OBJECTIVE: To summarize the clinical and genetic characteristics of children with Silver-Russell syndrome (SRS) and improve the recognition of this disease. METHODS: A retrospective analysis was conducted on the clinical manifestations and genetic testing results of 29 children with SRS diagnosed at the Children's Hospital Affiliated to Zhengzhou University between March 2016 and June 2025. RESULTS: The 29 children had included 18 boys and 11 girls, with the age ranging from 2 months to 16 years. Their primary clinical manifestations included postnatal growth retardation (100%), small for gestational age (SGA) (100%), characteristic facial features (90%), limb asymmetry (83%), feeding difficulties (76%), ulnar deviation of the fifth finger (69%), body mass index (BMI) of < -2 SD (62%), and abnormal bone age (55%), including 15 cases with delayed bone age for an average of 1.5 years and 1 case with advanced bone age for 2.5 years. Additional manifestations included abnormal sexual development in 11 cases (38%), dental malocclusion in 11 cases (38%), allergic diseases in 10 cases (34%), cardiac diseases in 9 cases (31%), skeletal abnormalities in 7 cases (24%), renal hypoplasia in 5 cases (17%), and abnormal cranial MRI findings in 5 cases (17%). Twenty children were treated with recombinant human growth hormone (rhGH) at a dose of 0.1 ~ 0.15 U/(kg.d). Among them, 7 cases achieved annual height increase of ≥ 10 cm, 11 cases achieved annual height increase of ≥ 5 ~ 9 cm, and 2 cases achieved annual height increase < 5 cm. Twenty three children exhibited hypomethylation of imprinted genes in the chromosome region of 11p15, 4 presented maternal uniparental disomy of chromosome 7 [UPD(7)mat], and 2 had harbored nonsense variants of the HMGA2 gene. CONCLUSION SRS patients may present with diverse clinical manifestations including postnatal growth retardation, SGA, characteristic facial features, limb asymmetry, feeding difficulties, and ulnar deviation of the fifth finger. Most patients may exhibit abnormal methylation in the 11p15 region. rhGH therapy can improve the height of these patients.
Humans ; Silver-Russell Syndrome/diagnosis* ; Male ; Female ; Child ; Child, Preschool ; Infant ; Adolescent ; Retrospective Studies

Doxorubicin (Dox) is an anthracycline drug widely applied in various malignancies. However, the fatal cardiotoxicity induced by Dox limits its clinical application. Post-transcriptional protein modification via ubiquitination/deubiquitination in cardiomyocytes mediates the pathophysiological process in Dox-induced cardiotoxicity (DIC). In this study, we aimed to clarify the regulatory role and mechanism of a deubiquitinating enzyme, ubiquitin-specific peptidase 13 (USP13), in DIC. RNA-seq analysis and experimental examinations identified that cardiomyocyte-derived USP13 positively correlated with DIC. Mice with cardiac-specific deletion of USP13 were subjected to Dox modeling. Adeno-associated virus serotype 9 (AAV9) carrying cTNT promoter was constructed to overexpress USP13 in mouse heart tissues. Cardiomyocyte-specific knockout of USP13 exacerbated DIC, while its overexpression mitigated DIC in mice. Mechanistically, USP13 deubiquitinates the stimulator of interferon genes (STING) and promotes the autolysosome-related degradation of STING, subsequently alleviating cardiomyocyte inflammation and death. Our study suggests that USP13 serves a cardioprotective role in DIC and indicates USP13 as a potential therapeutic target for DIC treatment.

OBJECTIVES: To characterize the biological properties of double-negative T (DNT) cells isolated from leukoreduction filter residues. METHODS: Leukoreduction filters containing residues from 400 mL whole blood units (n=6) were collected from a blood center. Filters were back-flushed with normal saline, and the eluate was concentrated to obtain leukoreduction filter residues. Leukocytes in the residues were counted by dual-fluorescence staining. DNT cells were then isolated from the residues using antibody-mediated adsorption and density gradient centrifugation. Both cryopreserved and fresh unstimulated DNT cells derived from the residues were subjected to in vitro culture. Following culture, cells were assessed for expansion fold, viability, immunophenotype, differentiation status, and cytotoxicity against target cells using dual-fluorescence staining and flow cytometry, with comparisons made to DNT cells derived from whole blood. RESULTS: The leukocyte recovery rate achieved through reverse flushing of the leukocyte reduction filter was (41.9±14.7)%. Compared to whole blood, the DNT cell starting material obtained from filter residues showed no significant difference in total T-cell content (P>0.05). However, the viability and purity of the resulting DNT cell starting materials were significantly lower (both P<0.05). After 17 days of culture, DNT cells from filter residues and whole blood showed no significant differences in expansion fold, immunophenotype, differentiation status, or cytotoxicity toward target cells (all P>0.05). However, the viability of DNT cells from residues was significantly lower than that of whole blood-derived DNT cells [(86.0±4.2)% vs. (92.2±1.2)%, P<0.05]. After thawing (post 3 or 15 days of cryopreservation) and 17 days of culture, DNT cell starting materials from residues showed comparable immunophenotype, expansion fold, and differentiation status to their non-cryopreserved counterparts from the same source (all P>0.05). However, the viability of DNT cells cryopreserved for 3 days [92.4% (91.8%, 92.8%)] and the cytotoxicity against target cells of those cryopreserved for 15 days [91.3% (89.4%, 95.1%)] were significantly higher than those of non-cryopreserved DNT cells [87.8% (82.0%, 89.0%) and 70.9% (67.3%, 80.2%), respectively] (P<0.05). CONCLUSIONS DNT cells derived from leukoreduction filter residues exhibited highly comparable characteristics to those from whole blood in terms of expansion, purity, differentiation, and biological potency. Furthermore, their biological activity post-cryopreservation and revival remained largely similar to non-cryopreserved cells. These findings suggest that leukoreduction filter residues represent a promising alternative source of starting material for manufacturing off-the-shelf, allogeneic DNT cell therapeutics.

Medical cross-modal retrieval aims to achieve semantic similarity search between different modalities of medical cases, such as quickly locating relevant ultrasound images through ultrasound reports, or using ultrasound images to retrieve matching reports. However, existing medical cross-modal hash retrieval methods face significant challenges, including semantic and visual differences between modalities and the scalability issues of hash algorithms in handling large-scale data. To address these challenges, this paper proposes a Medical image Semantic Alignment Cross-modal Hashing based on Transformer (MSACH). The algorithm employed a segmented training strategy, combining modality feature extraction and hash function learning, effectively extracting low-dimensional features containing important semantic information. A Transformer encoder was used for cross-modal semantic learning. By introducing manifold similarity constraints, balance constraints, and a linear classification network constraint, the algorithm enhanced the discriminability of the hash codes. Experimental results demonstrated that the MSACH algorithm improved the mean average precision (MAP) by 11.8% and 12.8% on two datasets compared to traditional methods. The algorithm exhibits outstanding performance in enhancing retrieval accuracy and handling large-scale medical data, showing promising potential for practical applications.
Algorithms ; Semantics ; Humans ; Ultrasonography ; Information Storage and Retrieval/methods* ; Image Processing, Computer-Assisted/methods*

Online hashing methods are receiving increasing attention in cross modal medical image retrieval research. However, existing online methods often lack the learning ability to maintain semantic correlation between new and existing data. To this end, we proposed online semantic similarity cross-modal hashing (OSCMH) learning framework to incrementally learn compact binary hash codes of medical stream data. Within it, a sparse representation of existing data based on online anchor datasets was designed to avoid semantic forgetting of the data and adaptively update hash codes, which effectively maintained semantic correlation between existing and arriving data and reduced information loss as well as improved training efficiency. Besides, an online discrete optimization method was proposed to solve the binary optimization problem of hash code by incrementally updating hash function and optimizing hash code on medical stream data. Compared with existing online or offline hashing methods, the proposed algorithm achieved average retrieval accuracy improvements of 12.5% and 14.3% on two datasets, respectively, effectively enhancing the retrieval efficiency in the field of medical images.
Semantics ; Humans ; Algorithms ; Information Storage and Retrieval/methods* ; Diagnostic Imaging ; Image Processing, Computer-Assisted/methods*

Honey, a natural substance, has long been valued for its dual role in both food and medicine in diverse cultural traditions, particularly in traditional Chinese medicine (TCM). It is rich in sugars, amino acids, enzymes, polyphenols, and flavonoids that contribute to its antimicrobial, antioxidant, and immunomodulatory properties. Additionally, honey is effective in managing some conditions, such as antibiotic-resistant infections, inflammation, and oxidative stress-related diseases. This review explores the extensive health benefits of honey, emphasizing the homology between food and medicine, as proposed by TCM philosophy. Further, this review explores the traditional applications of honey in respiratory health, wound healing, and gastrointestinal support, along with modern scientific validation of these uses. Moreover, the role of honey as a dietary supplement, functional food, and preservative in culinary practices is examined. Overall, this review highlights the synergy between ancient wisdom and contemporary science, advocating for the continued exploration of the role of honey in health, nutrition, and medicine.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

Objective To establish an expert consensus on in-hospital transfer safety management for patients undergoing invasive mechanical ventilation,providing guidance for clinical medical teams to conduct standardized transfers,reduce transfer risks,and ensure patient safety.Methods Through systematic searching,screening,evaluation,and summary of evidence related to in-hospital transfer safety management for patients on invasive mechanical ventilation,we extracted recommendations to form a preliminary draft of the expert consensus.From July to October 2024,totally 2 rounds of expert consultations,and 2 rounds of expert reviews were conducted,and the content was refined and finalized based on expert feedback.Results The final consensus encompasses 9 aspects,including transfer assessment and decision-making,pre-transfer preparation of medical staff,pre-transfer patient preparation,pre-transfer equipment preparation,pre-transfer medication preparation,monitoring and intervention during transfer,emergency events and management,transfer handover and documentation,and post-transfer management.Conclusion This consensus demonstrates strong practicality and operability,offering professional guidance for enhancing the safety of in-hospital transfers for patients on invasive mechanical ventilation.

Objective To observe the value of multi-task improved nnU-Net model based on enhanced CT for segmenting primary oral cancer and predicting patients'relapse free survival(RFS).Methods Enhanced CT data of 186 cases of primary oral cancer were retrospectively analyzed,and a multi-task improved nnU-Net model was constructed for tumor segmentation and survival prediction tasks.Pre-training of tumor segmentation was completed with nnU-Net as the baseline network,and the accuracy of recognizing and segmenting tumor was improved by enhancing the decoder through the modified skip connection.Then univariable and multivariable regression analyses were used to select clinical features closely associated with RFS.Radiomics and deep learning features were also extracted to construct a survival prediction model,with fine-tuning of the above model.The training set,validation set and test set were divided at a ratio of 7∶2∶1.Dice similarity coefficient(DSC)was used to evaluate the segmentation performance of the modified model,and the consistency index C-index was used to verify the performance of the improved model for predicting RFS.Results DSC of the multi-task improved nnU-Net model(0.78)for segmenting primary oral cancer was superior to that of 3D Inception ResNet(0.65),3D InceptSENet(0.75)and 3D U-Net models(0.69),respectively,its C-index for predicting RFS(0.798)was higher than that of Cox regression model(0.744),ICARE model(0.761),random forest model(0.744),DeepSurv model(0.735),nnU-Net model(0.760)and radiology+nnU-Net model(0.744),respectively.DSC for segmenting primary oral cancer and C-index for predicting RFS of multi-task improved nnU-Net model were both superior to those of simple baseline network(0.653 and 0.649),baseline network+multi-scale convolution fusion(0.755 and 0.752),as well as baseline network combined with clinical features(0.764 and 0.759),radiomics features(0.770 and 0.764)and clinical+radiomics features(0.773 and 0.761),respectively.Conclusion Multi-task improved nnU-Net model could be used to effectively improve the accuracy of tumor segmentation and predicting patients'RFS.

OBJECTIVE To investigate the current status of monitoring indicators related to the"Perioperative In-fection Control"in medical institutions above the secondary level in Guizhou Province,and to delve into the imple-mentation of key measures for infection prevention and control during the perioperative period for patients under-going surgical operations.METHODS Based on the"Implementation Plan for the'Perioperative Infection Control'Initiative in Guizhou Province",a"Case Investigation Form on Key Measures for Infection Prevention and Control During the Perioperative Period for Patients Undergoing Surgical Operation"was developed.A total of 138 medi-cal institutions participated in the case investigation,and a total of 2 128 cases were investigated.RESULTS The overall monitoring indicators for the"Perioperative Infection Control"initiative in the 138 medical institutions a-bove the secondary level in Guizhou Province were at a relatively low level.The skin cleansing compliance rate was 80.32％,the hair removal compliance rate was 16.43％,the prophylactic antibacterial drug administration rate within 0.5-1 hour before surgery was 55.94％and the antibacterial drug discontinuation rate within 24 hours after prophylactic medication for type Ⅰ incision surgeries was 56.48％.The hair removal compliance rate was higher in tertiary medical institutions(19.21％)than in secondary medical institutions(14.34％)(P=0.039).The distri-bution of the four monitoring indicators varied in clinical departments and surgery types,with statistically signifi-cant differences(P＜0.05).The preferred method for surgical site skin cleansing in medical institutions across the province was local wiping,primarily with clean water(57.21％).The primary method for hair removal was razors(68.82％),and hair removal on the day of surgery was most common(61.75％).CONCLUSIONS Conduc-ting a survey on the current status of"Perioperative Infection Control"initiative monitoring indicators in medi-cal institutions in Guizhou Province helps to understand the implementation of key measures for perioperative in-fection prevention and control and set intervention targets,thus providing references for establishing a dynam-ic monitoring indicator change mechanism.