A multicenter proof-of-concept study on deep learning-based intraoperative discrimination of primary central nervous system lymphoma.

Accurate intraoperative differentiation of primary central nervous system lymphoma (PCNSL) remains pivotal in guiding neurosurgical decisions. However, distinguishing PCNSL from other lesions, notably glioma, through frozen sections challenges pathologists. Here we sought to develop and validate a deep learning model capable of precisely distinguishing PCNSL from non-PCNSL lesions, especially glioma, using hematoxylin and eosin (H&E)-stained frozen whole-slide images. Also, we compared its performance against pathologists of varying expertise. Additionally, a human-machine fusion approach integrated both model and pathologic diagnostics. In external cohorts, LGNet achieved AUROCs of 0.965 and 0.972 in distinguishing PCNSL from glioma and AUROCs of 0.981 and 0.993 in differentiating PCNSL from non-PCNSL lesions. Outperforming several pathologists, LGNet significantly improved diagnostic performance, further augmented to some extent by fusion approach. LGNet's proficiency in frozen section analysis and its synergy with pathologists indicate its valuable role in intraoperative diagnosis, particularly in discriminating PCNSL from glioma, alongside other lesions.

Structural basis of human mpox viral DNA replication inhibition by brincidofovir and cidofovir.

Mpox virus has wildly spread over 108 non-endemic regions in the world since May 2022. DNA replication of mpox is performed by DNA polymerase machinery F8-A22-E4, which is known as a great drug target. Brincidofovir and cidofovir are reported to have broad-spectrum antiviral activity against poxviruses, including mpox virus in animal models. However, the molecular mechanism is not understood. Here we report cryogenic electron microscopy structures of mpox viral F8-A22-E4 in complex with a DNA duplex, or dCTP and the DNA duplex, or cidofovir diphosphate and the DNA duplex at resolution of 3.22, 2.98 and 2.79 Å, respectively. Our structural work and DNA replication inhibition assays reveal that cidofovir diphosphate is located at the dCTP binding position with a different conformation to compete with dCTP to incorporate into the DNA and inhibit DNA synthesis. Conformation of both F8-A22-E4 and DNA is changed from the pre-dNTP binding state to DNA synthesizing state after dCTP or cidofovir diphosphate is bound, suggesting a coupling mechanism. This work provides the structural basis of DNA synthesis inhibition by brincidofovir and cidofovir, providing a rational strategy for new therapeutical development for mpox virus and other pox viruses.

Considering microplastic characteristics in ecological risk assessment: A case study for China.

Microplastics (MPs) pose a significant global concern, requiring a multifaceted approach to their risk assessment procedures, especially concerning their characteristics in the environment. The Horqin Left Middle Banner in Northeast China was chosen for the research region to investigate the abundance, composition, distribution, and ecological impact of MPs in surface agricultural soils. The concentrations of MPs ranged from 300 to 12800 items/kg, with a median concentration of 1550 items/kg (average = 1994 items/kg). The normal-sized MPs (500-5000 µm) had a higher relative abundance than small MPs (<500 µm). MPs were mainly derived from textiles and packaging and were affected by atmospheric transportation. Rayon and PET fibers were the main polymers identified. Furthermore, the potential environmental risks posed by the fundamental characteristics (abundance, chemical composition, and size) of MPs were quantified using multiple risk assessment models. The conditional fragmentation model indicated a propensity for MPs to degrade into smaller particles. Ecological risk assessments using pollution load index, pollution hazard index, and potential ecological risk index models revealed varying levels of risk. This study conducted a comprehensive assessment of the ecological risks of MPs based on their environmental characteristics, emphasizing the importance of considering multiple factors in the risk assessment process. ENVIRONMENT IMPLICATION: This study investigates the occurrence, distribution, and ecological risk of microplastics (MPs) in agricultural soils of the Northeast Plain of China, a major food production area. MPs are persistent organic pollutants that can pose threats to soil health, crop quality, and food security. By analyzing the composition, size, and source of MPs, as well as their fragmentation and stability in soil, this study provides valuable data for assessing the environmental risk of MPs in agricultural regions. The study also suggests strategies for mitigating MPs pollution and protecting soil ecosystems.

Enhancement of doxorubicin production in Streptomyces peucetius by genetic engineering and process optimization.

Doxorubicin is an important class of anthracycline antitumor antibiotics produced by Streptomyces peucetius. The doxorubicin fermentation yield of the wild-type strain was very low, so it could not be produced directly by fermentation at an industrial scale due to the high cost. In the present study, S. peucetius SIPI-7-14 was obtained from SIPI-14 through several rounds of doxorubicin resistance screening. Then, the ketoreductase gene dnrU was knocked out to reduce (13S)-13-dihydrodaunorubicin production, and the resistance gene drrC was overexpressed to further enhance resistance to doxorubicin. The resulting engineered strain S. peucetius △U1/drrC produced 1128 mg/L doxorubicin, a 102.1% increase compared to that of SIPI-14. Then, fermentation medium was optimized using the response surface method. In the optimized fermentation medium, the yield of doxorubicin was increased to 1406 mg/L in shake flask on the 7th day. Furthermore, batch culture was carried out in a 10 L fermenter, and the concentration of doxorubicin reached 1461 mg/L after 7 days of culture, which was the highest yield reported to date, indicating the potential for industrial production of doxorubicin by fermentation.

Selective microRNA expression of exosomes from retinal pigment epithelial cells by oxidative stress.

The function of exosomal miRNAs (miRs) in retinal degeneration is largely unclear. We were aimed to investigate the functions of exosomes as well as their miRs derived from retinal pigment epithelial (RPE) cells following exposure to oxidative stress (OS). After the OS by lipopolysaccharide and rotenone on RPE cells, interleukin-1 beta (IL-1ß), Interleukin-6 (IL-6), Tumor Necrosis Factor-alpha (TNF-α) were upregulated, along with the decreased mitochondrial membrane potential and upregulated oxidative damage marker 8-OH-dG in RPE cells. RPE-derived exosomes were then isolated, identified, injected into the subretinal space in mice. After subretinal injection, RPE-exosomes after OS not only induced higher ROS level and apoptotic retinal cells, but also elevated IL-1ß, IL-6 alongside TNF-α expressions among retina/RPE/choroidal complex. Next, miRs inside the exosomes were sequenced by the next generation sequencing (NGS) technology. NGS revealed that certain miRs were abundant in exosomes, while others were selectively kept by RPE cells. Further, downregulated miRs, like miR-125b-5p, miR-125a-5p, alongside miR-128-3p, and upregulated miR, such as miR-7-5p were validated byRT-qPCR. Finally, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to find the possible target genes of those selective exosomal miRs. Our results proved that the RPE-derived exosomes after OS selectively express certain miRs, providing novel insights into the pathogenesis of age-related macular degeneration (AMD) in future.

A perspective of spatial variability and ecological risks of antibiotics in the agricultural-pastoral ecotone soils in eastern Inner Mongolia.

Antibiotics have garnered growing attention as pharmaceuticals ubiquitously present in human society. Within the soil environment, antibiotics exhibit a propensity for high environmental persistence, thereby posing a potential threat to the ecosystem. However, research on antibiotics in agricultural-pastoral ecotone soils is scarce. This study investigates the occurrence, distribution and risk of 11 common antibiotics in agricultural soils of the agro-pastoral transition zone in Horqin Left Middle Banner, eastern Inner Mongolia. The total concentration varies from not detectable to 609.62 µg/kg. Tetracyclines are the dominant antibiotic, with a higher detection frequency than Macrolides and Sulfonamides. The detection rates of the three types of antibiotics differ significantly. The study also finds that soil properties (organic matter content, pH, bulk density, clay, cation exchange capacity have no significant correlation with antibiotics in soil. Moreover, spatial regression analysis reveals that population density is the primary factor influencing the spatial distribution of antibiotics in soil. Ecological risk assessment shows that clarithromycin and erythromycin are the two most harmful factors in the ecological risk of agricultural soil.

Mapping trends and hotspots in research on global influenza vaccine hesitancy: A bibliometric analysis.

Background and Aims: Influenza is one of the most widespread respiratory infections and poses a huge burden on health care worldwide. Vaccination is key to preventing and controlling influenza. Influenza vaccine hesitancy is an important reason for the low vaccination rate. In 2019, Vaccine hesitancy was identified as one of the top 10 threats to global health by the World Health Organization. However, there remains a glaring scarcity of bibliometric research in that regard. This study sought to identify research hotspots and future development trends on influenza vaccine hesitation and provide a new perspective and reference for future research. Methods: We retrieved publications on global influenza vaccine hesitancy from the Web of Science Core Collection database, Scopus, and PubMed databases from inception to 2022. This study used VOSviewer and CiteSpace for visualization analysis. Results: Influenza vaccine hesitancy-related publications increased rapidly from 2012 and peaked in 2022. One hundred and nine countries contributed to influenza vaccine hesitation research, and the United States ranked first with 541 articles and 7161 citations. Vaccines-Basel was the journal with the largest number of published studies on influenza vaccine hesitations. MacDonald was the most frequently cited author. The most popular research topics on influenza vaccine hesitancy were (1) determinants of influenza vaccination in specific populations, such as healthcare workers, children, pregnant women, and so on; (2) influenza and COVID-19 vaccine hesitancy during the COVID-19 pandemic. Conclusions: The trend in the number of annual publications related to influenza vaccine hesitancy indicating the COVID-19 pandemic will prompt researchers to increase their attention to influenza vaccine hesitancy. With healthcare workers as the key, reducing vaccine hesitancy and improving vaccine acceptance in high-risk groups will be the research direction in the next few years.

Future land use simulation model-based landscape ecological risk prediction under the localized shared socioeconomic pathways in the Xiangjiang River Basin, China.

Landscape ecological risk (LER) is an effective index to identify regional ecological risk and measure regional ecological security. The localized shared socioeconomic pathways (LSSPs) can provide multi-scenario parameters of social and economic development for LER research. The research of LER under LSSPs is of scientific significance and practical value in curbing the breeding and spread of LER risk areas. In this study, land-cover raster files from 2010 to 2020 were used as the foundational data. Future land use simulation (FLUS), regression, and Markov chain models were used to predict the land cover patterns under the five LSSP scenarios in the Xiangjiang River Basin (XJRB) in 2030. Thus, an evaluation model was established, and the LER of the watershed was evaluated. We found that the rate of land cover change (LCC) in the XJRB between 2010 and 2020 had a higher intensity (increasing at an average of 18.89% per decade) than that projected under the LSSPs for 2020-2030 (averaging an increase of 8.58% per decade). Among the growth rates of all land use types in the XJRB, that of urban land was the highest (33.3%). From 2010 to 2030, the LER in the XJRB was classified as lower risk (33.73%), lowest risk (33.11%), and moderate risk (24.13%) for each decade. Finally, the LER exhibited significant heterogeneity among different scenarios. Specifically, the percentages of regions characterized by the highest (9.77%) and higher LER (9.75%) were notably higher than those in the remaining scenarios. The higher-level risk area under the localized SSP1 demonstrated a clear spatial reduction compared to those of the other four scenarios. In addition, in order to facilitate the differential management and control of LER by relevant departments, risk zoning was carried out at the county level according to the prediction results of LER. And we got three types of risk management regions for the XJRB under the LSSPs.

Highly anisotropic Fe3C microflakes constructed by solid-state phase transformation for efficient microwave absorption.

Soft magnetic materials with flake geometry can provide shape anisotropy for breaking the Snoek limit, which is promising for achieving high-frequency ferromagnetic resonances and microwave absorption properties. Here, two-dimensional (2D) Fe3C microflakes with crystal orientation are obtained by solid-state phase transformation assisted by electrochemical dealloying. The shape anisotropy can be further regulated by manipulating the thickness of 2D Fe3C microflakes under different isothermally quenching temperatures. Thus, the resonant frequency is adjusted effectively from 9.47 and 11.56 GHz under isothermal quenching from 700 °C to 550 °C. The imaginary part of the complex permeability can reach 0.9 at 11.56 GHz, and the minimum reflection loss (RLmin) is -52.09 dB (15.85 GHz, 2.90 mm) with an effective absorption bandwidth (EAB≤-10 dB) of 2.55 GHz. This study provides insight into the preparation of high-frequency magnetic loss materials for obtaining high-performance microwave absorbers and achieves the preparation of functional materials from traditional structural materials.

Angiogenic and Fibrogenic Dual-effect of Gremlin1 on Proliferative Diabetic Retinopathy.

Ocular angiogenic diseases, such as proliferative diabetic retinopathy (PDR), are often characterized by pathological new vessels and fibrosis formation. Anti-vascular endothelial growth factor (VEGF) therapy, despite of its efficiency to inhibit new vessels, has limitations, including drug resistance and retinal fibrosis. Here, we identified that Gremlin1, a novel angiogenesis and fibrosis inducer, was secreted from Müller glial cells, and its expression increased in the vitreous fluid from patients with PDR. Mechanistically, Gremlin1 triggered angiogenesis by promoting endothelial-mesenchymal transition via the EGFR/RhoA/ROCK pathway. In addition, Gremlin1 activated microglia to present profibrotic and fibrogenic properties. Further, anti-Gremlin1 antibody inhibited ocular angiogenesis and microglia fibrosis in mouse models. Collectively, Gremlin1 could be a potential therapeutic target in the treatment of ocular angiogenic diseases.

OHCCPredictor: an online risk stratification model for predicting survival duration of older patients with hepatocellular carcinoma.

BACKGROUND: Although the elderly constitute more than a third of hepatocellular carcinoma (HCC) patients, they have not been adequately represented in treatment and prognosis studies. Thus, there is not enough evidence to guide the treatment of such patients. The objective of this study is to identify the prognostic factors of older patients with HCC and to construct a new prognostic model for predicting their overall survival (OS). METHODS: 2,721 HCC patients aged ≥ 65 were extracted from the public database-Surveillance, Epidemiology, and End Results (SEER) and randomly divided into a training set and an internal validation set with a ratio of 7:3. 101 patients diagnosed from 2008 to 2017 in the First Affiliated Hospital of Zhejiang University School of Medicine were identified as the external validation set. Univariate cox regression analyses and multivariate cox regression analyses were adopted to identify these independent prognostic factors. A predictive nomogram-based risk stratification model was proposed and evaluated using area under the receiver operating characteristic curve (AUC), calibration curves, and a decision curve analysis (DCA). RESULTS: These attributes including age, sex, marital status, T stage, N stage, surgery, chemotherapy, tumor size, alpha-fetoprotein level, fibrosis score, bone metastasis, lung metastasis, and grade were the independent prognostic factors for older patients with HCC while predicting survival duration. We found that the nomogram provided a good assessment of OS at 1, 3, and 5 years in older patients with HCC (1-year OS: (training set: AUC = 0.823 (95%CI 0.803-0.845); internal validation set: AUC = 0.847 (95%CI 0.818-0.876); external validation set: AUC = 0.732 (95%CI 0.521-0.943)); 3-year OS: (training set: AUC = 0.813 (95%CI 0.790-0.837); internal validation set: AUC = 0.844 (95%CI 0.812-0.876); external validation set: AUC = 0.780 (95%CI 0.674-0.887)); 5-year OS: (training set: AUC = 0.839 (95%CI 0.806-0.872); internal validation set: AUC = 0.800 (95%CI 0.751-0.849); external validation set: AUC = 0.821 (95%CI 0.727-0.914)). The calibration curves showed that the nomogram was with strong calibration. The DCA indicated that the nomogram can be used as an effective tool in clinical practice. The risk stratification of all subgroups was statistically significant (p < 0.05). In the stratification analysis of surgery, larger resection (LR) achieved a better survival curve than local destruction (LD), but a worse one than segmental resection (SR) and liver transplantation (LT) (p < 0.0001). With the consideration of the friendship to clinicians, we further developed an online interface (OHCCPredictor) for such a predictive function ( https://juntaotan.shinyapps.io/dynnomapp_hcc/ ). With such an easily obtained online tool, clinicians will be provided helpful assistance in formulating personalized therapy to assess the prognosis of older patients with HCC. CONCLUSIONS: Age, sex, marital status, T stage, N stage, surgery, chemotherapy, tumor size, AFP level, fibrosis score, bone metastasis, lung metastasis, and grade were independent prognostic factors for elderly patients with HCC. The constructed nomogram model based on the above factors could accurately predict the prognosis of such patients. Besides, the developed online web interface of the predictive model provide easily obtained access for clinicians.

Utility of machine learning for identifying stapes fixation on ultra-high-resolution CT.

PURPOSE: Imaging diagnosis of stapes fixation (SF) is challenging owing to a lack of definite evidence. We developed a comprehensive machine learning (ML) model to identify SF on ultra-high-resolution CT. MATERIALS AND METHODS: We retrospectively enrolled 109 participants (143 ears) and divided them into the training set (115 ears) and test set (28 ears). Stapes mobility (SF or non-SF) was determined by surgical inspection. In the ML analysis, rectangular regions of interest were placed on consecutive axial slices in the training set. Radiomic features were extracted and fed into the training session. The test set was analyzed using 7 ML models (support vector machine, k nearest neighbor, decision tree, random forest, extra trees, eXtreme Gradient Boosting, and Light Gradient Boosting Machine) and by 2 dedicated neuroradiologists. Diagnostic performance (sensitivity, specificity and accuracy, with surgical findings as the reference) was compared between the radiologists and the optimal ML model by using the McNemar test. RESULTS: The mean age of the participants was 42.3 ± 17.5 years. The Light Gradient Boosting Machine (LightGBM) model showed the highest sensitivity (0.83), specificity (0.81), accuracy (0.82) and area under the curve (0.88) for detecting SF among the 7 ML models. The neuroradiologists achieved good sensitivities (0.75 and 0.67), moderate-to-good specificities (0.63 and 0.56) and good accuracies (0.68 and 0.61). This model showed no statistical differences with the neuroradiologists (P values 0.289-1.000). CONCLUSIONS: Compared to the neuroradiologists, the LightGBM model achieved competitive diagnostic performance in identifying SF, and has the potential to be a supportive tool in clinical practice.

Identification of genetic profile and biomarkers involved in acute respiratory distress syndrome.

PURPOSE: The purpose of this study was to profile genetic causal factors of acute respiratory distress syndrome (ARDS) and early predict patients at high ARDS risk. METHODS: We performed a phenome-wide Mendelian Randomization analysis through summary statistics of an ARDS genome-wide association study (1250 cases and 1583 controls of European ancestry) and 33,150 traits. Transcriptomic data from human blood and lung tissues of a preclinical mouse model were used to validate biomarkers, which were further used to construct a prediction model and nomogram. RESULTS: A total of 1736 traits, including 1223 blood RNA, 159 plasma proteins, and 354 non-gene phenotypes (classified by Biochemistry, Anthropometry, Disease, Nutrition and Habit, Immunology, and Treatment), exhibited a potentially causal relationship with ARDS development, which were accessible through a user-friendly interface platform called CARDS (Causal traits for Acute Respiratory Distress Syndrome). Regarding candidate blood RNA, four genes were validated, namely TMEM176B, SLC2A5, CDC45, and VSIG8, showing differential expression in blood of ARDS patients compared to controls, as well as dynamic expression in mouse lung tissues. Importantly, the addition of four blood genes and five immune cell proportions significantly improved the prediction performance of ARDS development, with 0.791 of the area under the curve from receiver-operator characteristic, compared to 0.725 for the basic model consisting of Acute Physiology and Chronic Health Evaluation (APACHE) III Score, sex, body mass index, bacteremia, and sepsis. A model-based nomogram was also developed for the clinical practice. CONCLUSION: This study identifies a wide range of ARDS relevant factors and develops a promising prediction model, enhancing early clinical management and intervention for ARDS development.

[Retracted] miR­141 inhibits prostatic cancer cell proliferation and migration, and induces cell apoptosis via targeting of RUNX1.

Following the publication of the above paper, a concerned reader drew to the Editor's attention that a number of plates showing colony formation assay data in Fig. 3A appeared to be overlapping, such that data purportedly showing the results from differently performed experiments may have been derived from the same original source(s); furthermore, certain of the cell­cycle histograms shown in Fig. 4B were duplicated, again where they were intended to have shown results obtained under different experimental conditions. Subsequently, following an independent enquiry in the office, it was also noted that, in Fig. 2B, the data shown for the RUNX1 western blots were apparently the same for both the DU145 and PC­2 cell lines. Although a corrigendum was requested by the authors, given the extent of the errors that were identified with respect to the compilation of as many as three of the figures in this paper, the Editor of Oncology Reports has decided that this article should be retracted from the publication owing to a lack of overall confidence in the presented data. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience that might result from the retraction of this article. [Oncology Reports 39: 1454­1460, 2018; DOI: 10.3892/or.2018.6209].

Comparative study of the sensitivity of ultra-high-resolution CT and high-resolution CT in the diagnosis of isolated fenestral otosclerosis.

PURPOSE: To compare the diagnostic sensitivity of ultra-high-resolution computed tomography (U-HRCT) and HRCT in isolated fenestral otosclerosis (IFO). METHODS: A retrospective analysis was conducted on 85 patients (85 ears) diagnosed with IFO between October 2020 and November 2022. U-HRCT (0.1 mm thickness) was performed for 20 ears, HRCT (0.67 mm thickness) for 45 ears, and both for 20 ears. The images were evaluated by general radiologists and neuroradiologists who were blinded to the diagnosis and surgical information. The diagnostic sensitivity of U-HRCT and HRCT for detecting IFO was compared between the two groups. RESULTS: Excellent inter-observer agreement existed between the two neuroradiologists (Cohen's κ coefficient 0.806, 95% CI 0.692-0.920), with good agreement between the general radiologists (Cohen's κ coefficient 0.680, 95% CI 0.417-0.943). U-HRCT had a sensitivity of 100% (40/40 ears) for neuroradiologists and 87.5% (35/40 ears) for general radiologists, significantly higher than HRCT (89.2% [58/65 ears] for neuroradiologists; 41.5% [27/65 ears] for general radiologists) (p = 0.042, p' < 0.000). General radiologists' sensitivity with HRCT was significantly lower compared to neuroradiologists (p < 0.000), but no significant difference was observed when general radiologists switched to U-HRCT (p = 0.152). Among the 20 ears that underwent both examinations, U-HRCT detected lesions smaller than 1 mm in 5 ears, whereas HRCT's sensitivity for neuroradiologists was 40% (2/5 ears), significantly lower than for lesions larger than 1 mm (93.3%, 14/15 ears, p = 0.032). CONCLUSION: U-HRCT exhibits higher sensitivity than HRCT in diagnosing IFO, suggesting its potential as a screening tool for suspected otosclerosis patients. CRITICAL RELEVANCE STATEMENT: Ultra-high-resolution computed tomography has the potential to become a screening tool in patients with suspected otosclerosis and to bridge the diagnostic accuracy gap between general radiologists and neuroradiologists. KEY POINTS: • U-HRCT exhibits higher sensitivity than HRCT in the diagnosis of IFO. • U-HRCT has a significant advantage in the detection of less than 1 mm IFO. • U-HRCT has the potential to be used for screening of patients with suspected otosclerosis.

EDDMF: An Efficient Deep Discrepancy Measuring Framework for Full-Reference Light Field Image Quality Assessment.

The increasing demand for immersive experience has greatly promoted the quality assessment research of Light Field Image (LFI). In this paper, we propose an efficient deep discrepancy measuring framework for full-reference light field image quality assessment. The main idea of the proposed framework is to efficiently evaluate the quality degradation of distorted LFIs by measuring the discrepancy between reference and distorted LFI patches. Firstly, a patch generation module is proposed to extract spatio-angular patches and sub-aperture patches from LFIs, which greatly reduces the computational cost. Then, we design a hierarchical discrepancy network based on convolutional neural networks to extract the hierarchical discrepancy features between reference and distorted spatio-angular patches. Besides, the local discrepancy features between reference and distorted sub-aperture patches are extracted as complementary features. After that, the angular-dominant hierarchical discrepancy features and the spatial-dominant local discrepancy features are combined to evaluate the patch quality. Finally, the quality of all patches is pooled to obtain the overall quality of distorted LFIs. To the best of our knowledge, the proposed framework is the first patch-based full-reference light field image quality assessment metric based on deep-learning technology. Experimental results on four representative LFI datasets show that our proposed framework achieves superior performance as well as lower computational complexity compared to other state-of-the-art metrics.

Maternal and neonatal outcomes of twin pregnancies complicated by gestational diabetes mellitus.

INTRODUCTION: Gestational diabetes mellitus (GDM) is associated with a higher risk of adverse maternal outcomes, but its effects on maternal and perinatal outcomes of twin pregnancies remain conflicting. METHODS: This retrospective cohort study included all primipara who delivered twin pregnancies at a single tertiary perinatal center between January 1, 2016 and December 31, 2022. Excluded were those who had a single pregnancy, twin pregnancies with pre-existing diabetes, missing information on GDM screening, a delivery before gestational 28 weeks, complications related to monochorionic placentation, multifetal reduction, fetal anomalies, and monochorionic monoamniotic twins. Maternal outcomes included preterm birth, pre-eclampsia, hypothyroidism, preterm premature rupture of membranes (PROM), placental abruption, severe postpartum hemorrhage, and oligohydramnios. Neonatal outcomes included small-for-gestational-age (SGA), large-for-gestational-age (LGA), birthweight, Apgar score, neonatal intensive care unit (NICU) admission, extrauterine growth restriction (EUGR), and neonatal hypoglycemia. RESULTS: A total of 3269 twins were delivered, with 897 women (27.4%) diagnosed with GDM during pregnancies; moreover, 72 (8.0%) of these women received insulin treatment. The GDM group showed a significantly higher maternal age at delivery (≥35 years), as well as incidences of overweight and obesity. These factors also elevated the odds of insulin treatment in GDM women with twin pregnancies (OR = 1.881, 95% CI = 1.073-3.295, P = 0.027; OR = 2.450, 95% CI = 1.422-4.223, P < 0.001; OR = 4.056, 95% CI = 1.728-9.522, P < 0.001, respectively). Chronic hypertension prior to pregnancy was identified as a risk factor for GDM during twin pregnancies (OR = 1.896, 95% CI = 1.290-2.785, P < 0.001), although it did not increase the proportion of women requiring insulin treatment (P = 0.808). Aside from a higher incidence of preterm birth before 37 weeks in insulin-treated GDM twins (OR = 2.096, 95% CI = 1.017-4.321, P = 0.045), there were no significant difference in other maternal outcomes (preterm birth before 34 weeks, pre-eclampsia, hypothyroidism, PROM, placental abruption, placenta previa, severe postpartum hemorrhage, and oligohydramnios) between the GDM group and non-GDM group, and between insulin-treated GDM and non-insulin-treated GDM. The rate of newborns with birthweight <1500 g was significantly lower among twins born to GDM women, but the prevalence of EUGR was notably higher. Additionally, the risk of EUGR was elevated in insulin-treated GDM twins (OR = 3.170, 95% CI = 1.639,6.131, P < 0.001). No significant differences were observed between the GDM group and non-GDM group, or between insulin-treated GDM and non-insulin-treated GDM group in terms of mean birthweight, newborn sex ratio, and incidences of other adverse neonatal outcomes, including gestational age at delivery, LGA, birth weight <2500 g, and 1-min and 5-min Apgar scores. CONCLUSION: Maternal age ≥35 years, overweight or obesity, and chronic hypertension are significant risk factors for GDM during twin pregnancies. Women with GDM during twin pregnancies may achieve similar outcomes compared to those without GDM. However, the women with GDM during twin pregnancies receiving insulin therapy may have a higher risk of preterm birth and EUGR.

Development and validation of a risk prediction model for osteoporosis in elderly patients with type 2 diabetes mellitus: a retrospective and multicenter study.

BACKGROUND: This study aimed to construct a risk prediction model to estimate the odds of osteoporosis (OP) in elderly patients with type 2 diabetes mellitus (T2DM) and evaluate its prediction efficiency. METHODS: This study included 21,070 elderly patients with T2DM who were hospitalized at six tertiary hospitals in Southwest China between 2012 and 2022. Univariate logistic regression analysis was used to screen for potential influencing factors of OP and least absolute shrinkage. Further, selection operator regression (LASSO) and multivariate logistic regression analyses were performed to select variables for developing a novel predictive model. The area under the receiver operating characteristic curve (AUROC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were used to evaluate the performance and clinical utility of the model. RESULTS: The incidence of OP in elderly patients with T2DM was 7.01% (1,476/21,070). Age, sex, hypertension, coronary heart disease, cerebral infarction, hyperlipidemia, and surgical history were the influencing factors. The seven-variable model displayed an AUROC of 0.713 (95% confidence interval [CI]:0.697-0.730) in the training set, 0.716 (95% CI: 0.691-0.740) in the internal validation set, and 0.694 (95% CI: 0.653-0.735) in the external validation set. The optimal decision probability cut-off value was 0.075. The calibration curve (bootstrap = 1,000) showed good calibration. In addition, the DCA and CIC demonstrated good clinical practicality. An operating interface on a webpage ( https://juntaotan.shinyapps.io/osteoporosis/ ) was developed to provide convenient access for users. CONCLUSIONS: This study constructed a highly accurate model to predict OP in elderly patients with T2DM. This model incorporates demographic characteristics and clinical risk factors and may be easily used to facilitate individualized prediction.

Crystal structure of the lipopolysaccharide outer core galactosyltransferase WaaB involved in pathogenic bacterial invasion of host cells.

Lipopolysaccharide (LPS) is essential for most gram-negative bacteria and plays an important role in serum resistance, pathogenesis, drug resistance, and protection from harsh environments. The outer core oligosaccharide of LPS is involved in bacterial recognition and invasion of host cells. The D-galactosyltransferase WaaB is responsible for the addition of D-galactose to the outer core oligosaccharide of LPS, which is essential for Salmonella typhimurium invasion. Here we report the first crystal structures of WaaB and WaaB in complex with UDP to resolutions of 1.8 and 1.9 Å, respectively. Mutagenesis and enzyme activity assays confirmed that residues V186, K195, I216, W243, E276, and E269 of WaaB are essential for the binding and hydrolysis of UDP-galactose. The elucidation of the catalytic mechanism of WaaB is of great importance and could potentially be used for the design of novel therapeutic reagents.

Potential of ultra-high-resolution CT in detecting osseous changes of temporomandibular joint: experiences in temporomandibular disorders.

BACKGROUND: Osseous changes of the temporomandibular joint (TMJ) are related to the progression of temporomandibular disorders (TMD), and computed tomography (CT) plays a vital role in disease evaluation. OBJECTIVE: The aims of this study were to evaluate the image quality and diagnostic value of ultra-high-resolution CT (U-HRCT) in TMD compared to cone-beam CT (CBCT). METHODS: TMD patients who underwent both CBCT and U-HRCT between November 2021 and September 2022 were retrospectively included. Image quality scores were assigned for four osseous structures (the cortical and trabecular bones of the condyle, articular eminence, and glenoid fossa) by two independent observers from Score 1 (unacceptable) to Score 5 (excellent). Diagnostic classification of TMD was categorized as follows: Class A (no evident lesion), Class B (indeterminate condition) and Class C (definitive lesion). Image quality scores and diagnostic classifications were compared between CBCT and U-HRCT. The Cohen's Kappa test, Wilcoxon signed-rank test, Chi-square test and Fisher's exact test were conducted for statistical analysis. RESULTS: Thirty TMD patients (median age, 30 years; interquartile range, 26-43 years; 25 females) with 60 TMJs were enrolled. Image quality scores were higher for U-HRCT than for CBCT by both observers (all Ps < 0.001). Definitive diagnoses (Class A and C) were achieved in more cases with U-HRCT than with CBCT (93.3% vs. 65.0%, Fisher's exact value = 7.959, P = 0.012). Among the 21 cases which were ambiguously diagnosed (Class B) by CBCT, definitive diagnosis was achieved for 17 cases (81.0%) using U-HRCT. CONCLUSIONS: U-HRCT can identify osseous changes in TMD, providing improved image quality and a more definitive diagnosis, which makes it a feasible diagnostic imaging method for TMD.