Histone lactylation is a recently identified post-translational modification, wherein lactate mediates the enzymatic addition of lactyl groups to lysine residues on histones. Since its discovery, extensive research has demonstrated that histone lactylation is widely present in human tissues and plays a pivotal role in regulating the transcription of specific genes. Subsequent studies have further established this modification as a widespread epigenetic mark with significant physiological implications. With advancing research, accumulating evidence confirms that lactylation at distinct histone sites elicits diverse biological effects—such as promoting cell proliferation, driving inflammatory responses, and enhancing fibrosis—all of which profoundly influence disease progression and serve as key drivers of disease onset and development. Conversely, inhibiting histone lactylation can alter disease outcomes, positioning histone lactylation as a promising therapeutic target. Moreover, studies have revealed crosstalk between histone lactylation and other post-translational modifications, such as acetylation and methylation, which collectively regulate disease progression. Notably, lactylation occurs not only on histones but also on non-histone proteins. Histone lactylation activates specific gene transcription and reshapes metabolic epigenetics, while non-histone lactylation directly modulates enzyme activity, signal transduction, and protein stability. These two facets form a synergistic network through shared lactate pools, common modifying enzyme systems, and pathway crosstalk, thereby constructing a multi-dimensional regulatory framework—namely, the “histone lactylation-metabolism hub-non-histone lactylation” axis. This architecture bridges metabolism and epigenetics, and deciphering its topological structure may provide novel targets for precise intervention in diseases driven by lactate-mediated signaling hijacking. Traditional Chinese medicine (TCM), grounded in clinical practice, has been shown to regulate histone lactylation by modulating lactate metabolism and lactylation-related enzymes, thereby influencing disease progression. Moreover, certain TCM formulations exhibit potential as alternative therapies for drug-resistant diseases, underscoring the significance of further exploring TCM-mediated regulation of histone lactylation in future therapeutic strategies. This review aims to elucidate the mechanisms underlying histone lactylation, systematically delineate the associations between site-specific histone lactylation and various diseases, present a comprehensive landscape of the “lactate-histone lactylation and functional protein lactylation” axis, and summarize the mechanistic basis and research advances in TCM-mediated regulation of histone lactylation for disease treatment. Additionally, we discuss current challenges in histone lactylation research and propose future directions, ultimately aiming to deepen understanding and broaden perspectives on the roles and therapeutic potential of histone lactylation in disease.

OBJECTIVE: To explore the efficacy of a Thalassemia risk assessment software for the screening of thalassemia mutation carriers and distribution of thalassemia genotypes detected by screening. METHODS: A total of 6 040 individuals were evaluated at Leshan Maternal and Child Health Care Hospital between 2022 and 2024 using the commonly used clinical thalassemia risk assessment method and the thalassemia screening software, respectively, and the performance indicators of the two methods were compared and analyzed against the result of thalassemia gene testing. This study was approved by the Ethics Committee of our hospital (Ethics No.: LfyLL[2022]005). RESULTS: The high-risk rate by the thalassemia screening software was 11.19%, with a sensitivity of 95.12%, specificity of 93.28%, positive predictive value of 43.20%, negative predictive value of 99.72%, and the area under the ROC curve (AUC) was 0.942. The thalassemia gene detection rate of the high-risk samples screened was 4.83%. The high-risk screening rate of the conventional method was 2.50%, with a sensitivity of 51.22%, specificity of 93.28%, positive predictive value of 80.79%, negative predictive value of 97.40%, and the AUC was 0.754. The thalassemia gene detection rate of the high-risk samples was 2.02%. CONCLUSION The software can effectively detect thalassemia carriers and significantly reduce the missed detection compared with conventional method, thereby significantly improve the efficacy of screening.
Humans ; Thalassemia/diagnosis* ; Software ; Female ; Genetic Testing/methods* ; Male ; Mutation ; Adult ; Genotype ; ROC Curve ; Risk Assessment

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

To investigate the positivity rates of specific antibodies, including parietal cell antibody (PCA) and anti-inner factor antibody (IFA), in a community population in Xinjiang for autoimmune gastritis (AIG), determine the prevalence of AIG, and analyze the correlations of PCA and IFA with clinical characteristics, pepsinogen (PG), gastrin 17 (G17), and Helicobacter pylori antibody (Hp-Ab).

Colorectal cancer (CRC) is characterized by persistently high incidence and mortality. Current therapies are limited by drug resistance and modest patient benefit, underscoring the urgent need for new perspectives rooted in tumor biology. The unique metabolic landscape of CRC makes it an ideal model in which to dissect the pathological roles of lactylation regulatory networks: microsatellite-stable (MSS) CRC, which accounts for approximately 85% of cases, concurrently upregulates glycolysis and oxidative phosphorylation, engaging in intense metabolic competition with immune cells; the intratumoral lactate pool exhibits a distinctive “dual-source supply” feature—in addition to tumor-intrinsic glycolysis, substantial exogenous lactate is provided by gut microbiota dysbiosis and by colonizing bacteria within liver metastases; high-frequency oncogenic mutations and lactylation modifications establish a feed-forward circuit of “oncogene-driven lactate accumulation-lactylation-facilitated tumor progression”. Moreover, MSS CRC displays near-complete unresponsiveness to immune checkpoint inhibitors, a phenomenon underpinned by multiple immune evasion mechanisms mediated by lactate and lactylation. Lactate metabolism is a hallmark of metabolic reprogramming in cancer. Lactate homeostasis provides tumor cells with metabolic substrates, modulates redox status, and regulates fatty acid metabolism to promote malignant progression. Notably, lactate can drive lactylation—an emerging post-translational modification (PTM) in which lactyl groups are attached to lysine residues, dynamically governing gene transcription and protein function and thereby establishing a bridge between metabolism and epigenetics. Lactate and lactylation form a multidimensional, coordinated network: lactylation of key metabolic enzymes such as LDHA reinforces a positive feedback loop that sustains lactate production; lactylation of upstream transcription factors such as HIF-1α drives metabolic reprogramming; furthermore, lactylation engages in crosstalk with m6A and m5C RNA modifications as well as with other PTMs such as acetylation, profoundly reshaping cellular behavior. In CRC, histone lactylation drives malignant phenotypes by activating immunosuppressive programs, inhibiting ferroptosis, and promoting invasion and migration; non-histone lactylation accelerates translation elongation, stabilizes β‑catenin, maintains redox homeostasis, and prevents PD-L1 degradation, thereby facilitating tumor progression. Lactylation-related gene signatures have demonstrated potential for prognostic stratification. Therapeutic strategies targeting the lactylation network range from upstream metabolic intervention to modulation of the modifying enzymes and direct blockade of lactylation modifications, forming a hierarchical interventional framework. However, current evidence derives predominantly from cell lines and xenograft models, and a causal relationship between lactylation and malignant progression in CRC has yet to be rigorously established. Whether inhibition of lactylation can alter CRC phenotypes independently of metabolic alterations and acetylation fluctuations remains a central unanswered question in the field. This review systematically examines the research progress and translational challenges surrounding lactylation regulatory networks, aiming to provide a circumspect assessment to inform the development of novel therapeutic strategies for CRC.

Objective: Inflammatory cascade reactions play a crucial role in secondary neuronal injury in acute ischemic stroke (AIS). The aim of this study was to explore the correlations between specific serological indicators, early neurological deterioration (END), disease prognosis, and syndrome factors in AIS based on this injury mechanism. Methods: The data for this study were collected from 135 patients with AIS admitted to the emergency department of Fangshan Hospital, Beijing University of Chinese Medicine, within 24 h of onset between November 2019 and May 2021. Among these, 29 patients had complete data and experienced END. Additionally, 9 non-END patients were matched from the remaining 90 patients with complete data, resulting in a total of 38 patients for statistical analysis. Statistical methods, including logistic regression and receiver operating curves, were used to analyze the correlation between serum levels of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-10 (IL-10), vascular endothelial growth factor (VEGF), and intercellular adhesion molecule-1 (ICAM-1) within 24 h of END onset, disease prognosis, and syndrome factors. Grouping criteria included END occurrence, presence of syndrome elements on the first and third day post-onset, and prognosis at 90 days post-onset. Results: All 38 cases had onset time of less than 12 h, and there were no significant differences in age, gender, and onset time between the END and non-END groups. The TNF-α serum level within 24 h of onset was not associated with the occurrence of END but was negatively correlated with all-cause mortality at 90 days [0.110; P<0.05). An elevated IL-10 serum level within 24 h of onset showed a strong negative correlation with non-disabling and good functional outcomes at 90 days post-onset (0.110; P<0.05). When the ICAM-1 serum levels exceeded 233 599.500 μg/L and 125 141.500 μg/L, respectively, the susceptibility to endogenous wind and endogenous fire on the third day of onset was 15.364 times and 6.071 times higher, respectively, than that in patients with serum levels below these thresholds. Conclusion As accessible and objective biomarkers, inflammatory serum indicators are closely associated with both disease progression and traditional Chinese medicine (TCM) syndrome elements. They enhance AIS diagnosis, assessment, and treatment and contribute to a deeper understanding of the role of TCM syndrome differentiation in AIS diagnosis and treatment.

Objective:To explore the optimization potential of clinical target volume (CTV) delineation proposed in the guidelines of the Oncology Group (RTOG), the Francophone Group of Urological Radiotherapy (GFRU), and the European Society for Radiotherapy and Oncology (ESTRO) based on prostate bed local occurrence patterns after radical prostatectomy identified using prostate-specific membrane antigen positron emission tomography (PSMA PET).Methods:A retrospective analysis was conducted on patients with local prostate bed recurrence after radical prostatectomy who underwent PSMA PET at the Department of Nuclear Medicine, Peking University First Hospital from September 2021 to February 2024. The central point of each recurrence was marked. A six-zone method was established based on prostate bed anatomy and the characteristics of cross-sectional imaging. Then, the positional relationships (within or outside) were recorded with respect to recurrences and CTV defined by the RTOG, GFRU, and ESTRO (CTV RTOG, CTV GFRU, and CTV ESTRO), followed the analysis of the recurrence rates and distribution characteristics of various zones. Results:A total of 63 patients with prostate bed recurrence after radical prostatectomy were enrolled in this study, including 97 recurrences. The recurrence rates in the six zones were as follows: 10% of zone 1, 22% of zone 2, 29% of zone 3, 2% of zone 4, 12% of zone 5a, 18% of zone 5b, and 7% of zone 6. Among these zones, zones 2 and 3 showed the highest and second-highest recurrence rates, respectively. CTV GFRU and CTV ESTRO completely covered zones 2 and 3, while CTV RTOG covered zone 2 completely and zone 3 partially. Zone 4, characterized by a low recurrence rate, was not covered by CTV GFRU and CTV ESTRO but was entirely covered by CTV RTOG. Zone 5a, with a recurrence rate of 12%, was completely covered by CTV RTOG but was partially covered by CTV GFRU and CTV ESTRO. The range of 1.3 cm in front of the posterior wall of the bladder covered all recurrences in zone 5a. Conclusions:For CTV delineation of the prostate cancer surgical bed, zone 4, the anterior half of the bladder above the pubic symphysis midpoint, should be contracted due to the low recurrence rate in this zone. In contrast, the anterior boundary above the pubic symphysis midpoint should extend to 1.3 cm in front of the posterior wall of the bladder to completely cover the recurrence zones.

Objective:To analyze the short-term hospital-based transmission characteristics and gene variation of Carbapenem-Resistant Klebsiella pneumoniae (CRKP) by genome-wide technique to provide evidence for transmission control. Methods:The experimental strain was derived from all the CRKP isolated in Affiliated Hospital of North China University of Science and Technology from October 2022 to December 2023. Strain identification and drug susceptibility were tested with VITEK 2-Compact automatic bacterial identification drug susceptibility analyzer or disk method, and the results were interpreted through whole genome sequencing. The ST type, carbapenem resistance gene, virulence factor, and O serotype of the collected strains were analyzed.Results:Among the 115 strains of CRKP, 94 strains were isolated from the intensive care unit (ICU), accounting for 81.7%, and 21 strains were isolated from the non-intensive care unit (NICU), accounting for 18.3%. The 115 strains of CRKP can be divided into 11 ST types, of which ST11 type was the most (54.8%, 63/115), followed by ST15 type (22.6%, 26/115) and ST5492 type (15.7%, 18/115). Type ST5492 was a new clonal group in the region. The 115 strains of CRKP could be divided into 7 O serotypes, most of which were O2a type(32.2%,37/115), followed by O5 type(30.4%,35/115) and O1 type(27.8%,32/115). The resistance genes of carbapenem antibiotics showed that there were 107 strains carrying the blaKPC-2 gene, one strain with the blaNDM-1 gene, and one strain with both the blaKPC-2 and blaNDM-13 genes. Virulence genes were detected in 55 CRKP strains (47.8%, 55/115), among which six strains detected peg-344, iucA, iroB, rmpA, and rmpA2 virulence genes (5.2%, 6/115). Four virulence genes ( peg-344, iucA, rmpA, and rmpA2) were detected in 34 strains (29.6%, 34/115). Three virulence genes ( iucA, iroB and rmpA) were detected in two strains (1.7%, 2/115). Three virulence genes ( peg-344, iucA and rmpA) were detected in one strain (0.8%, 1/115). IucA and rmpA virulence genes were detected in 12 strains (10.4%, 12/115). KPC-2_ST11_O2a, KPC-2_ST15_O1 and KPC-2_ST5492_O5 were dominant clones, and their distribution was mainly in the intensive care unit. The whole genome sequence analysis showed that there were three dominant clones, among which ST11 clones were subdivided into three dominant O serotypes, all of which were mainly in the intensive care unit. Conclusion:The popular strain in the hospital of CRKP is a KPC-2_ST11 clone group carrying iucA, rmpA/rmpA2, with cross-department transmission and mutation. ST5492 is a newly-launched clone type. The intensive care unit of hvKP carrying five virulence genes, including peg-344, should be alert to the epidemic risk of CR-hvKP outbreak.

Objective:To analyze the carriage status, subtype distribution and flanking gene sequence characteristics of oxacillinases (OXA enzyme) in 241 clinical strains of Pseudomonas aeruginosa, and assess their roles in the drug resistance of Pseudomonas aeruginosa and ability to horizontally transfer across species. Methods:Clinical P. aeruginosa isolates were collected from four hospitals in Sanya, Tangshan, Zhangjiakou, and Beijing. The prevalence of oxacillinases and their flanking gene sequences was analyzed by whole-genome sequencing (NGS) and bioinformatic approaches. Results:A total of 241 isolates of P. aeruginosa were gathered, and 35 blaOXA subtypes were identified through screening of 252 blaOXA genes. These genes were classified into three subfamilies: blaOXA-50-like (241, 95.6%), blaOXA-1-like (9, 3.6%) and blaOXA-10-like (2, 0.8%). Among these, 11 subtypes (11, 31.4%) were novel blaOXA subtypes. Nine of these belonged to the blaOXA-50-like subfamily and were designated as blaOXA-1244, blaOXA-1245, blaOXA-1246, blaOXA-1250, blaOXA-1252, blaOXA-1253, blaOXA-1254, blaOXA-1255, and blaOXA-1256. The remaining two belonged to the blaOXA-10-like subfamily and were named blaOXA-1247 and blaOXA-1248. Compared to the amino acid sequence of OXA-10, the newly identified subtype OXA-1247 exhibited a mutation at position 117, where a valine was replaced by a leucine. This change was thought to improve the enzyme′s ability to hydrolyze carbapenems. In the analysis of the flanking sequences of the blaOXA genes, Class I integrons were identified in four bacterial strains. The variable regions of these integrons carried three distinct patterns of resistance gene cassettes: aac( 6′) -Ib-blaOXA-1247-ant( 3′′) -Ia, aac( 6′) -Ib-blaOXA-1248 and aac( 6′) -Ib- blaIMP-45-blaOXA-1-catB3. Among these, the strain BJ2326 carried a class I integron that was connected to the downstream IS CR1 element to form a composite class I integron structure, additionally carrying the resistance gene blaPER-1. Out of the 223 non-wild-type P. aeruginosa strains, 127 strains exhibited non-wild-type profiles to the four beta-lactam antibiotics MEM, CAZ, FEP, and TZP, with the combination of MEM+CAZ+FEP being the most prevalent, representing 57.0% of the total. Conclusions:The blaOXA genes in 241 clinical P. aeruginosa strains showed diversity. Some blaOXA genes had a co-transfer risk with the metallo-β-lactamase resistance gene blaIMP-45. Among the 11 newly discovered blaOXA subtypes, the new subtype OXA-1247 may have carbapenemase activity and potential for horizontal transfer.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.