The spine is the most common site of skeletal metastasis in lung cancer, which frequently leads to severe complications such as pathological fracture and neurological compromise and is associated with poor prognosis. The development and progression of spinal metastasis from lung cancer are linked to the unique local microenvironment and tumor microenvironment (TME) of the vertebral column. During metastatic evolution, the dense vascular network of the spine and a plethora of signaling molecules, together with the complex cellular constituents and their intricate interactions within the TME, all cooperate to facilitate the tumor invasion and colonization of the vertebral compartment. Mechanistic studies delineating the role of the TME in spinal metastasis from lung cancer have markedly expanded, fostering the emergence of innovative therapeutic strategies—including nanomedicines, sono-photodynamic therapy, gene therapy, and combination regimens. These strategies demonstrate remarkably potential for clinical translation and offer new directions for the precision management of spinal metastasis from lung cancer.

Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.

ObjectiveTo investigate the novel post-translational modifications (PTMs) of SnRK2.6, a central component in the abscisic acid (ABA) signaling pathway, such as SUMOylation, and to establish a foundation for revealing the physiological functions and molecular mechanisms of SnRK2.6 regulated by these new modifications. MethodsThe interaction between SnRK2.6 and the SUMO E3 ligase SIZ1, as well as members of the SUMO protease family, was examined using yeast two-hybrid and in vitro pull-down assays. An in vitro SUMOylation system in Escherichia coli was utilized to determine whether SnRK2.6 undergoes SUMOylation. Mass spectrometry, combined with site-directed mutagenesis of candidate lysine residues, was employed to identify potential SUMOylation sites on SnRK2.6. In vitro de-SUMOylation assays were performed to assess whether SUMO proteases interacting with SnRK2.6 could catalyze the removal of SUMO moieties from modified SnRK2.6. The protein stability of SnRK2.6 was assessed in a cell-free degradation assay using bacterial-purified SnRK2.6 incubated with total protein extracts from Col and siz1 mutant seedlings. To dissect the genetic relationship between SnRK2.6 and SIZ1, stomatal aperture assays were performed under ABA treatment using snrk2.6, siz1, and snrk2.6 siz1 double mutant plants. ResultsSnRK2.6 physically interacts with SIZ1 and the SUMO protease ESD4, with the binding domains localized to the C-terminal region of SIZ1 and the N-terminal region of ESD4, respectively. SnRK2.6 was found to be SUMOylated, exhibiting two distinct high-molecular-mass bands ranging from 70 to 100 ku, indicative of modified forms. Bioinformatics analysis predicted four putative SUMOylation sites on lysine residues K57, K63, K142, and K190. Mass spectrometry identified three SUMOylation sites on K63, K142, and K174. However, individual or combinatorial point mutations on these sites had minimal impact on the pattern or intensity of SUMOylation signals, suggesting that these residues may not be responsible for the SUMOylation on SnRK2.6. Instead, such mutations only weaken the protein stability or accelerate the protein mobility of SnRK2.6. Therefore, the exact SUMOylation sites on SnRK2.6 remain unidentified. In de-SUMOylation experiments, incubation of GST-ESD4 with SUMOylated SnRK2.6 for 1-2 h led to the near-complete disappearance of both SUMOylated bands. In contrast, neither the GST control nor the catalytically inactive mutant GST-ESD4^C448S exhibited any de-SUMOylation activity. In protein turnover experiments, SnRK2.6 exhibited markedly enhanced half-life in siz1 compared with Col, indicating that SIZ1-dependent SUMOylation promotes SnRK2.6 turnover. Phenotypically, snrk2.6 mutants were completely insensitive to ABA-induced stomatal closure; siz1 mutants displayed pronounced hypersensitivity; and the snrk2.6 siz1 double mutant phenocopied snrk2.6—showing no significant response to ABA beyond that of the snrk2.6 mutant. These data indicate that SIZ1 acts as a negative regulator of ABA-triggered stomatal closure and SnRK2.6 functions as a positive regulator, and the inhibitory activity of SIZ1 is strictly dependent on SnRK2.6, placing SnRK2.6 genetically upstream of SIZ1 in the ABA signaling pathway. ConclusionSnRK2.6 undergoes SUMOylation, although the specific SUMOylation sites have not been defined. SnRK2.6 is dynamically regulated by reversible SUMOylation—catalyzed by SIZ1 and reversed by ESD4—which controls its protein stability. SUMOylation acts as a destabilizing signal for SnRK2.6, and SIZ1 exerts its negative effect on ABA-triggered stomatal closure probably through promoting SnRK2.6 degradation via SUMOylation. These findings uncover SUMOylation as a critical regulatory layer fine-tuning SnRK2.6 abundance in ABA signaling.

Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.

Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.

Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

The study was aimed at identifying the diversity of tick species in selected areas of Qinghai,to analyze the genetic differentiation characteristics of tick-borne spotted fever group rickettsiae(SFGR),and to provide the theoretical basis for SFGR prevention and control in the region.The 16S rRNA gene was used for molecular biological identification of 446 collected tick samples,and the infection characteristics of SFGR in tick samples were determined according to the SFGR outer membrane protein A(ompA)gene.Haplotype analysis,phylogenetic tree construction,and estimation of differentiation times for SFGR were conducted in DNASP v6,IQ-tree v2.2.0,and BEAST v2.7.4 software.The obtained 446 tick samples belonged to three categories:(1)Haemaphy-salis spp.,including Haemaphysalis qinghaiensis(n=192)and H.danieli(n=37);(2)Dermacentor spp.,including Dermacentor ever-estianus(n=121),D.nuttalli(n=55),and D.silvarum(n=36);and(3)Hyalomma marginatum(n=5).Rickettsia raoultii was de-tected in D.everestianus,D.silvarum,D.nuttalli,H.qinghaiensis,and H.danieli,with infection rates of 95.9%,80.6%,69.1%,4.1%,and 2.7%,respectively.R.sibirica subsp.sibirica BJ-90 was found only in D.silvarum and D.nuttalli,with infection rates of 5.6%and 1.8%,respectively.The Candidatus R.gannanii F107 was found in H.danieli and H.qinghaiensis,with infection rates of 16.2%and 7.8%,respectively.Ca.R.hongyuanensis was detected only in H.qinghaiensis,with a prevalence of 16.3%.The prevalence of R.aeschlimannii was 20%and 2.7%in Hy.marginatum and H.danieli,respectively.Haplotype and nucleotide polymorphism analy-ses revealed 13 haplotypes in R.raoultii,with haplotype H13 as the dominant haplotype(42/192);seven haplotypes in Ca.R.ganna-nii F107,with haplotype H4 as the dominant haplotype(4/18);and three haplotypes in Ca.R.hongyuanensis,with haplotype H1 as the dominant haplotype(11/13).The phylogenetic tree indicated that the sequences of R.raoultii in selected areas of Qinghai and R.rhipicephali clustered into one branch;Ca.R.hongyuanensis and Ca.R.gannanii F107 clustered into one branch;and R.sibirica subsp.sibirica BJ-90 clustered into one branch with R.sibirica.Estimates of differentiation time revealed that the mean differentiation time for the six Rickettsia was approximately 2 000 Mya(95%CI:1 999.08-2 001.02 Mya).The tick species distributed in selected ar-eas of Qinghai are diverse,and this study provides the first report of Hy.marginatum in Qinghai Province.SFGR significantly varied in prevalence among tick species and showed high genetic diversity.