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Abstract Microplastics (MPs)-induced changes in soil nutrient cycling and microbial activity may pose a potential risk to soil ecosystem. Although some studies have explored these topics, there is still a large space for exploration and a relative lack of research on the mechanism by which soil health and its functions are affected by these changes. Thus, this study investigated the effects of polyethylene (PE) MPs with two particle sizes (13 μm and 130 μm) at five concentrations (0%, 1%, 3%, 6% and 10%, w/w) on soil biochemical properties and ecosystem function. The findings revealed that the exposure to 13 μm MPs significantly reduced soil respiration (Res) rate, β-glucosidase (Glu) and catalase (CAT) activity, which accompanied with enhanced urease activity and decreased soil pH, available phosphorus (AP), dissolved reactive phosphorus (DRP), dissolved organic carbon (DOC) and available potassium (AK) content in most cases. However, 130 μm MPs exerted negligible influence on the DOC and DRP content, Glu and CAT activity. High concentrations of 130 μm MPs significantly reduced soil pH, total dissolved nitrogen (TDN), AP and AK content, but significantly increased soil Res rate. Overall, soil ecosystem function was significantly reduced by the addition of MPs. The Res rate, soil AP and DRP content and Glu activity were the most important predictors of soil ecosystem function. We found that the risk posed by MPs to soil ecosystem function was dose-dependent and size-dependent. These findings underscore that MPs can alter soil functions related to soil nutrient cycling and provide further insights into MPs behavior in agroecosystems.

Abstract Background Cancer development is intricately linked with metabolic dysregulation, including lactic acid metabolism, which plays a pivotal role in tumor progression and immune evasion. However, its specific implications in gastric adenocarcinoma (STAD) remain unclear. This study introduces a novel methodology to evaluate lactic acid metabolism comprehensively in STAD, aiming to elucidate its prognostic significance and impact on immunotherapy efficacy. Targeted therapies directed at key lactic acid metabolism genes (LMGs) identified within the tumor microenvironment (TME) hold promise for personalized treatment strategies. Methods Lactic acid metabolism patterns were assessed in 415 STAD patients using a panel of 21 LMGs. Cox regression and Lasso regression analyses were employed to develop a predictive risk model based on differentially expressed genes (DEGs). Validation of the model was conducted using independent cohorts from the GEO and TCGA databases, as well as additional datasets focused on immunotherapy responses. Further investigations into TME dynamics of lactic acid metabolism included functional assays targeting SLC16A3, a pivotal gene identified through our analyses. Results Patients were stratified into distinct risk groups based on their lactic acid metabolism profiles. Low-risk patients exhibited attenuated lactic acid metabolism, correlating with favorable clinical outcomes characterized by prolonged survival and enhanced responsiveness to immunotherapy. Notably, tumor cells within the TME demonstrated heightened levels of active lactic acid metabolism, particularly impacting tumor-infiltrating lymphocytes such as CD8 + T cells and regulatory T cells. Mechanistically, SLC16A3 emerged as a critical regulator promoting STAD cell proliferation, invasion, and migration while modulating the metabolic landscape. Conclusion This study underscores the prognostic value of a lactic acid metabolism-based model in STAD, providing insights into its potential as a predictive biomarker for patient stratification and therapeutic targeting. The findings highlight SLC16A3 as a promising candidate for therapeutic intervention aimed at modulating lactic acid metabolism in the TME, thereby advancing personalized treatment strategies in gastric cancer management.

Societal Impact Statement Nitrogen, phosphorus, and potassium are essential elements for plant growth and are the primary nutrients in commercial fertilizers. However, the extent to which these nutrients individually limit plant growth is still unclear, as is the influence of their interactions. Using a meta‐analysis approach, plant growth was found to be co‐limited by nitrogen, phosphorus, and potassium. Furthermore, these findings demonstrate that multiple nutrient additions are primarily additive, with the exception of synergistic effects observed with NP additions on plant growth. These findings are important as they provide a timely and valuable reference for assessing the ecosystem‐scale consequences of increasing nutrient deposition caused by human activities. Summary Numerous field studies and a few meta‐analyses have confirmed that terrestrial primary production is individually or jointly limited by nitrogen (N) and phosphorus (P). Meanwhile, a recent synthesis emphasized that potassium (K) limitation in terrestrial ecosystems is more widespread than previously thought. However, it remains unclear whether N, P, and K co‐limit terrestrial production and how their interactions influence plant growth. Therefore, we conducted a globally comprehensive synthesis of a total 2877 observations to explore the individual and interactive effects of N, P, and K additions on plant growth. We found that N, P, K, NP, NK, PK, and NPK additions significantly increased aboveground biomass production (AGP) by 30.8%, 15.3%, 12.3%, 68.4%, 36.5%, 21.1%, and 78.7%, respectively. The combined addition of multiple nutrients resulted in a larger increase in AGP than a single addition of nutrients. These findings suggested that terrestrial production is widely co‐limited by N, P, and K. However, no significant responses of belowground biomass production (BGP) to nutrient additions were observed. Except for synergistic interactions between N and P additions, the responses of AGP to other pairs of nutrient additions were predominantly additive. This meta‐analysis highlights the importance of multiple‐nutrient limitation in regulating terrestrial primary production while pointing out that non‐additive effects (including synergistic and antagonistic) of multiple‐nutrient additions on terrestrial production are relatively rare.

Zhenbao pill (ZBP) has been shown to improve outcomes in spinal cord injury (SCI). However, its potential regulatory mechanisms in SCI remain to be elucidated. This study aimed to define the role of ZBP and its underlying molecular mechanisms in SCI, both in vitro and in vivo. Our findings indicated that ZBP ameliorated SCI by inhibiting neuronal apoptosis and the inflammatory response through the enhancement of miR-214-5p in vivo. In vitro, ZBP significantly reduced the levels of inflammatory factors, increased cell viability, and decreased apoptosis induced by oxygen–glucose deprivation (OGD)-activated microglia via miR-214-5p. Furthermore, the addition of miR-214-5p diminished the inflammatory response, enhanced cell viability, and suppressed apoptosis in OGD-treated microglia. We identified SRY-box transcription factor 4 (SOX4) as a potential target of miR-214-5p. Overexpression of SOX4 negated the effects of miR-214-5p on the inflammatory response, cell viability, and apoptosis in OGD-activated microglia. ZBP inhibited SOX4/β-catenin activation and reduced pro-inflammatory cytokine secretion by enhancing miR-214-5p in activated microglia. In summary, our findings demonstrate that ZBP mitigates SCI by inhibiting neuronal damage caused by activated microglia through the miR-214-5p/SOX4/β-catenin axis, providing valuable insights into the molecular basis of ZBP as a therapeutic agent for SCI.

Abstract Background Although low-dose computed tomography (LDCT) screening effectively reduces LC mortality in high-risk individuals with a history of smoking in China, the feasibility and efficacy of lung cancer screening (LCS) in individuals who never smoked versus individuals who smoked remains unclear. Methods We conducted a retrospective analysis of prospective cohort studies at the National Cancer Center (NCC) in China from January 2006 to December 2022. A comprehensive LCS initiative was undertaken, involving 30,468 participants (54.5% male). Participants underwent LCS using LDCT. Potential malignancies were managed through joint consensus between patients and their physicians. Epidemiology, screening eligibility criteria, and LC detection rates and survival outcomes were compared between individuals who smoked and individuals who never smoked. Results Among 30,468 participants, 339 LCs were pathologically confirmed in 289 patients. The LC detection rate was 0.9% (289/30,468) overall, 0.8% in individuals who smoked (71/9,042), and 1.0% in individuals who never smoked (218/21,426). In individuals who smoked, LC detection rates were 0.5% (21/4516) and 1.1% (50/4526) in the

Abstract Drug‐drug interaction (DDI) prediction is a crucial issue in molecular biology. Traditional methods of observing drug‐drug interactions through medical experiments require significant resources and labour. The authors present a Medical Knowledge Graph Question Answering (MedKGQA) model, dubbed MedKGQA, that predicts DDI by employing machine reading comprehension (MRC) from closed‐domain literature and constructing a knowledge graph of “drug‐protein” triplets from open‐domain documents. The model vectorises the drug‐protein target attributes in the graph using entity embeddings and establishes directed connections between drug and protein entities based on the metabolic interaction pathways of protein targets in the human body. This aligns multiple external knowledge and applies it to learn the graph neural network. Without bells and whistles, the proposed model achieved a 4.5% improvement in terms of DDI prediction accuracy compared to previous state‐of‐the‐art models on the QAngaroo MedHop dataset. Experimental results demonstrate the efficiency and effectiveness of the model and verify the feasibility of integrating external knowledge in MRC tasks.

Aims: This study aimed to assess the risk of acute kidney injury (AKI) associated with combined intravenous (IV) and topical antibiotic therapy in patients undergoing treatment for periprosthetic joint infections (PJIs) following total knee arthroplasty (TKA), utilizing the Kidney Disease: Improving Global Outcomes (KDIGO) criteria for classification. Methods: We conducted a retrospective analysis of 162 knees (162 patients) that received treatment for PJI post-TKA with combined IV and topical antibiotic infusions at a single academic hospital from 1 January 2010 to 31 December 2022. The incidence of AKI was evaluated using the KDIGO criteria, focussing on the identification of significant predictors and the temporal pattern of AKI development. Results: AKI was identified in 9.26% (15/162) of the cohort, predominantly presenting as stage 1 AKI, which was transient in nature and resolved prior to discharge. The analysis highlighted moderate anaemia and lower baseline serum creatinine levels as significant predictors for the development of AKI. Notably, the study found no instances of severe complications such as wound dehiscence, skin erosion, or the need for haemodialysis following treatment. Conclusion: The findings suggest that the combined use of IV and topical antibiotic therapy in the management of PJIs post-TKA is associated with a low incidence of primarily transient stage 1 AKI. This indicates a potentially favourable renal safety profile, advocating for further research to confirm these outcomes and potentially influence treatment protocols in PJI management. Cite this article: Bone Joint Res 2024;13(10):525–534.

Aims: The optimum type of antibiotics and their administration route for treating Gram-negative (GN) periprosthetic joint infection (PJI) remain controversial. This study aimed to determine the GN bacterial species and antibacterial resistance rates related to clinical GN-PJI, and to determine the efficacy and safety of intra-articular (IA) antibiotic injection after one-stage revision in a GN pathogen-induced PJI rat model of total knee arthroplasty. Methods: A total of 36 consecutive PJI patients who had been infected with GN bacteria between February 2015 and December 2021 were retrospectively recruited in order to analyze the GN bacterial species involvement and antibacterial resistance rates. Antibiotic susceptibility assays of the GN bacterial species were performed to screen for the most sensitive antibiotic, which was then used to treat the most common GN pathogen-induced PJI rat model. The rats were randomized either to a PJI control group or to three meropenem groups (intraperitoneal (IP), IA, and IP + IA groups). After two weeks of treatment, infection control level, the side effects, and the volume of antibiotic use were evaluated. Results: Escherichia coli was the most common pathogen in GN-PJI, and meropenem was the most sensitive antibiotic. Serum inflammatory markers, weightbearing activity, and Rissing score were significantly improved by meropenem, especially in the IA and IP + IA groups ( p < 0.05). Meropenem in the IA group eradicated E. coli from soft-tissue, bone, and prosthetic surfaces, with the same effect as in the IP + IA group. Radiological results revealed that IA and IP + IA meropenem were effective at relieving bone damage. Haematoxylin and eosin staining also showed that IA and IP + IA meropenem improved synovial inflammation and bone destruction. No pathological changes in the main organs or abnormal serum markers were observed in any of the meropenem-treated rats. The IA group required the lowest amount of meropenem, followed by the IP and IP + IA groups. Conclusion: IA-only meropenem with a two-week treatment course was effective and safe for PJI control following one-stage revision in a rat model, with less meropenem use. Cite this article: Bone Joint Res 2024;13(10):546–558.

Abstract Purpose To develop and validate a radiomic model for differentiating pulmonary invasive adenocarcinomas from benign lesions based on follow-up longitudinal CT images. Methods This is a retrospective study including 336 patients (161 with invasive adenocarcinomas and 175 with benign lesions) who underwent baseline (T0) and follow-up (T1) CT scans from January 2016 to June 2022. The patients were randomized in a 7:3 ratio into training and test sets. Radiomic features were extracted from lesion volumes of interest on longitudinal CT images at T0 and T1. Differences in radiomic features between T1 and T0 were defined as delta-radiomic features. Logistic regression was used to build models based on clinicoradiological (CR), T0, T1, and delta radiomic features and compute signatures. Finally, a nomogram based on the CR, T0, T1 and delta signatures was constructed. Model performance was evaluated for calibration, discrimination, and clinical utility. Results The T1 radiomic model was superior to the other independent models. In the training set, it had an area under the curve (AUC) of 0.858), superior to the CR model (AUC 0.694), the T0 radiomic model (AUC 0.825), and the delta radiomic model (AUC 0.734). In the test set, it had an AUC of 0.817, again outperforming the CR model (AUC 0.578), the T0 radiomic model (AUC 0.789), and the delta radiomic model (AUC 0.647). The nomogram incorporating the CR, T0, T1 and delta signatures showed the best predictive performance in both the training (AUC: 0.906) and test sets (AUC: 0.856), and it exhibited excellent fit with calibration curves. Decision curve analysis provided additional validation of the clinical utility of the nomogram. Conclusion A nomogram utilizing radiomic features extracted from longitudinal CT images can enhance the discriminative capability between pulmonary invasive adenocarcinomas and benign lesions.

Abstract The placenta, a temporary but essential organ for gestational support, undergoes intricate morphological and functional transformations throughout gestation. However, the spatiotemporal patterns of gene expression underlying placentation remain poorly understood. Utilizing Stereo-seq, we constructed a Mouse Placentation Spatiotemporal Transcriptomic Atlas (MPSTA) spanning from embryonic day (E) 7.5 to E14.5, which includes the transcriptomes of large trophoblast cells that were not captured in previous single-cell atlases. We defined four distinct strata of the ectoplacental cone, an early heterogeneous trophectoderm structure, and elucidated the spatial trajectory of trophoblast differentiation during early postimplantation stages before E9.5. Focusing on the labyrinth region, the interface of nutrient exchange in the mouse placenta, our spatiotemporal ligand–receptor interaction analysis unveiled pivotal modulators essential for trophoblast development and placental angiogenesis. We also found that paternally expressed genes are exclusively enriched in the placenta rather than in the decidual regions, including a cluster of genes enriched in endothelial cells that may function in placental angiogenesis. At the invasion front, we identified interface-specific transcription factor regulons, such as Atf3, Jun, Junb, Stat6, Mxd1, Maff, Fos, and Irf7, involved in gestational maintenance. Additionally, we revealed that maternal high-fat diet exposure preferentially affects this interface, exacerbating inflammatory responses and disrupting angiogenic homeostasis. Collectively, our findings furnish a comprehensive, spatially resolved atlas that offers valuable insights and benchmarks for future explorations into placental morphogenesis and pathology.

Abstract Defective renal excretion and increased production of uric acid engender hyperuricemia that predisposes to gout. However, molecular mechanisms underlying defective uric acid excretion remain largely unknown. Here, we report a rare genetic variant of gout-unprecedented NUMB gene within a hereditary human gout family, which was identified by an unbiased genome-wide sequencing approach. This dysfunctional missense variant within the conserved region of the NUMB gene (NUMBR630H) underwent intracellular redistribution and degradation through an autophagy-dependent mechanism. Mechanistically, we identified the uric acid transporter, ATP Binding Cassette Subfamily G Member 2 (ABCG2), as a novel NUMB-binding protein through its intracellular YxNxxF motif. In polarized renal tubular epithelial cells (RTECs), NUMB promoted ABCG2 trafficking towards the apical plasma membrane. Genetic loss-of-function of NUMB resulted in redistribution of ABCG2 in the basolateral domain and ultimately defective excretion of uric acid. To recapitulate the clinical situation in human gout patients, we generated a NUMBR630H knock-in mouse strain, which showed marked increases of serum urate and decreased uric acid excretion. The NUMBR630H knock-in mice exhibited clinically relevant hyperuricemia. In summary, we have uncovered a novel NUMB-mediated mechanism of uric acid excretion and a functional missense variant of NUMB in humans, which causes hyperuricemia and gout.

Abstract Background Fusarium head blight (FHB), a devastating disease of wheat production, is predominantly elicited by Fusarium graminearum (Fg). The tetraploid Thinopyrum elongatum is a tertiary gene resource of common wheat that possesses high affinity and displays high resistance traits against multiple biotic and abiotic stress. We aim to employ and utilize the novel FHB resistance resources from the wild germplasm of common wheat for breeding. Results Durum wheat-tetraploid Th. elongatum amphiploid 8801 was hybridized with common wheat cultivars SM482 and SM51, and the F5 generation was generated. We conducted cytogenetically in situ hybridization (ISH) technologies to select and confirm a genetically stable 7E(7D) substitution line K17-1069-5, which showed FHB expansion resistance in both field and greenhouse infection experiments and displayed no significant disadvantage in agronomic traits compared to their common wheat parents in the field. The F2 segregation populations (K17-1069-5 × SM830) showed that the 7E chromosome conferred dominant FHB resistance with dosage effect. We developed 19 SSR molecular markers specific to chromosome 7E, which could be conducted for genetic mapping and large breeding populations marker-assisted selection (MAS) during selection procedures in the future. We isolated a novel Fhb7 allele from the tetraploid Th. elongatum chromosome 7E (Chr7E) using homology-based cloning, which was designated as TTE7E-Fhb7. Conclusions In summary, our study developed a novel wheat-tetraploid Thinopyrum elongatum 7E(7D) K17-1069-5 substitution line which contains stable FHB resistance.

Abstract To analyze the risk factors of secondary Central nervous system infections (CNSIs) after craniotomy, and to establish an individualized predictive model for CNSIs risk. The independent risk factors were screened by univariate and multivariate logistic regression analysis. Logistic regression, naive bayes, random forest, light GBM and adaboost algorithms were used to establish predictive models for secondary CNSIs after craniotomy. The predictive model based on the Adaboost algorithm demonstrated superior prediction performance compared to the other four models. Under 5-fold cross validation, the accuracy was 0.80, the precision was 0.69, the recall was 0.85, the F1-score was 0.76, the area under the ROC curve was 0.897,and the average precision was 0.880. The top 5 variables of importance in Adaboost model were operation time, indwelling time of lumbar drainage tube, indwelling lumbar drainage tube during operation, indwelling epidural drainage tube during operation, and GCS score. In addition, Adaboost model with the best prediction performance was used for clinical verification, and the prediction results were compared with the actual occurrence of CNSIs after surgery. The results showed that the accuracy of Adaboost model in predicting CNSIs was 60%, the accuracy of Adaboost model in predicting non-CNSIS was 92%, and the overall prediction accuracy was 76%.

Abstract Bitter gourd wilt, a severe vascular disease triggered by the soilborne pathogen Fusarium oxysporum f. sp. momordicae (FOM), markedly constrains bitter gourd yield. In this study, a novel strain BF19 of Brevibacillus brevis was isolated and identified, exhibiting strong antimicrobial activity against FOM through in vivo and in vitro experiments. To comprehensively assess the biocontrol potential of strain BF19, we conducted phenotypic, phylogenetic, and comparative genomics analyses. Phenotypic analysis revealed that BF19 exhibited 53.33% biocontrol efficacy and significantly increased the average plant height, root fresh weight, and dry weight. Whole-genome sequencing and comparative genomic analysis revealed numerous potential genes associated with biocontrol mechanisms in BF19. Importantly, the integration of metabolic cluster prediction with liquid chromatography‒tandem mass spectrometry (LC‒MS/MS) revealed the presence of a macrobrevin antibiotic, a product of polyketide synthases (PKSs), predominantly in BF19 fermentation products. The effectiveness of the Br. brevis strain BF19 and its crude extract against bitter gourd wilt has also been confirmed. This study provides a genetic framework for future investigations on PKSs and establishes a scientific basis for optimizing field applications of microbial biopesticides derived from Br. brevis BF19.

Abstract Bract coloration is one of the key ornamental traits in Bougainvillea, yet research has predominantly focused on phenotypic color traits and pigment composition, with limited understanding of the molecular mechanisms underlying color formation. This gap hinders the improvement and innovation in bract coloration. To elucidate the regulatory mechanisms of bract coloration in Bougainvillea and to enhance the utilization of its germplasm resources, this study employed the Illumina Novaseq 6000 sequencing platform to conduct transcriptomic sequencing on 21 samples of bracts exhibiting seven distinct phenotypes. Comparative analysis against Nr, Pfam, EggNOG, GO, and KEGG databases annotated 90,279 unigenes. The highest annotation rates were achieved with the Nr (40.13%), GO (30.44%), and EggNOG (25.64%) databases. Among the species annotated, Beta vulgaris (20.08%) and Chenopodium quinoa (14.58%) shared the highest homology with Bougainvillea bract transcriptomes. WGCNA analysis identified 12 positively correlated tissue-specific modules, of which 2 are related to bract color formation. By comparing transcriptome data and genes within these specific modules against the KEGG database, a total of 321 unigenes associated with bract color formation in Bougainvillea were discovered. Among these, 220 unigenes are involved in anthocyanin synthesis, 43 unigenes are involved in betalain synthesis, 23 unigenes are annotated as Chlorophyll a-b binding protein genes, and 35 unigenes participate in carotenoid synthesis. Quantitative real-time PCR (qRT-PCR) validation of 16 differentially expressed genes (DEGs) including PAL2, CHS1, ANS, BZ1, 6GT, CDOPA5GT, ANR, CHS2, and DOPA, revealed significant expression differences among magenta, yellow, white, and cherry-colored bracts, suggesting their potential as candidate genes for bract color development. This study not only enriches the transcriptomic data of Bougainvillea but also identifies genes associated with bract coloration, providing a valuable theoretical basis for future gene cloning, genetic engineering, and breeding efforts in Bougainvillea.

Abstract Autophagy plays a dual role in coronavirus infection, facilitating the elimination of either proviral components (virophagy) or antiviral factors such as mitochondria (mitophagy), leading to complex mechanisms of immune evasion. Understanding the mechanisms that govern the switch between the autophagic degradation of deleterious or beneficial substrates in coronavirus infection is crucial for developing precise drug targets to treat virus-induced diseases. However, this switch remains largely unknown. Using a dual split-fluorescence assay, we identify PDPK1 as a negative regulator of innate immunity, directing the transition from virophagy to mitophagy through the phosphorylation of SQSTM1 at T138. Remarkably, a PDPK1-targeting peptide inhibits the replication of various RNA viruses by restoring innate immunity through enhanced virophagy and suppressed mitophagy, thereby protecting female mice from lethal infections. These findings underscore the detrimental role of PDPK1 in innate immunity by orchestrating the shift from virophagy to mitophagy, positioning PDPK1 as a promising pharmacological target for effectively combating a broad spectrum of virus infections.

Abstract Background Chimeric antigen receptor (CAR)-NK cell therapy has shown remarkable clinical efficacy and safety in the treatment of hematological malignancies. However, this efficacy was limited in solid tumors owing to hostile tumor microenvironment (TME). Radiotherapy is commonly used for solid tumors and proved to improve the TME. Therefore, the combination with radiotherapy would be a potential strategy to improve therapeutic efficacy of CAR-NK cells for solid tumors. Methods Glypican-3 (GPC3) was used as a target antigen of CAR-NK cell for hepatocellular carcinoma (HCC). To promote migration towards HCC, CXCR2-armed CAR-NK92 cells targeting GPC3 were first developed, and their cytotoxic and migration activities towards HCC cells were evaluated. Next, the effects of irradiation on the anti-tumor activity of CAR-NK92 cells were assessed in vitro and in HCC-bearing NCG mice. Lastly, to demonstrate the potential mechanism mediating the sensitized effect of irradiation on CAR-NK cells, the differential gene expression profiles induced by irradiation were analyzed and the expression of some important ligands for the NK-cell activating receptors were further determined by qRT-PCR and flow cytometry. Results In this study, we developed CXCR2-armed GPC3-targeting CAR-NK92 cells that exhibited specific and potent killing activity against HCC cells and the enhanced migration towards HCC cells. Pretreating HCC cells with irradiation enhanced in vitro anti-HCC effect and migration activity of CXCR2-armed CAR-NK92 cells. We further found that only high-dose (8 Gy) but not low-dose (2 Gy) irradiation in one fraction could significantly enhanced in vivo anti-HCC activity of CXCR2-armed CAR-NK92 cells. Irradiation with 8 Gy significantly up-regulated the expression of NK cell-activating ligands on HCC cells. Conclusions Our results indicate the evidence that irradiation could efficiently enhance the anti-tumor effect of CAR-NK cells in solid tumor model. The combination with radiotherapy would be an attractive strategy to improve therapeutic efficacy of CAR-NK cells for solid tumors.

Abstract Ultrasound technology has been recognized as the mainstream approach for the identification of gas-liquid two-phase flow patterns, which holds great value in engineering domain. However, commercial rigid probes are bulky, limiting their adaptability to curved surfaces. Here, we propose a strategy for autonomous identification of flow patterns based on flexible ultrasound array and machine learning. The array features high-performance 1–3 piezoelectric composite material, stretchable serpentine wires, soft Eco-flex layers and a polydimethylsiloxane (PDMS) adhesive layer. The resulting ultrasound array exhibits excellent electromechanical characteristics and offers a large stretchability for an intimate interfacial contact to curved surface without the need of ultrasound coupling agents. We demonstrated that the flexible ultrasound array combined with machine learning can accurately identify gas-liquid two-phase flow patterns, in a circular pipeline. This work presents an effective tool for recognizing gas-liquid two-phase flow patterns, offering engineering opportunities in petroleum extraction and natural gas transportation.

Abstract To tackle the clinical challenge of noninvasively assessing immunotherapy efficacy in patients, here we used positron emission tomography (PET) with 68Ga-grazytracer, which targets granzyme B, a crucial effector molecule secreted by activated CD8+ T cells. In this phase 1/2 clinical trial (NCT05000372) involving a diverse cohort of 24 patients with solid tumors and lymphomas who received immunotherapies, including immune checkpoint inhibitors (either alone or with chemotherapies) and chimeric antigen receptor-T cell therapy, we examined the in vivo behaviors of 68Ga-grazytracer. Primary endpoints were safety, biodistribution, granzyme B specificity, and the predictive utility of 68Ga-grazytracer, while secondary endpoint was the relationship between 68Ga-grazytracer uptake and tumor immune phenotype. 68Ga-grazytracer exhibited a safe profile and specifically targeted granzyme B in patients. 68Ga-grazytracer PET showed superior predictive value for short-term prognosis and progression-free survival than those of conventional assessment criteria, including RECIST 1.1 and PERCIST. Moreover, the uptake of 68Ga-grazytracer in tumors was significantly higher in those with a “non-desert” immune phenotype than those with an immune “desert” phenotype, thereby meeting the primary and secondary endpoints of this trial. Collectively, we successfully visualized CD8+ T cell effector function in humans using 68Ga-grazytracer PET, offering insights for enhancing immunotherapy assessment, patient stratification and treatment planning.

Abstract Background Streptococcus pneumoniae (S. pneumoniae) is a major cause of morbidity and mortality in children worldwide, and its evolving serotype distribution and antibiotic resistance patterns are of global health concern. This meta-analysis aims to investigate the serotype distribution and antimicrobial resistance of S. pneumoniae after the introduction of pneumococcal conjugate vaccine 13-valent (PCV13) as a self-funded vaccine in Chinese pediatric populations. Methods We systematically reviewed studies published between 2017 and 2024 that focused on S. pneumoniae serotypes isolated from children under 14 years old in mainland China. Data sources included PubMed, Embase, Web of Science, CNKI, Wanfang, and SinoMed. The findings were synthesized using either a fixed-effects or random-effects model. Results Our meta-analysis included 12 studies, identifying the most common serotypes of S. pneumoniae were 19 F, 19 A, 23 F, 14, 6B and 6 A. Vaccine serotype coverage rates were 52.17% (95%CI: 44.91-59.42%) for PCV10, 74.77% (95%CI: 71.53-78.01%) for PCV13, 76.72% (95%CI: 75.37-78.07%) for PCV15 and 92.90% (95%CI: 92.09-93.71%) for PPSV23. Antimicrobial resistance was most pronounced for erythromycin at 93.73% (95%CI: 90.58-96.88%), followed by azithromycin, tetracycline, clindamycin, and sulfamethoxazole. Serotype prevalence and vaccine coverage varied regionally and by strain type. Conclusion The distribution of S. pneumoniae serotypes and their antibiotic resistance profiles in children under 14 years in mainland China have remained relatively stable post-PCV13 introduction as a self-funded vaccine. The results support continued use and possible expansion of PCV13 immunization and highlight the importance of ongoing surveillance and vaccine development to cover all prevalent serotypes in China.

Abstract Aryl hydrocarbon receptor (AhR) plays an important role in inflammation and immunity as a new therapeutic target for infectious disease and sepsis. Punicalagin (PUN) is a Chinese herbal monomer extract of pomegranate peel that has beneficial anti-inflammatory, antioxidant and anti-infective effects. However, whether PUN is a ligand of AhR, its effect on AhR expression, and its signaling pathway remain poorly understood. In this study, we found that PUN was a unique polyphenolic compound that upregulated AhR expression at the transcriptional level, and regulated the AhR nongenomic pathway. AhR expression in lipopolysaccharide-induced macrophages was upregulated by PUN in vitro and in vivo in a time- and dose-dependent manner. Using specific inhibitors and siRNA, induction of AhR by PUN depended on sequential phosphorylation of 90-kDa ribosomal S6 kinase (p90RSK), which was activated by the mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) and phosphoinositide-dependent protein kinase (PDK)1 pathways. PUN promoted p90RSK-mediated activator protein-1 (AP-1) activation. AhR knockout or inhibitors reversed suppression of interleukin (IL)-6 and IL-1β expression by PUN. PUN decreased Listeria load and increased macrophage survival via AhR upregulation. In conclusion, we identified PUN as a novel selective AhR modulator involved in AhR expression via the MEK/ERK and PDK1 pathways targeting p90RSK/AP-1 in inflammatory macrophages, which inhibited macrophage inflammation and promoted bactericidal activity.

Abstract Wheat leaf rust, caused by Puccinia triticina (Pt), remains a constant threat to wheat production worldwide. Deployment of race-specific leaf rust (Lr) resistance genes in wheat provides effective protection against leaf rust, but often leads to selective pressures that drive the rapid emergence of new virulent Pt isolates in nature. However, the molecular mechanisms underlying the evasion of Lr-delivered resistance by leaf rust remain largely unknown. Here, we identify an avirulence gene AvrLr21 in Pt that triggers Lr21-dependent immune responses. BSMV (Barley stripe mosaic virus)-mediated host-induced gene silencing assay shows that silencing AvrLr21 compromises Lr21-mediated immunity. AvrLr21 interacts directly with Lr21 protein to induce a hypersensitive response in tobacco leaves. The evolved Lr21-breaking Pt isolates can suppress Lr21-mediated immunity. Our data provide a basis for studying the molecular determinants in Pt-wheat incompatible interaction and monitoring natural Pt populations to prioritize the deployment of Lr resistance genes in the field.

Abstract Background The reference values of eNO have certain differences among people of different countries and races. We aimed to obtain the reference value of eNO in healthy children and adolescents (6–18 years old) in China and to explore the associations between the reference values with ages, gender, heights, BMI, and regions. Methods We measured FeNO50 levels in 5949 healthy Chinese children and adolescents, FeNO200 and CaNO levels in 658 participants from 16 provinces of 7 administrative areas in China aged 6–18. All persons were studied after obtaining informed consent from children and their parents. Results The mean FeNO50 of 5949 Chinese children and adolescents aged 6–18 years was 14.1 ppb, with a 95% confidence interval of 1-38.1 ppb. The mean FeNO200 of 658 persons was 6.9 ppb with a 95% upper confidence interval of 15.0 ppb, and the mean CaNO was 3.0 ppb with a 95% upper confidence interval of 11.2 ppb. In the 6–11 age group, age and height were correlated with the logarithm of FeNO50 (P 0.05). The logarithm of CaNO was correlated with gender (P

Abstract The growing prevalence of mental health issues underscores the need for innovative screening methods. Large-scale, internet-based psychological screening has emerged as a vital tool to accurately determine morbidity rates and facilitate early diagnosis of mental disorders. However, conventional psychological screening methods often struggle with non-genuine responses and lack objective metrics. To bridge this gap, we have compiled a novel dataset derived from an expansive screening initiative at Xinxiang Medical University. The study, conducted from February 27 to March 17, 2021, yielded a dataset comprising responses from 24,292 students to four well-established psychological scales—PHQ-9, GAD-7, ISI, and PSS. A distinctive feature of this dataset is the inclusion of response time data, which captures the temporal dynamics of participants’ interactions with the scales, offering valuable insights into their response behaviour. The release of this dataset offers a substantial opportunity for researchers in the domains of psychology and public health to explore new insights into mental health, scale reliability, and the dynamics of psychological assessment.

Abstract Uterine arteriovenous malformation (UAM) is a rare medical condition. Even though UAM can cause abnormal and life-threatening uterine hemorrhage, there is no consensus on the clinical guideline on its treatments, most likely due to its low incidence, unknown etiology, and distinct fertility demands by different patients. Here, we present one elderly woman with uncommon UAM. We first discuss our experience regarding the diagnoses and treatments of UAM and then propose a hypothesis for the pathogenesis of UAM.

Abstract Purpose The purpose of this study was to investigate whether the vastus medialis oblique (VMO) muscle compensates in patellar dislocation (PD) patients with the increased femoral anteversion angle (FAA). Methods Between 2021 and 2024, we included 60 patients with recurrent PD (RPD group). Inclusion criteria were at least two episodes of PD, as well as complete CT scans of the knee and hip. Exclusion criteria included traumatic or habitual dislocation, previous knee surgery, etc. Of these patients, 30 with excessive FAA (≥ 30°) were assigned to the A group, and 30 without excessive FAA (

Abstract We investigate the parity-violating effects in primordial gravitational waves (GWs) due to null energy condition (NEC) violation in two very early universe scenarios: bounce-inflation and intermediate NEC violation during inflation. In both scenarios, we numerically solve the power spectra of parity-violating primordial GWs generated by coupling the background field and the spectator field with the Nieh-Yan term, respectively. We find that the background field can significantly enhance parity-violating effects at scales corresponding to the maximum of the GW power spectra. In contrast, the parity-violating effects produced by the spectator show significantly weaker observability even if the coupling constant is large. Therefore, in NEC-violating scenarios, the significant observable parity-violating effects in primordial GWs primarily arise from the physics directly related to NEC violation. This result highlights the potential of primordial GWs as crucial tools for exploring NEC-violating and parity-violating physics.

Abstract Background Black spot disease in tree peony caused by the fungal necrotroph A. alternata, is a primary limiting factor in the production of the tree peony. The intricate molecular mechanisms underlying the tree peony resistance to A. alternata have not been thoroughly investigated. Results The present study utilized high-throughput RNA sequencing (RNA-seq) technology to conduct global expression profiling, revealing an intricate network of genes implicated in the interaction between tree peony and A. alternata. RNA-Seq libraries were constructed from leaf samples and high-throughput sequenced using the BGISEQ-500 sequencing platform. Six distinct libraries were characterized. M1, M2 and M3 were derived from leaves that had undergone mock inoculation, while I1, I2 and I3 originated from leaves that had been inoculated with the pathogen. A range of 10.22–11.80 gigabases (Gb) of clean bases were generated, comprising 68,131,232 − 78,633,602 clean bases and 56,677 − 68,996 Unigenes. A grand total of 99,721 Unigenes were acquired, boasting a mean length of 1,266 base pairs. All these 99,721 Unigenes were annotated in various databases, including NR (Non-Redundant, 61.99%), NT (Nucleotide, 45.50%), SwissProt (46.32%), KEGG (Kyoto Encyclopedia of Genes and Genomes, 49.33%), KOG (clusters of euKaryotic Orthologous Groups, 50.18%), Pfam (Protein family, 47.16%), and GO (Gene Ontology, 34.86%). In total, 66,641 (66.83%) Unigenes had matches in at least one database. By conducting a comparative transcriptome analysis of the mock- and A. alternata-infected sample libraries, we found differentially expressed genes (DEGs) that are related to phytohormone signalling, pathogen recognition, active oxygen generation, and circadian rhythm regulation. Furthermore, multiple different kinds of transcription factors were identified. The expression levels of 10 selected genes were validated employing qRT-PCR (quantitative real-time PCR) to confirm RNA-Seq data. Conclusions A multitude of transcriptome sequences have been generated, thus offering a valuable genetic repository for further scholarly exploration on the immune mechanisms underlying the tree peony infected by A. alternata. While the expression of most DEGs increased, a few DEGs showed decreased expression.

Abstract Objective To evaluate the potential utility of 18F-FDG PET/CT to assess response to neoadjuvant immunochemotherapy in patients with resectable NSCLC, and the ability to screen patients who may benefit from neoadjuvant immunochemotherapy. Methods Fifty one resectable NSCLC (stage IA–IIIB) patients were analyzed, who received two-three cycles neoadjuvant immunochemotherapy.18F-FDG PET/CT was carried out at baseline(scan-1) and prior to radical resection(scan-2). SULmax, SULpeak, MTV, TLG, T/N ratio, ΔSULmax%,ΔSULpeak%, ΔMTV%, ΔTLG%,ΔT/N ratio% were calculated. 18F-FDG PET/CT responses were classified using PERCIST. We then compared the RECIST 1.1 and PERCIST criteria for response assessment.With surgical pathology of primary lesions as the gold standard, the correlation between metabolic parameters of 18F-FDG PET/CT and major pathologic response (MPR) was analyzed. All metabolic parameters were compared to treatment response and correlated to PFS and OS. Results In total of fifty one patients, MPR was achieved in 25(49%, 25/51) patients after neoadjuvant therapy. The metabolic parameters of Scan-1 were not correlated with MPR.The degree of pathological regression was negatively correlated with SULmax, SULpeak, MTV, TLG, T/N ratio of scan-2, and the percentage changes of the ΔSULmax%, ΔSULpeak%, ΔMTV%,ΔTLG%,ΔT/N ratio% after neoadjuvant therapy (p

Abstract Traditional Chinese medicine (TCM) is considered to be one of the most comprehensive and influential form of traditional medicine. It plays an important role in clinical treatment and adjuvant therapy for cancer. However, the complex composition of TCM presents challenges to the comprehensive and systematic understanding of its antitumor mechanisms, which hinders further development of TCM with antitumor effects. Omics technologies can immensely help in elucidating the mechanism of action of drugs. They utilize high-throughput sequencing and detection techniques to provide deeper insights into biological systems, revealing the intricate mechanisms through which TCM combats tumors. Multi-omics approaches can be used to elucidate the interrelationships among different omics layers by integrating data from various omics disciplines. By analyzing a large amount of data, these approaches further unravel the complex network of mechanisms underlying the antitumor effects of TCM and explain the mutual regulations across different molecular levels. In this study, we presented a comprehensive overview of the recent progress in single-omics and multi-omics research focused on elucidating the mechanisms underlying the antitumor effects of TCM. We discussed the significance of omics technologies in advancing research on the antitumor properties of TCM and also provided novel research perspectives and methodologies for further advancing this research field.

This study aimed to screen out the differential metabolites between Taigu yam and Tiegun yam by metabolomics approach, and determine differential markers for predicting different yam varieties through the east absolute shrinkage and selection operator (LASSO) regression method. Ultra-performance liquid chromatography-quadrupole time of flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS) was employed to analyze metabolites in two types of yams. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were applied to identify distinct metabolites in these two yam varieties. Additionally, the LASSO regression method was used to screen out differential markers and establish a prediction model for variety identification. The results showed that a total of 206 metabolites were identified in the two yams. PCA found that Taigu yam and Tiegun yam were clearly distinguished. OPLS-DA further screened out 56 differential metabolites. LASSO regression analysis was performed based on these differential metabolites, and five differential markers were obtained including ophiogenin 3-O-beta-L-rhamnopyranosyl-beta-D-glucopyranoside, aspartic acid, epicatechin gallate, schaftoside and gallocatechin. These differential markers were used to establish a LASSO regression prediction model for identification of Taigu yam and Tiegun yam varieties. Based on metabolomics and LASSO regression methods, this study identified differential markers between Taigu yam and Tiegun yam, constructed a prediction model to identify different yam varieties, and would provide new ideas for the identification of yam.

Abstract. Background:. Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors. Methods:. The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25–70 years old from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020. Results:. The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy. Conclusions:. We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.

Background: In the recent decade, there has been substantial progress in the technologies and philosophies associated with diagnosing and treating anterior cruciate ligament (ACL) injuries in China. The therapeutic efficacy of ACL reconstruction in re-establishing the stability of the knee joint has garnered widespread acknowledgment. However, the path toward standardizing diagnostic and treatment protocols remains to be further developed and refined. Objective: In this context, the Chinese Association of Orthopaedic Surgeons (CAOS) and the Chinese Society of Sports Medicine (CSSM) collaboratively developed an expert consensus on diagnosing and treating ACL injury, aiming to enhance medical quality through refining professional standards. Methods: The consensus drafting team invited experts across the Greater China region, including the mainland, Hong Kong, Macau, and Taiwan, to formulate and review the consensus using a modified Delphi method as a standardization approach. As members of the CSSM Lower Limb Study Group and the CAOS Arthroscopy and Sports Medicine Study Group, invited experts concentrated on two pivotal issues: “Graft Selection” and “Clinical Outcome Evaluation” during the second part of the consensus development. Results: This focused discussion ultimately led to a strong consensus on nine specific consensus terms. Conclusion: The consensus clearly states that ACL reconstruction has no definitive “gold standard” graft choice. Autografts have advantages in healing capability but are limited in availability and have potential donor site morbidities; allografts reduce surgical trauma but incur additional costs, and there are concerns about slow healing, quality control issues, and a higher failure rate in young athletes; synthetic ligaments allow for early rehabilitation and fast return to sport, but the surgery is technically demanding and incurs additional costs. When choosing a graft, one should comprehensively consider the graft's characteristics, the doctor's technical ability, and the patient's needs. When evaluating clinical outcomes, it is essential to ensure an adequate sample size and follow-up rate, and the research should include patient subjective scoring, joint function and stability, complications, surgical failure, and the return to sport results. Medium and long-term follow-ups should not overlook the assessment of knee osteoarthritis.

Urban vegetation in China has changed substantially in recent decades due to rapid urbanization and dramatic climate change. Nevertheless, the spatial differentiation of greenness among major cities of China and its evolution process and drivers are still poorly understood. This study examined the spatial patterns of vegetation greenness across 289 cities in China in 2000, 2005, 2010, 2015, and 2018 by using spatial autocorrelation analysis on the Normalized Difference Vegetation Index (NDVI); then, the influencing factors were analyzed by using the optimal parameters-based geographical detector (OPGD) model and 18 natural and anthropogenic indicators. The findings demonstrated a noticeable rise in the overall greenness of the selected cities during 2000–2018. The cities in northwest China and east China exhibited the rapidest and slowest greening, respectively, among the six sub-regions. A significant positive spatial correlation was detected between the greenness of the 289 cities in different periods, but the correlation strength weakened over time. The hot and very hot spots in southern and eastern China gradually shifted to the southwest. While the spatial pattern of urban greenness in China is primarily influenced by wind speed (WS) and precipitation (PRE), the interaction between PRE and gross domestic product (GDP) has the highest explanatory power. The explanatory power of most natural factors decreased and, conversely, the influence of anthropogenic factors generally increased. These findings emphasize the variations in the influence strength of multiple factors on urban greenness pattern, which should be taken into account to understand and adapt to the changing urban ecosystem.

Turbine blades are mainly subjected to thermal stress and gradient centrifugal stress in operational conditions. The effects of centrifugal stress on the microstructural degradation of single crystal superalloys under a multiaxial stress state remain unclear. Here, the NiAlReRu component was exposed to high-speed rotation at 20,000 rpm and a high temperature of 1000 °C for 100 h. The analysis indicates that the centrifugal stress causes the distortion of dendrite stems and the aggregation of micropores. The centrifugal stress promotes the formation of interfacial dislocation networks, accompanied by more severe rafting of γ′ phases. These findings provide a comprehensive experimental understanding of the microstructural evolution under simulated turbine blade working conditions, which provides a reference for the subsequent tests under near-service conditions.

Precise classification of Light Detection and Ranging (LiDAR) point cloud is a fundamental process in various applications, such as land cover mapping, forestry management, and autonomous driving. Due to the lack of spectral information, the existing research on single wavelength LiDAR classification is limited. Spectral information from images could address this limitation, but data fusion suffers from varying illumination conditions and the registration problem. A novel multispectral LiDAR successfully obtains spatial and spectral information as a brand-new data type, namely, multispectral point cloud, thereby improving classification performance. However, spatial and spectral information of multispectral LiDAR has been processed separately in previous studies, thereby possibly limiting the classification performance of multispectral LiDAR. To explore the potential of this new data type, the current spatial–spectral classification framework for multispectral LiDAR that includes four steps: (1) neighborhood selection, (2) feature extraction and selection, (3) classification, and (4) label smoothing. Three novel highlights were proposed in this spatial – spectral classification framework. (1) We improved the popular eigen entropy-based neighborhood selection by spectral angle match to extract a more precise neighborhood. (2) We evaluated the importance of geometric and spectral features to compare their contributions and selected the most important features to reduce feature redundancy. (3) We conducted spatial label smoothing by a conditional random field, accounting for the spatial and spectral information of the neighborhood points. The proposed method demonstrated by a multispectral LiDAR with three channels: 466 nm (blue), 527 nm (green), and 628 nm (red). Experimental results demonstrate the effectiveness of the proposed spatial – spectral classification framework. Moreover, this research takes advantages of the complementation of spatial and spectral information, which could benefit more precise neighborhood selection, more effective features, and satisfactory refinement of classification result. Finally, this study could serve as an inspiration for future efficient spatial–spectral process for multispectral point cloud.

Background: Recently, the arterial velocity pulse index (AVI) and arterial pressure volume index (API) have been used to evaluate arterial stiffness and endothelial function. As arterial stiffness and endothelial injury are risk factors for coronary artery disease (CAD), these two indexes are therefore expected to predict and evaluate the future risk of CAD and cardiovascular events before clinical manifestations. Methods: A total of 90 consecutive patients with coronary angiography (CAG) were enrolled. After excluding normal patients and acute coronary syndrome patients, forty-seven patients with CAD and thirty-two patients with coronary atherosclerosis, and baseline characteristics data were collected. A multifunctional blood pressure monitoring device, AVE-1500 (Shisei Datum, Tokyo, Japan), was used to measure the AVI and API before CAG, and immediately and 2 h, 24 h, and 48 h after CAG and (or) PCI in all the selected participants. Results: After adjusting for various variables using stepwise multiple linear regression analyses, we found that the AVI in the CAD subjects was significantly higher than that in the coronary atherosclerosis subjects before CAG (p = 0.02), immediately after CAG/PCI (p = 0.01), and 48 h after CAG/PCI (p = 0.01), whereas the AVI decreased 24–48 h rather than immediately after CAG/PCI in the CAD group. Moreover, we also found that the API clearly changed in both groups during the periprocedural period of CAG (p = 0.01). Conclusions: In accordance with the results, we propose that the API and AVI may be useful for predicting the early stage of CAD and may be promising as indicators to assess the effect of early revascularization.

Delayed wound healing is one vital complication of diabetes mellitus (DM) that adversely impacts patient quality of life. Infliximab (INF), a monoclonal tumor necrosis factor α (TNF-α) antibody, has been investigated for its therapeutic potential across various diseases through displaying anti-inflammation ability. However, the regulatory mechanisms by which INF influences and correlates with delayed wound healing in DM remain unclear. In this study, we first induced diabetes in mice using streptozotocin (STZ) to establish a DM model, and then excision wounds were generated. We observed that wound closure was significantly retarded in DM mice, but this effect was reversed following INF treatment (5 mg/kg). Moreover, INF treatment attenuated the heightened inflammation observed in DM mice. Furthermore, we found that INF expedited the M2 phenotype polarization in DM mice. Mechanistically, INF was shown to delay activation of the nuclear factor kappa-B (NF-κB) pathway. To sum up, our findings demonstrate that in diabetic mice, INF facilitates wound healing by modulating macrophage polarization, and refrained the NF-κB pathway, supporting INF as a promising treatment approach for improving wound healing in diabetics.

Abstract Rheumatoid arthritis (RA) is a complex immune-mediated inflammatory disorder in which patients suffer from inflammatory-erosive arthritis. Recent advances on histopathology heterogeneity of RA synovial tissue revealed three distinct phenotypes based on cellular composition (pauci-immune, diffuse and lymphoid), suggesting that distinct etiologies warrant specific targeted therapy which motivates a need for cost effective phenotyping tools in preclinical and clinical settings. To this end, we developed an automated multi-scale computational pathotyping (AMSCP) pipeline for both human and mouse synovial tissue with two distinct components that can be leveraged together or independently: (1) segmentation of different tissue types to characterize tissue-level changes, and (2) cell type classification within each tissue compartment that assesses change across disease states. Here, we demonstrate the efficacy, efficiency, and robustness of the AMSCP pipeline as well as the ability to discover novel phenotypes. Taken together, we find AMSCP to be a valuable cost-effective method for both pre-clinical and clinical research.

Abstract Meningitis induced by Pasteurella multocida has been substantially described in clinical practice in both human and veterinary medicine, but the underlying mechanisms have not been previously reported. In this study, we investigated the influence of P. multocida infection on the permeability of the blood–brain barrier (BBB) using different models. Our in vivo tests in a mouse model and in vitro tests using human brain microvascular endothelial cell (hBMEC) model showed that P. multocida infection increased murine BBB permeability in mice and hBMEC monolayer permeability. Furthermore, we observed that P. multocida infection resulted in decreased expression of tight junctions (ZO1, claudin-5, occludin) and adherens junctions (E-cadherin) between neighboring hBMECs. Subsequent experiments revealed that P. multocida infection promoted the activation of hypoxia inducible factor-1α (HIF-1α)/vascular endothelial growth factor A (VEGFA) signaling and NF-κB signaling, and suppressed the HIF-1α/VEGFA significantly remitted the decrease in ZO1/E-cadherin induced by P. multocida infection (P

Abstract In order to facilitate cardiovascular research to develop non-invasive optical heart pacing methods, we have generated a double-transgenic Drosophila melanogaster (fruit fly) model suitable for optogenetic pacing. We created a fly stock with both excitatory H134R-ChR2 and inhibitory eNpHR2.0 opsin transgenes. Opsins were expressed in the fly heart using the Hand-GAL4 driver. Here we describe Hand > H134R-ChR2; eNpHR2.0 model characterization including bi-directional heart control (activation and inhibition) upon illumination of light with distinct wavelengths. Optical control and real-time visualization of the heart function were achieved non-invasively using an integrated light stimulation and optical coherence microscopy (OCM) system. OCM produced high-speed and high-resolution imaging; simultaneously, the heart function was modulated by blue (470 nm) or red (617 nm) light pulses causing tachycardia, bradycardia and restorable cardiac arrest episodes in the same animal. The irradiance power levels and illumination schedules were optimized to achieve successful non-invasive bi-directional heart pacing in Drosophila larvae and pupae.

Abstract Prostate cancer (PRAD) is one of the leading malignancies in men all around the world. Here, we identified Myosin Heavy Chain 6 (MYH6) as a potential tumor suppressor gene in the development of prostate cancer. We found lower expression of MYH6 in prostate cancer tissues, and its lower gene expression was also associated with worse clinical outcomes. In vitro and in vivo assays indicated that overexpressed MYH6 could suppress the proliferation and migration progression of prostate cancer cells. RNA-seq was employed to investigate the mechanism, and KIT Proto-Oncogen (KIT) was determined as the downstream gene of MYH6, which was further confirmed using rescue assays. In all, we provide the evidence that MYH6 could serve as a tumor suppressor in prostate cancer. Our results highlight the potential role of MYH6 in the development of prostate cancer.

Abstract Deep learning models have been developed for various predictions in glioma; yet, they were constrained by manual segmentation, task-specific design, or a lack of biological interpretation. Herein, we aimed to develop an end-to-end multi-task deep learning (MDL) pipeline that can simultaneously predict molecular alterations and histological grade (auxiliary tasks), as well as prognosis (primary task) in gliomas. Further, we aimed to provide the biological mechanisms underlying the model’s predictions. We collected multiscale data including baseline MRI images from 2776 glioma patients across two private (FAHZU and HPPH, n = 1931) and three public datasets (TCGA, n = 213; UCSF, n = 410; and EGD, n = 222). We trained and internally validated the MDL model using our private datasets, and externally validated it using the three public datasets. We used the model-predicted deep prognosis score (DPS) to stratify patients into low-DPS and high-DPS subtypes. Additionally, a radio-multiomics analysis was conducted to elucidate the biological basis of the DPS. In the external validation cohorts, the MDL model achieved average areas under the curve of 0.892–0.903, 0.710–0.894, and 0.850–0.879 for predicting IDH mutation status, 1p/19q co-deletion status, and tumor grade, respectively. Moreover, the MDL model yielded a C-index of 0.723 in the TCGA and 0.671 in the UCSF for the prediction of overall survival. The DPS exhibits significant correlations with activated oncogenic pathways, immune infiltration patterns, specific protein expression, DNA methylation, tumor mutation burden, and tumor-stroma ratio. Accordingly, our work presents an accurate and biologically meaningful tool for predicting molecular subtypes, tumor grade, and survival outcomes in gliomas, which provides personalized clinical decision-making in a global and non-invasive manner.

Abstract Imaging through dynamic scattering media is one of the most challenging yet fascinating problems in optics, with applications spanning from biological detection to remote sensing. In this study, we propose a comprehensive learning-based technique that facilitates real-time, non-invasive, incoherent imaging of real-world objects through dense and dynamic scattering media. We conduct extensive experiments, demonstrating the capability of our technique to see through turbid water and natural fog. The experimental results indicate that the proposed technique surpasses existing approaches in numerous aspects and holds significant potential for imaging applications across a broad spectrum of disciplines.

Abstract Deep learning has enabled breakthroughs in automated diagnosis from medical imaging, with many successful applications in ophthalmology. However, standard medical image classification approaches only assess disease presence at the time of acquisition, neglecting the common clinical setting of longitudinal imaging. For slow, progressive eye diseases like age-related macular degeneration (AMD) and primary open-angle glaucoma (POAG), patients undergo repeated imaging over time to track disease progression and forecasting the future risk of developing a disease is critical to properly plan treatment. Our proposed Longitudinal Transformer for Survival Analysis (LTSA) enables dynamic disease prognosis from longitudinal medical imaging, modeling the time to disease from sequences of fundus photography images captured over long, irregular time periods. Using longitudinal imaging data from the Age-Related Eye Disease Study (AREDS) and Ocular Hypertension Treatment Study (OHTS), LTSA significantly outperformed a single-image baseline in 19/20 head-to-head comparisons on late AMD prognosis and 18/20 comparisons on POAG prognosis. A temporal attention analysis also suggested that, while the most recent image is typically the most influential, prior imaging still provides additional prognostic value.

Abstract Background Patient safety (PS) is a core competency for registered nurses. However, there is a gap between the PS competence of nursing students and their clinical experience in PS. This study explored the effect of PS competence levels on the occurrence of adverse events (AEs) among nursing master’s students in China. Methods A sequential mixed methods design was used, with a purposive sample across seven colleges. A total of 327 graduate nursing students, aged 22 to 38, participated in the survey, and 15 participated in qualitative interviews. The Health Professional Education in Patient Safety Survey (H-PEPSS) assessed the students’ competence levels in PS. The respondents also reported any AEs that they had been involved in over the past year. Results A total of 78 AEs occurred in the past year, with 17.7% of the participants involved 1 to 3 AEs. The most common AEs were medication administration errors (30.77%) and improper use of medical equipment/supplies (28.20%). Students acquired more competencies from the clinical setting than from the classroom setting. Three competencies learned from classroom settings were associated with clinical AEs: low clinical safety skills [OR = 0.61], inappropriate identify, response to and disclosing AE and close calls [OR = 0.454], and low confidence in working in teams with other health professionals [OR = 2.168]. Qualitative data analysis revealed five themes: recognizing AEs, reducing harm by addressing immediate risks to patients and others involved, promoting safe medication and clinical practice, managing members’ authority and team dynamics, and dealing with inter-professional conflict. Conclusions The quantitative and qualitative data align, supporting the enhancement of students’ PS competence.

Abstract Background The unfolded protein response (UPR) is associated with immune cells that regulate the biological behavior of tumors. This article aims to combine UPR-associated genes with immune cells to find a prognostic marker and to verify its connection to the UPR. Methods Univariate cox analysis was used to screen prognostically relevant UPRs and further screened for key UPRs among them by machine learning. ssGSEA was used to calculate immune cell abundance. Univariate cox analysis was used to screen for prognostically relevant immune cells. Multivariate cox analysis was used to calculate UPR_score and Tumor Immune Microenvironment score (TIME_score). WGCNA was used to screen UPR-Immune-related (UI-related) genes. Consensus clustering analysis was used to classify patients into molecular subtype. Based on the UI-related genes, we classified colon adenocarcinoma (COAD) samples by cluster analysis. Single-cell analysis was used to analyze the role of UI-related genes. We detected the function of TIMP1 by cell counting and transwell. Immunoblotting was used to detect whether TIMP1 was regulated by key UPR genes. Results Combined UPR-related genes and immune cells can determine the prognosis of COAD patients. Cluster analysis showed that UI-related genes were associated with clinical features of COAD. Single-cell analysis revealed that UI-related genes may act through stromal cells. We defined three key UI-related genes by machine learning algorithms. Finally, we found that TIMP1, regulated by key genes of UPR, promoted colon cancer proliferation and metastasis. Conclusions We found that TIMP1 was a prognostic marker and experimentally confirmed that TIMP1 was regulated by key genes of UPR.

Highlights Developing surface-functionalized catalysts with exceptional activity and selectivity for the electrocatalytic CO2RR to C2+ products under neutral electrolyte. A remarkable C2+ FE of nearly 90% at an unprecedented current density of 300 mA cm−2 and maintain high FE (> 80%) at the wide current density performance (100–600 mA cm−2) in neutral environments using a flow cell as well as MEA electrolyzer. Mechanical study reveals that reducing the coverage of coordinated K·H2O water increased the probability of intermediate reactants (CO) interacting with the surface, thereby promoting efficient C–C coupling and enhancing the yield of C2+ products.