA treatment were screened in the present study, and the top two were ursolic acid and emodin, all playing crucial roles in RA treatment with ZHZTP. Additionally, the key target was AKTA, TNF and IL-6. GO and KEGG enrichment analysis revealed that ZHZTP regulated BP, MF and CC, and also focused on regulating AKTA, TNF and IL-6 signaling pathway. Molecular docking showed that interactions between key active compounds and key targets were stable. In vitro ZHZTP significantly inhibited cell viability and migration of TNF-a-stimulated HUVECs, and the involved mechanism may be associated with PI3K/AKT/m-TOR signaling. Conclusions The present study reveals that the potential active compounds of ZHZTP are ursolic acid and emodin, and moreover, the involved mechanisms of ZHZTP for RA treatment are associated with PI3 K/AKT/m-TOR signaling.