Cell-recruited microspheres for OA treatment by dual-modulating inflammatory and chondrocyte metabolism.

Osteoarthritis (OA) is a degenerative disease potentially exacerbated due to inflammation, cartilage degeneration, and increased friction. Both mesenchymal stem cells (MSCs) and pro-inflammatory macrophages play important roles in OA. A promising approach to treating OA is to modify multi-functional hydrogel microspheres to target the OA microenvironment and structure. Arginyl-glycyl-aspartic acid (RGD) is a peptide widely used in bioengineering owing to its cell adhesion properties, which can recruit BMSCs and macrophages. We developed TLC-R, a microsphere loaded with TGF-ß1-containing liposomes. The recruitment effect of TLC-R on macrophages and BMSCs was verified by in vitro experiments, along with its function of promoting chondrogenic differentiation of BMSCs. And we evaluated the effect of TLC-R in balancing OA metabolism in vitro and in vivo. When TLC-R was co-cultured with BMSCs and lipopolysaccharide (LPS)-treated macrophages, it showed the ability to recruit both cells in substantial numbers. As the microspheres degraded, TGF-ß1 and chondroitin sulfate (ChS) were released to promote chondrogenic differentiation of the recruited BMSCs, modulate chondrocyte metabolism and inhibit inflammation induced by the macrophages. Furthermore, in vivo analysis showed that TLC-R restored the narrowed space, reduced osteophyte volume, and improved cartilage metabolic homeostasis in OA rats. Altogether, TLC-R provides a comprehensive and novel solution for OA treatment by dual-modulating inflammatory and chondrocyte metabolism.

Directed Evolution of Acoustic Reporter Genes Using High-Throughput Acoustic Screening.

A major challenge in the fields of biological imaging and synthetic biology is noninvasively visualizing the functions of natural and engineered cells inside opaque samples such as living animals. One promising technology that addresses this limitation is ultrasound (US), with its penetration depth of several cm and spatial resolution on the order of 100 µm. Within the past decade, reporter genes for US have been introduced and engineered to link cellular functions to US signals via heterologous expression in commensal bacteria and mammalian cells. These acoustic reporter genes (ARGs) represent a novel class of genetically encoded US contrast agent, and are based on air-filled protein nanostructures called gas vesicles (GVs). Just as the discovery of fluorescent proteins was followed by the improvement and diversification of their optical properties through directed evolution, here we describe the evolution of GVs as acoustic reporters. To accomplish this task, we establish high-throughput, semiautomated acoustic screening of ARGs in bacterial cultures and use it to screen mutant libraries for variants with increased nonlinear US scattering. Starting with scanning site saturation libraries for two homologues of the primary GV structural protein, GvpA/B, two rounds of evolution resulted in GV variants with 5- and 14-fold stronger acoustic signals than the parent proteins. We anticipate that this and similar approaches will help high-throughput protein engineering play as large a role in the development of acoustic biomolecules as it has for their fluorescent counterparts.

Investigating the effect of dynamic traffic distribution on network-wide traffic emissions: An empirical study in Ningbo, China.

Urban road traffic is one of the primary sources of carbon emissions. Previous studies have demonstrated the close relationship between traffic flow characteristics and carbon emissions (CO2). However, the impact of dynamic traffic distribution on carbon emissions is rarely empirically studied on the network level. To fill this gap, this study proposes a dynamic network carbon emissions estimation method. The network-level traffic emissions are estimated by combining macroscopic emission models and recent advances in dynamic network traffic flow modeling, namely, Macroscopic Fundamental Diagram. The impact of traffic distribution and the penetration of battery electric vehicles on total network emissions are further investigated using the Monte Carlo method. The results indicate the substantial effect of network traffic distribution on carbon emissions. Using the urban expressway network in Ningbo as an example, in the scenario of 100% internal combustion engine vehicles, increasing the standard deviation of link-level traffic density from 0 to 15 veh/km-ln can result in an 8.9% network capacity drop and a 15.5% reduction in network carbon emissions. This effect can be moderated as the penetration rate of battery electric vehicles increases. Based on the empirical and simulating evidence, different expressway pollution management strategies can be implemented, such as petrol vehicle restrictions, ramp metering, congestion pricing, and perimeter control strategies.

WWP1 inhibition increases SHP2 inhibitor efficacy in colorectal cancer.

Protein tyrosine phosphatase SHP2 activates RAS signaling, which is a novel target for colorectal cancer (CRC) therapy. However, SHP2 inhibitor monotherapy is ineffective for metastatic CRC and a combination therapy is required. In this study, we aimed to improve the antitumor efficacy of SHP2 inhibition and try to explore the resistance mechanism of SHP2 inhibitor. Results showed that WWP1 promoted the proliferation of CRC cells. Genetic or pharmacological inhibition of WWP1 enhanced the effect of SHP2 inhibitor in suppressing tumor growth in vitro and in vivo. WWP1 may mediate feedback reactivation of AKT signaling following SHP2 inhibition. Furthermore, nomogram models constructed with IHC expression of WWP1 and SHP2 greatly improved the accuracy of prognosis prediction for patients with CRC. Our findings indicate that WWP1 inhibitor I3C can synergize with SHP2 inhibitor and is expected to be a new strategy for clinical trials in treating advanced CRC patients.

Mitofusin 2 inhibits high glucose-induced apoptosis of human lens epithelial cells via modulating mitochondrial function and autophagy.

INTRODUCTION: Diabetic cataract (DC) is a common ocular complication of diabetes. Mitofusin 2 (MFN2), a mitochondrial fusion protein, is involved in the pathogenesis of cataract and diabetic complications. However, its role and molecular mechanisms in DC remain unclear. MATERIALS AND METHODS: DC models in rats were induced by intraperitoneal injection of streptozocin (STZ) for 12 weeks. We measured the body weight of rats, blood glucose concentrations, sorbitol dehydrogenase (SDH) activity and advanced glycation end products (AGE) content in the lenses of rats. MFN2 mRNA and protein expression levels in the lenses were detected by RT-qPCR and western blot assays. In vitro, human lens epithelial (HLE) B3 cells were treated for 48 h with 25 mM glucose (high glucose, HG) to induce cell damage. To determine the role of MFN2 in HG-induced cell damage, HLE-B3 cells were transfected with lentivirus loaded with MFN2 overexpression plasmid or short hairpin RNA (shRNA) to overexpress or knock down MFN2 expression, followed by HG exposure. Cell viability was assessed by CCK-8 assay. Flow cytometry was used to detect cell apoptosis and reactive oxygen species (ROS) level. JC-1 staining showed the changes in mitochondrial membrane potential (Δψm). The mediators related to apoptosis, mitochondrial damage, and autophagy were determined. RESULTS: STZ-administrated rats showed reduced body weight, increased blood glucose levels, elevated SDH activity and AGE content, suggesting successful establishment of the DC rat model. Interestingly, MFN2 expression was significantly downregulated in DC rat lens and HG-induced HLE-B3 cells. Further analysis showed that under HG conditions, MFN2 overexpression enhanced cell viability and inhibited apoptosis accompanied by decreased Bax, cleaved caspase-9 and increased Bcl-2 expression in HLE-B3 cells. MFN2 overexpression also suppressed the mitochondrial damage elicited by HG as manifested by reduced ROS production, recovered Δψm and increased mitochondrial cytochrome c (Cyto c) level. Moreover, MFN2 overexpression increased LC3BⅡ/LC3BⅠ ratio and Beclin-1 expression, but decreased p62 level, and blocked the phosphorylation of mTOR in HG-treated HLE-B3 cells. In contrast, MFN2 silencing exerted opposite effects. CONCLUSIONS: Our findings indicate that MFN2 expression may be essential for preventing lens epithelial cell apoptosis during development of diabetic cataract.

The combination of detection and simulation for the distribution and sourcing of microplastics in Shing Mun River estuary, Hong Kong.

For the first time, combined detection and simulation was performed on microplastic (MP) debris in surface water, sediment, and oyster samples at ten coastal sites of Shing Mun River estuary, Hong Kong at different tidal conditions. The MP debris were extracted and detected using Fourier transform infrared (FT-IR) spectroscopy, and the simulation was conducted using Weather Research & Forecasting Model (WRF) / Regional Ocean Modelling System (ROMS) coupled hydro-dynamic modelling and the subsequent Lagrangian particle tracking. The results demonstrated the majority of polyethylene (with partial chlorine substitution) debris among all the MPs found, and great spatial and tidal variabilities of MP concentrations were observed. The combination of MP observation and simulations referred to the interpretation that a considerable percentage of MPs found in this study originated from South China Sea. Those MPs were probably transported to Tolo Harbour through sea currents and drifted inshore and offshore with tides. This study provided baseline measures of MP concentrations in Shing Mun River estuary and comprehensive understanding for how MPs transport and distribute within a dynamic estuarine system.

Transoceanic ships as a source of alien dinoflagellate invasions of inland freshwater ecosystems.

Ships' ballast water and sediments have long been linked to the global transport and expansion of invasive species and thus have become a hot research topic and administrative challenge in the past decades. The relevant concerns, however, have been mainly about the ocean-to-ocean invasion and sampling practices have been almost exclusively conducted onboard. We examined and compared the dinoflagellate cysts assemblages in 49 sediment samples collected from ballast tanks of international and domestic routes ships, washing basins associated with a ship-repair yard, Jiangyin Port (PS), and the nearby area of Yangtze River (YR) during 2017-2018. A total of 43 dinoflagellates were fully identified to species level by metabarcoding, single-cyst PCR-based sequencing, cyst germination and phylogenetic analyses, including 12 species never reported from waters of China, 14 HABs-causing, 9 toxic, and 10 not strictly marine species. Our metabarcoding and single-cyst sequencing also detected many OTUs and cysts of dinoflagellates that could not be fully identified, indicating ballast tank sediments being a risky repository of currently unrecognizable invasive species. Particularly important, 10 brackish and fresh water species of dinoflagellate cysts (such as Tyrannodinium edax) were detected from the transoceanic ships, indicating these species may function as alien species potentially invading the inland rivers and adjacent lakes if these ships conduct deballast and other practices in fresh waterbodies. Significantly higher numbers of reads and OTUs of dinoflagellates in the ballast tanks and washing basins than that in PS and YR indicate a risk of releasing cysts by ships and the associated ship-repair yards to the surrounding waters. Phylogenetic analyses revealed high intra-species genetic diversity for multiple cyst species from different ballast tanks. Our work provides novel insights into the risk of bio-invasion to fresh waters conveyed in ship's ballast tank sediments and washing basins of shipyards.

Establishment and risk factor assessment of the abnormal body temperature probability prediction model (ABTP) for dairy cattle.

The study aims to develop an abnormal body temperature probability (ABTP) model for dairy cattle, utilizing environmental and physiological data. This model is designed to enhance the management of heat stress impacts, providing an early warning system for farm managers to improve dairy cattle welfare and farm productivity in response to climate change. The study employs the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm to analyze environmental and physiological data from 320 dairy cattle, identifying key factors influencing body temperature anomalies. This method supports the development of various models, including the Lyman Kutcher-Burman (LKB), Logistic, Schultheiss, and Poisson models, which are evaluated for their ability to predict abnormal body temperatures in dairy cattle effectively. The study successfully validated multiple models to predict abnormal body temperatures in dairy cattle, with a focus on the temperature-humidity index (THI) as a critical determinant. These models, including LKB, Logistic, Schultheiss, and Poisson, demonstrated high accuracy, as measured by the AUC and other performance metrics such as the Brier score and Hosmer-Lemeshow (HL) test. The results highlight the robustness of the models in capturing the nuances of heat stress impacts on dairy cattle. The research develops innovative models for managing heat stress in dairy cattle, effectively enhancing detection and intervention strategies. By integrating advanced technologies and novel predictive models, the study offers effective measures for early detection and management of abnormal body temperatures, improving cattle welfare and farm productivity in changing climatic conditions. This approach highlights the importance of using multiple models to accurately predict and address heat stress in livestock, making significant contributions to enhancing farm management practices.

Development of a risk prediction model for radiation dermatitis following proton radiotherapy in head and neck cancer using ensemble machine learning.

PURPOSE: This study aims to develop an ensemble machine learning-based (EML-based) risk prediction model for radiation dermatitis (RD) in patients with head and neck cancer undergoing proton radiotherapy, with the goal of achieving superior predictive performance compared to traditional models. MATERIALS AND METHODS: Data from 57 head and neck cancer patients treated with intensity-modulated proton therapy at Kaohsiung Chang Gung Memorial Hospital were analyzed. The study incorporated 11 clinical and 9 dosimetric parameters. Pearson's correlation was used to eliminate highly correlated variables, followed by feature selection via LASSO to focus on potential RD predictors. Model training involved traditional logistic regression (LR) and advanced ensemble methods such as Random Forest and XGBoost, which were optimized through hyperparameter tuning. RESULTS: Feature selection identified six key predictors, including smoking history and specific dosimetric parameters. Ensemble machine learning models, particularly XGBoost, demonstrated superior performance, achieving the highest AUC of 0.890. Feature importance was assessed using SHAP (SHapley Additive exPlanations) values, which underscored the relevance of various clinical and dosimetric factors in predicting RD. CONCLUSION: The study confirms that EML methods, especially XGBoost with its boosting algorithm, provide superior predictive accuracy, enhanced feature selection, and improved data handling compared to traditional LR. While LR offers greater interpretability, the precision and broader applicability of EML make it more suitable for complex medical prediction tasks, such as predicting radiation dermatitis. Given these advantages, EML is highly recommended for further research and application in clinical settings.

Brain implantation of tissue-level-soft bioelectronics via embryonic development.

The design of bioelectronics capable of stably tracking brain-wide, single-cell, and millisecond-resolved neural activities in the developing brain is critical to the study of neuroscience and neurodevelopmental disorders. During development, the three-dimensional (3D) structure of the vertebrate brain arises from a 2D neural plate 1,2 . These large morphological changes previously posed a challenge for implantable bioelectronics to track neural activity throughout brain development 3-9 . Here, we present a tissue-level-soft, sub-micrometer-thick, stretchable mesh microelectrode array capable of integrating into the embryonic neural plate of vertebrates by leveraging the 2D-to-3D reconfiguration process of the tissue itself. Driven by the expansion and folding processes of organogenesis, the stretchable mesh electrode array deforms, stretches, and distributes throughout the entire brain, fully integrating into the 3D tissue structure. Immunostaining, gene expression analysis, and behavioral testing show no discernible impact on brain development or function. The embedded electrode array enables long-term, stable, brain-wide, single-unit-single-spike-resolved electrical mapping throughout brain development, illustrating how neural electrical activities and population dynamics emerge and evolve during brain development.

Measuring and modeling the dynamics of mitotic error correction.

Error correction is central to many biological systems and is critical for protein function and cell health. During mitosis, error correction is required for the faithful inheritance of genetic material. When functioning properly, the mitotic spindle segregates an equal number of chromosomes to daughter cells with high fidelity. Over the course of spindle assembly, many initially erroneous attachments between kinetochores and microtubules are fixed through the process of error correction. Despite the importance of chromosome segregation errors in cancer and other diseases, there is a lack of methods to characterize the dynamics of error correction and how it can go wrong. Here, we present an experimental method and analysis framework to quantify chromosome segregation error correction in human tissue culture cells with live cell confocal imaging, timed premature anaphase, and automated counting of kinetochores after cell division. We find that errors decrease exponentially over time during spindle assembly. A coarse-grained model, in which errors are corrected in a chromosome-autonomous manner at a constant rate, can quantitatively explain both the measured error correction dynamics and the distribution of anaphase onset times. We further validated our model using perturbations that destabilized microtubules and changed the initial configuration of chromosomal attachments. Taken together, this work provides a quantitative framework for understanding the dynamics of mitotic error correction.

Regulator of G protein signaling 16 restrains apoptosis in colorectal cancer through disrupting TRAF6-TAB2-TAK1-JNK/p38 MAPK signaling.

Colorectal cancer (CRC) remains a major global cause of cancer-related mortality, lacking effective biomarkers and therapeutic targets. Revealing the critical pathogenic factors of CRC and the underlying mechanisms would offer potential therapeutic strategies for clinical application. G protein signaling (RGS) protein family modulators play essential role within regulating downstream signaling of GPCR receptors, with function in cancers unclear. Our study focused on the expression patterns of RGS proteins in CRC, identifying Regulator of G protein signaling 16 (RGS16) as a prospective diagnostic and therapeutic target. Analyzing 899 CRC tissues revealed elevated RGS16 levels, correlating with clinicopathological features and CRC prognosis by immunohistochemistry (IHC) combined with microarray. We confirmed the elevated RGS16 protein level in CRC, and found that patients with RGS16-high tumors exhibited decreased disease-specific survival (DSS) and disease-free survival (DFS) compared to those with low RGS16 expression. Functional assays demonstrated that RGS16 promoted the CRC progression, knockdown of RGS16 led to significantly increased apoptosis rates of CRC in vitro and in vivo. Notably, we also confirmed these phenotypes of RGS16 in organoids originated from resected primary human CRC tissues. Mechanistically, RGS16 restrained JNK/P38-mediated apoptosis in CRC cells through disrupting the recruitment of TAB2/TAK1 to TRAF6. This study provides insights into addressing the challenges posed by CRC, offering avenues for clinical translation.

NOTCH3 as a prognostic biomarker and its correlation with immune infiltration in gastrointestinal cancers.

NOTCH receptor 3 (NOTCH3) is known to regulate the transcription of oncogenes or tumor suppressor genes, thereby playing a crucial role in tumor development, invasion, maintenance, and chemotherapy resistance. However, the specific mechanism of how NOTCH3 drives immune infiltration in gastrointestinal cancer remains uncertain. The expression of NOTCH3 was analyzed through Western blot, PCR, Oncomine database, and the Tumor Immune Estimation Resource (TIMER) site. Kaplan-Meier plotter, PrognoScan database, and gene expression profile interactive analysis (GEPIA) were used to assess the impact of NOTCH3 on clinical prognosis. The correlation between NOTCH3 expression and immune infiltration gene markers was investigated using TIMER and GEPIA. NOTCH3 was found to be commonly overexpressed in various types of gastrointestinal tumors and was significantly associated with poor prognosis. Furthermore, the expression level of NOTCH3 showed a significant correlation with the tumor purity of gastrointestinal tumors and the extent of immune infiltration by different immune cells. Our findings suggest that NOTCH3 may act as a crucial regulator of tumor immune cell infiltration and can serve as a valuable prognostic biomarker in gastrointestinal cancers.

Melanin Nanoparticle-Modified Probiotics for Targeted Synergistic Therapy of Ulcerative Colitis.

Ulcerative colitis (UC) is a recurrent chronic mucosal inflammation disease whose most significant pathological characteristics are intestinal inflammation and damaged mucosal barrier induced by reactive oxygen/nitrogen species, abnormal immune microenvironment, and intestinal microecological imbalance. Oral probiotics are a living therapy for intestinal diseases, but their clinical application is hindered by poor bacterial biological activity and insufficient intestinal retention. Here, we developed a targeted oral formulation, functionalized probiotic Lf@MPB, with Lactobacillus fermentum (Lf) as the core and modified melanin nanoparticles (MNPs) on its surface through a click reaction of tricarboxyphenylboronic acid for synergistic therapy of UC. In vitro experiments showed that Lf@MPB not only possessed strong free radical scavenging ability, reduced cellular mitochondrial polarization, and inhibited apoptosis but also significantly enhanced the viability of Lf probiotics in simulated gastrointestinal fluid. Fluorescence imaging in vivo revealed the high accumulation of Lf@MPB at the site of intestinal inflammation in dextran sulfate sodium-induced UC mice. Moreover, in vivo results demonstrated that Lf@MPB effectively alleviated oxidative stress and inflammatory response and restored the intestinal barrier. In addition, 16S rRNA gene sequencing verified that Lf@MPB could increase the abundance and diversity of intestinal microbial communities and optimize microbial composition to inhibit the progression of UC. This work combines effective antioxidant and anti-inflammatory strategies with the oral administration of functionalized probiotics to provide a promising alternative for UC treatment.

[Source Apportionment and Health Risk Assessment of Heavy Metals in Dust Around Bus Stops in Kaifeng City Based on APCS-MLR Model].

In order to reveal the influence of urban transportation systems on the quality of urban ecological environment, this study selected surface dust from bus stops, which is strongly disturbed by transportation, as the research object. The contents of eight heavy metals (V, Cr, Co, Ni, Cu, Zn, Cd, and Pb) in the dust were determined through inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectroscopy (ICP-ASE). The spatial distribution characteristics and pollution levels of the eight heavy metals in the dust were analyzed using the geo-accumulation index method. A combined qualitative (correlation analysis and principal component analysis) and quantitative (absolute principal component scores-multiple linear regression model (APCS-MLR)) method was used to explore the sources of heavy metals in surface dust near bus stops. The spatial distribution characteristics of heavy metals from different sources were elucidated using the Kriging interpolation method. The health risk assessment model proposed by the United States Environmental Protection Agency was used to evaluate the human health risks. The results showed that the average values of ω(V), ω(Cr), ω(Co), ω(Ni), ω(Cu), ω(Zn), ω(Cd), ω(Pb), and ω(As) in the bus stop surface dust were 68.36, 59.73, 5.81, 19.34, 40.10, 208.32, 1.01, and 49.46 mg·kg-1, respectively. The concentrations of heavy metals (Cd, Zn, Pb, Cu, and Cr) in the dust were all higher than the background values in the surrounding dust, exceeding them by 3.37, 2.70, 2.01, 1.95, and 1.28 times, respectively. The order of the geo-accumulation index for the eight heavy metals was Cd > Zn > Pb > Cu > Cr > V > Ni > Co, with Cd, Zn, Cu, and Pb in the dust indicating mild pollution levels and the others showing no pollution. The source analysis results showed that Cr, Co, and Ni were natural sources, whereas Cu, Zn, Pb, and Cd were traffic sources, and V was derived from a combination of industrial and natural sources. The APCS-MLR results indicated that the average contribution rates of the four sources were as follows:natural source (34.17 %), traffic source (29.84 %), industrial-natural mixed source (14.64 %), and unknown source (21.35 %). The spatial distribution map of the contribution rate of the traffic source was consistent with the trends of traffic volume and bus route density distribution. According to the health risk assessment, the cancer risk and non-cancer risk for children were both higher than those for adults. Cr was the main non-cancer factor, and Cd was the main cancer-causing factor. Natural and traffic sources contributed the most to non-cancer risk and cancer risk, respectively.

Linking the relationship between dietary folic acid intake and risk of osteoporosis among middle-aged and older people: A nationwide population-based study.

Among middle-aged and older people, balanced and nutritious diets are the foundation for maintaining bone health and preventing osteoporosis. This study is aimed at investigating the link between dietary folic acid intake and the risk of osteoporosis among middle-aged and older people. A total of 20,686 people from the National Health and Nutritional Examination Survey (NHANES) 2007-2010 are screened and included, and 5312 people aged ≥45 years with integral data are ultimately enrolled in evaluation. Demographics and dietary intake-related data are gathered and analyzed, and the odds ratio (OR) and 95% confidence interval (CI) of each tertile category of dietary folic acid intake and each unit increase in folic acid are assessed via multivariate logistic regression models. On this basis, the receiver operating characteristic (ROC) curve is used to identify the optimal cutoff value of dietary folic acid intake for indicating the risk of osteoporosis. Of 5312 people with a mean age of 62.4 ± 11.0 years old, a total of 513 people with osteoporosis are screened, and the dietary folic acid intake amount of the osteoporosis group is significantly lower than that of the non-osteoporosis group (p < .001). The lowest tertile category is then used to act as a reference category, and a higher dietary folic acid intake amount is observed to be positively related to lower odds for risk of osteoporosis. This trend is also not changed in adjustments for combinations of different covariates (p all < .05). Based on this, a dietary folic acid intake of 475.5 µg/day is identified as an optimal cutoff value for revealing osteoporosis. Collectively, this nationwide population-based study reveals that a higher daily dietary folic acid intake has potential protective effects on osteoporosis in middle-aged and older people.

Analysis of CCND3 mutations in diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL), accounts for 30-40% of newly diagnosed lymphomas, has an overall cure rate of approximately 60%. Despite previous reports suggesting a negative prognostic association between CCND3 mutations and Burkitt lymphoma, their prognostic implications in DLBCL remain controversial. To investigate this, we evaluated CCND3 mutation status in 2059 DLBCL patient samples from four database (integrated cohort) and additional 167 DLBCL patient samples in our center (JSPH cohort). The mutation was identified in 5.5% (113/2059) of the cases in the integrated cohort, with 86% (97/113) found in exon 5. Furthermore, P284, R271, I290 and Q276 are described as CCND3 mutation hotspots. CCND3 mutation was associated with decreased overall survival (OS) in the integrated cohort (P = 0.0407). Further subgroup analysis revealed that patients diagnosed as EZB subtype DLBCL by LymphGen algorithm with CCND3 mutations had poorer OS than patients diagnosed as EZB subtype without CCND3 mutations (P = 0.0140). Using the next-generation sequencing (NGS) in the JSPH cohort, it was found that both cell cycle and DNA replication pathways were highly upregulated in patients with CCND3 mutations. Our results suggest that CCND3 mutations can serve as a novel prognostic factor in DLBCL pathogenesis. Consequently, the development of personalized therapeutic strategies for DLBCL patients with CCND3 mutations might enhance their prognosis.

Comparison of Interstitial Lung Disease Between Antineutrophil Cytoplasmic Antibodies Positive and Negative Patients: A Retrospective Cohort Study.

OBJECTIVE: Positive antineutrophil cytoplasmic antibodies (ANCAs) may occur in the setting of interstitial lung disease (ILD), with or without ANCA-associated vasculitis (AAV). We aim to compare the characteristics and clinical course of patients with ILD and positive ANCA (ANCA-ILD) to those with negative ANCA. METHODS: We performed a single-center retrospective cohort study from 2018 to 2021. All patients with ILD and ANCA testing were included. Patient characteristics (symptoms, dyspnea scale, and systemic AAV), test results (pulmonary high-resolution computed tomography and pulmonary function tests), and adverse events were collected from electronic medical records. Descriptive statistics and the Fisher exact test were used to compare the outcomes of patients with ANCA-ILD to those with ILD and negative ANCA. RESULTS: A total of 265 patients with ILD were included. The mean follow-up duration was 69.3 months, 26 patients (9.8%) were ANCA positive, and 69.2% of those with ANCA-ILD had another autoantibody. AAV occurred in 17 patients (65.4%) with ANCA-ILD. In 29.4% of patients, AAV developed following ILD diagnosis. Usual interstitial pneumonia was the most common radiologic pattern in patients with ANCA-ILD. There was no association between ANCA status and the evolution of dyspnea, diffusing capacity of the lungs for carbon monoxide, and lung imaging. Forced vital capacity improved over time in 42% of patients with ANCA-ILD and in 17% of patients with negative ANCA (P = 0.006). Hospitalization occurred in 46.2% of patients with ANCA-ILD and in 21.8% of patients with negative ANCA (P = 0.006). Both groups had similar mortality rates. CONCLUSION: Routine ANCA testing should be considered in patients with ILD. Patients with ANCA-ILD are at risk for AAV. More research is required to better understand and manage patients with ANCA-ILD.

Influencing risk factors of voriconazole-induced liver injury in Uygur pediatric patients undergoing allogeneic hematopoietic stem cell transplantation.

PURPOSE: We aimed to investigated the influencing risk factors of voriconazole-induced liver injury in Uygur pediatric patients undergoing allogeneic hematopoietic stem cell transplantation (HSCT). METHODS: This was a prospective cohort design study. High-performance liquid chromatography-mass spectrometry was employed to monitor voriconazole concentration. First-generation sequencing was performed to detect gene polymorphisms. Indicators of liver function were detected at least once before and after voriconazole therapy. RESULTS: Forty-one patients were included in this study, among which, 15 patients (36.6%) had voriconazole-induced liver injury. The proportion of voriconazole trough concentration > 5.5 µg·mL-1 patients within the DILI group (40.0%) was significantly higher compared to the control group (15.4%) (p < 0.05). After administration of voriconazole, the values of ALT (103.3 ± 80.3 U/L) and AST (79.9 ± 60.6 U/L) in the DILI group were higher than that in the control group (24.3 ± 24.8 and 30.4 ± 8.6 U/L) (p < 0.05). There was no significant difference between the two groups in genotype and allele frequencies of CYP2C19*2, CYP2C19*3, CYP2C19*17, and UGT1A4 (rs2011425) (p > 0.05). CONCLUSION: There was a significant correlation between voriconazole-induced liver injury and voriconazole trough concentration in high-risk Uygur pediatric patients with allogeneic HSCT.

Diagnostic Role of Metagenomic Next-Generation Sequencing in Tubercular Orthopedic Implant-Associated Infection.

Objective: The diagnosis of tubercular orthopedic implant-associated infection (TB-IAI) is challenging. This study evaluated the value of metagenomic next-generation sequencing (mNGS) for the diagnosis of TB-IAI and developed a standardized diagnostic procedure for TB-IAI. Methods: The records of all patients with TB-IAI diagnosed and treated at our institution between December 2018 and September 2022 were retrospectively reviewed. Patient demographic characteristics, medical history, laboratory test, microbial culture, histopathology, and mNGS results, and time to diagnosis were recorded. The diagnostic efficiency of mNGS for TB-IAI was assessed by comparing the results and diagnostic time with that of other diagnostic modalities. Results: Ten patients were included in the analysis, including eight with prosthetic joint infections and two with fracture-related infections. The mNGS positivity rate was 100% (10/10), which was higher than that of TB-antibody (11%, 1/9), real-time quantitative polymerase chain reaction (22%, 2/9), T-SPOT.TB (25%, 2/8), purified protein derivative (50%, 4/8), microbial culture (50%, 5/10), and histopathology (20%, 2/10). mNGS shortened the time to diagnosis of TB-IAI. A standardized diagnostic procedure for TB-IAI was developed based on the findings. Conclusion: mNGS is useful for the diagnosis of TB-IAI. mNGS is recommended in cases where it is difficult to identify a pathogen using routine diagnostic tests. The standardized diagnostic procedure might improve TB-IAI diagnosis. Importance: TB-IAI is a rare infection, which occurs after orthopedic surgery and hard to diagnose microbiologically. mNGS is a new detection technique not yet discussed in current literature as a means for TB-IAI diagnostics. Here we describe a cohort of patients with TB-IAI diagnosed by mNGS show high efficiency of mNGS for detection of this pathology and present a clinical algorithm supplementing conventional methods for TB-IAI assessment.