Ambient air pollution and gestational diabetes mellitus: An updated systematic review and meta-analysis.

OBJECTIVE: We aimed to evaluate the relationship between the composition of particulate matter (PM) and gestational diabetes mellitus (GDM) by a comprehensively review of epidemiological studies. METHODS: We systematically identified cohort studies related to air pollution and GDM risk before February 8, 2023 from six databases (PubMed, Embase, Web of Science Core Collection, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform and Chongqing VIP Chinese Science and Technology Periodical databases). We calculated the relative risk (RR) and its 95% confidence intervals (CIs) to assess the overall effect by using a random effects model. RESULTS: This meta-analysis of 31 eligible cohort studies showed that exposure to PM2.5, PM10, SO2, and NO2 was associated with a significantly increased risk of GDM, especially in preconception and first trimester. Analysis of the components of PM2.5 found that the risk of GDM was strongly linked to black carbon (BC) and nitrates (NO3-). Specifically, BC exposure in the second trimester and NO3- exposure in the first trimester elevated the risk of GDM, with the RR of 1.128 (1.032-1.231) and 1.128 (1.032-1.231), respectively. The stratified analysis showed stronger correlations of GDM risk with higher levels of pollutants in Asia, except for PM2.5 and BC, which suggested that the specific composition of particulate pollutants had a greater effect on the exposure-outcome association than the concentration. CONCLUSIONS: Our study found that ambient air pollutant is a critical factor for GDM and further studies on specific particulate matter components should be considered in the future.

Multi-modal analysis for accurate prediction of preoperative stage and indications of optimal treatment in gastric cancer.

BACKGROUND: Accurate preoperative clinical staging of gastric cancer helps determine therapeutic strategies. However, no multi-category grading models for gastric cancer have been established. This study aimed to develop multi-modal (CT/EHRs) artificial intelligence (AI) models for predicting tumor stages and optimal treatment indication based on preoperative CT images and electronic health records (EHRs) in patients with gastric cancer. METHODS: This retrospective study enrolled 602 patients with a pathological diagnosis of gastric cancer from Nanfang hospital retrospectively and divided them into training (n = 452) and validation sets (n = 150). A total of 1326 features were extracted of which 1316 radiomic features were extracted from the 3D CT images and 10 clinical parameters were obtained from electronic health records (EHRs). Four multi-layer perceptrons (MLPs) whose input was the combination of radiomic features and clinical parameters were automatically learned with the neural architecture search (NAS) strategy. RESULTS: Two two-layer MLPs identified by NAS approach were employed to predict the stage of the tumor showed greater discrimination with the average ACC value of 0.646 for five T stages, 0.838 for four N stages than traditional methods with ACC of 0.543 (P value = 0.034) and 0.468 (P value = 0.021), respectively. Furthermore, our models reported high prediction accuracy for the indication of endoscopic resection and the preoperative neoadjuvant chemotherapy with the AUC value of 0.771 and 0.661, respectively. CONCLUSIONS: Our multi-modal (CT/EHRs) artificial intelligence models generated with the NAS approach have high accuracy for tumor stage prediction and optimal treatment regimen and timing, which could facilitate radiologists and gastroenterologists to improve diagnosis and treatment efficiency.

Spatiotemporal characteristics and co-effects of air quality and carbon dioxide emissions changes during the COVID-19 epidemic lockdown measures in China.

The COVID-19 pandemic prompted several nations, including China, to enact unprecedented lockdown measures, leading to significant alterations in environmental conditions. Previous studies have solely analysed the impact of lockdown measures on air pollutants or carbon dioxide (CO2) emissions during the COVID-19 pandemic in China, but few have focused on the spatio-temporal change characteristics and synergistic effects between the two. In this study, we constructed a methodological framework to examine the spatiotemporal characteristics and co-effects of air quality (PM2.5, SO2, and NO2) and CO2 changes in 324 prefecture-level cities in China due to the COVID-19 blockade measures from January 24 to April 30, 2020, using the regression discontinuity in time method and co-effect control coordinate system. The results show that a significant improvement in air quality and CO2 emissions during the lockdown period, with notable north‒south heterogeneity. During the major lockdown period (January 24 to February 29), the measures resulted in respective reductions of 5.6%, 16.6%, and 25.1% in the concentrations of SO2, NO2, and CO2 nationwide. The proportions of cities with negative treatment effects on PM2.5, SO2, NO2, and CO2 were 39.20%, 70.99%, 84.6%, and 99.38%, respectively. Provinces where concentrations of CO2 and NO2 declined by over 30% were primarily concentrated in southern areas of the 'Yangtze River Defense Line'. Starting from March, the improvement effect of air quality and CO2 has weakened, and the concentration of air pollutants has rebounded. This study offers crucial insights into the causal effects of lockdown measures on air quality changes, and reveals the synergy between air quality and CO2, thereby providing a reference for devising effective air quality improvement and energy-saving emission reduction strategies.

CT-based radiomics nomograms for preoperative prediction of diffuse-type and signet ring cell gastric cancer: a multicenter development and validation cohort.

BACKGROUND: The prevalence of diffuse-type gastric cancer (GC), especially signet ring cell carcinoma (SRCC), has shown an upward trend in the past decades. This study aimed to develop computed tomography (CT) based radiomics nomograms to distinguish diffuse-type and SRCC GC preoperatively. METHODS: A total of 693 GC patients from two centers were retrospectively analyzed and divided into training, internal validation and external validation cohorts. Radiomics features were extracted from CT images, and the Lauren radiomics model was established with a support vector machine (SVM) classifier to identify diffuse-type GC. The Lauren radiomics nomogram integrating radiomics features score (Rad-score) and clinicopathological characteristics were developed and evaluated regarding prediction ability. Further, the SRCC radiomics nomogram designed to identify SRCC from diffuse-type GC was developed and evaluated following the same procedures. RESULTS: Multivariate analysis revealed that Rad-scores was significantly associated with diffuse-type GC and SRCC (p < 0.001). The Lauren radiomics nomogram showed promising prediction performance with an area under the curve (AUC) of 0.895 (95%CI, 0.957-0.932), 0.841 (95%CI, 0.781-0.901) and 0.893 (95%CI, 0.831-0.955) in each cohort. The SRCC radiomics nomogram also showed good discrimination, with AUC of 0.905 (95%CI,0.866-0.944), 0.845 (95%CI, 0.775-0.915) and 0.918 (95%CI, 0.842-0.994) in each cohort. The radiomics nomograms showed great model fitness and clinical usefulness by calibration curve and decision curve analysis. CONCLUSION: Our CT-based radiomics nomograms had the ability to identify the diffuse-type and SRCC GC, providing a non-invasive, efficient and preoperative diagnosis method. They may help guide preoperative clinical decision-making and benefit GC patients in the future.

An artificial intelligence method to assess the tumor microenvironment with treatment outcomes for gastric cancer patients after gastrectomy.

BACKGROUND: The tumor microenvironment (TME) plays an important role in the occurrence and development of gastric cancer (GC) and is widely used to assess the treatment outcomes of GC patients. Immunohistochemistry (IHC) and gene sequencing are the main analysis methods for the TME but are limited due to the subjectivity of observers, the high cost of equipment and the need for professional analysts. METHODS: The ImmunoScore (IS) was developed in the TCGA cohort and validated in GEO cohorts. The Radiomic ImmunoScore (RIS) was developed in the TCGA cohort and validated in the Nanfang cohort. A nomogram was developed and validated in the Nanfang cohort based on RIS and clinical features. RESULTS: For IS, the area under the curves (AUCs) were 0.798 for 2-year overall survival (OS) and 0.873 for 4-year overall survival. For RIS, in the TCGA cohort, the AUCs distinguishing High-IS or Low-IS and predicting prognosis were 0.85 and 0.81, respectively; in the Nanfang cohort, the AUC predicting prognosis was 0.72. The nomogram performed better than the TNM staging system according to the ROC curve (all P < 0.01). Patients with TNM stage II and III in the High-nomogram group were more likely to benefit from adjuvant chemotherapy than Low-nomogram group patients. CONCLUSIONS: The RIS and the nomogram can be used to assess the TME, prognosis and adjuvant chemotherapy benefit of GC patients after radical gastrectomy and are valuable additions to the current TNM staging system. High-nomogram GC patients may benefit more from adjuvant chemotherapy than Low-nomogram GC patients.

Constant conflict between Gypsy LTR retrotransposons and CHH methylation within a stress-adapted mangrove genome.

The evolutionary dynamics of the conflict between transposable elements (TEs) and their host genome remain elusive. This conflict will be intense in stress-adapted plants as stress can often reactivate TEs. Mangroves reduce TE load convergently in their adaptation to intertidal environments and thus provide a unique opportunity to address the host-TE conflict and its interaction with stress adaptation. Using the mangrove Rhizophora apiculata as a model, we investigated methylation and short interfering RNA (siRNA) targeting patterns in relation to the abundance and age of long terminal repeat (LTR) retrotransposons. We also examined the distance of LTR retrotransposons to genes, the impact on neighboring gene expression and population frequencies. We found differential accumulation amongst classes of LTR retrotransposons despite high overall methylation levels. This can be attributed to 24-nucleotide siRNA-mediated CHH methylation preferentially targeting Gypsy elements, particularly in their LTR regions. Old Gypsy elements possess unusually abundant siRNAs which show cross-mapping to young copies. Gypsy elements appear to be closer to genes and under stronger purifying selection than other classes. Our results suggest a continuous host-TE battle masked by the TE load reduction in R. apiculata. This conflict may enable mangroves, such as R. apiculata, to maintain genetic diversity and thus evolutionary potential during stress adaptation.

Effect of Carbon Fiber Paper with Thickness Gradient on Electromagnetic Shielding Performance of X-Band.

Flexible paper-based materials play a crucial role in the field of flexible electromagnetic shielding due to their thinness and controllable shape. In this study, we employed the wet paper forming technique to prepare carbon fiber paper with a thickness gradient. The electromagnetic shielding performance of the carbon fiber paper varies with the ladder-like thickness distribution. Specifically, an increase in thickness gradient leads to higher reflectance of the carbon fiber paper. Within the X-band frequency range (8.2-12.4 GHz), reflectivity decreases as electromagnetic wave frequency increases, indicating enhanced penetration of electromagnetic waves into the interior of the carbon fiber paper. This enhancement is attributed to an increased fiber content per unit area resulting from a greater thickness gradient, which further enhances reflection loss and promotes internal multiple reflections and scattering effects, leading to increased absorption loss. Notably, at a 5 mm thickness, our carbon fiber paper exhibits an impressive average overall shielding performance, reaching 63.46 dB. Moreover, it exhibits notable air permeability and mechanical properties, thereby assuming a pivotal role in the realm of flexible wearable devices in the foreseeable future.

Screening, characterization and mechanism of a potential stabiliser for nisin nanoliposomes with high encapsulation efficiency.

The encapsulation efficiency (EE%) reflects the amount of bioactive components that can be loaded into nanoliposomes. Obtaining a suitable nanoliposome stabiliser may be the key to improving their EE%. In this study, three polyphenols were screened as stabilisers of nanoliposomes with high nisin EE%, with curcumin nanoliposomes (Cu-NLs) exhibiting the best performance (EE% = 95.94%). Characterizations of particle size, PDI and zeta potential indicate that the Cu-NLs had good uniformity and stability. TEM found that nisin accumulated at the edges of the Cu-NLs' phospholipid layer. DSC and FT-IR revealed that curcumin was involved in the formation of the phospholipid layer and altered its structure. FT-IR and molecular docking simulations indicate that the interactions between curcumin and nisin are mainly hydrogen bonding and hydrophobic. In whole milk, Cu-NLs effectively protected nisin activity. This study provides an effective strategy for improving the EE% of nanoliposomes loaded with nisin and other bacteriocins.

Preparation of PCL/lecithin/bacteriocin CAMT6 antimicrobial and antioxidant nanofiber films using emulsion electrospinning: Characteristics and application in chilled salmon preservation.

Multi-functional packaging materials are an important development for food preservation. Emulsion electrospinning is a novel and simple method that can be used to prepare multi-functional packaging materials, which can effectively protect the loaded active substances during the preparation process. In this study, PCL/lecithin/bacteriocin CAMT6 nanofiber films with antimicrobial and antioxidant activity were prepared by emulsion electrostatic spinning. The morphology and homogeneity of the prepared nanofibrous membranes could be improved by optimising the formulation of the emulsion for electrospinning. Analytical testing of the prepared nanofiber films revealed that the nanofibers had a core-shell structure, with bacteriocin CAMT6 effectively encapsulated in the core layer and the PCL and phospholipids homogeneously mixed to form the shell layer. Additionally, the nanofiber films had acceptable tensile properties and water absorption capacity. In chilled salmon meat, the nanofiber film effectively inhibited the growth of bacteria, slowed the oxidation of oil and slowed water loss, which was a good protective effect. This study provides a reference for the encapsulation application of food-active packaging materials and bacteriocins.

POLQ inhibition attenuates the stemness and ferroptosis resistance in gastric cancer cells via downregulation of dihydroorotate dehydrogenase.

Gastric cancer (GC) contains subpopulations of cancer stem cells (CSCs), which are described as the main contributors in tumor initiation and metastasis. It is necessary to clarify the molecular mechanism underlying CSCs phenotype and develop novel biomarkers and therapeutic targets for gastric cancer. Here, we show that POLQ positively regulates stem cell-like characteristics of gastric cancer cells, knockdown of POLQ suppressed the stemness of GC cells in vitro and in vivo. Further mechanistic studies revealed that POLQ knockdown could downregulate the expression of dihydroorotate dehydrogenase (DHODH). DHODH overexpression rescued the reduced stemness resulted by POLQ knockdown. Furthermore, we found that POLQ expression correlated with resistance to ferroptosis, and POLQ inhibition renders gastric cancer cells more vulnerable to ferroptosis. Further investigation revealed that POLQ regulated DHODH expression via the transcription factors E2F4, thereby regulating ferroptosis resistance and stemness of gastric cancer cells. Given the importance of POLQ in stemness and ferroptosis resistance of GC, we further evaluated the therapeutic potential of POLQ inhibitor novobiocin, the results show that novobiocin attenuates the stemness of GC cells and increased ferroptosis sensitivity. Moreover, the combination of POLQ inhibitor and ferroptosis inducer synergistically suppressed MGC-803 xenograft tumor growth and diminished metastasis. Our results identify a POLQ-mediated stemness and ferroptosis defense mechanism and provide a new therapeutic strategy for gastric cancer.

Endoplasmic Reticulum Stress and Autophagy Are Involved in Hepatotoxicity Induced by Tributyltin.

Tributyltin (TBT), a common contaminant in aquatic ecosystems, has severe toxic effects on multiple tissues and organs, especially the liver. Previous toxicogenomic analysis has indicated that the main mechanism of TBT-induced hepatotoxicity is related to the activation of the apoptotic pathway. However, the mechanism of action occurring before the activation of apoptosis is still unclear. Herein, we applied proteomic technology to explore the protein expression profile of TBT-treated HL7702 normal human liver cells. The ultrastructural changes in cells were observed by transmission electron microscopy. After low dose (2 µΜ) TBT treatment, activation of the unfolded protein response and endoplasmic reticulum stress were observed; the expression levels of PERK, ATF6, BiP, and CHOP were significantly elevated, and splicing of XBP1 mRNA was initiated. When the TBT concentration increased to 4 µΜ, the protein levels of Beclin1, Atg3, Atg5, Atg7, and Atg12-Atg5 were significantly elevated, and the protein level of LC3Ⅰ decreased while that of LC3Ⅱ increased, suggesting the activation of autophagy. As the TBT concentration continued to increase, autophagy could not eliminate the damage, and apoptosis eventually occurred. These results indicate novel pathways of hepatotoxicity induced by TBT and provide insights for future studies.

Preparation, characterization and application of bacteriocin CAMT6 nanoliposomes using resveratrol as a novel stabilizer.

Nanoliposomes are ideal nanocarriers for encapsulated active compounds used in the food industry as they provide stability and controlled release. However, cholesterol may pose risks in large intake, which is the commonly-used nanoliposome stabilizers. In this study, resveratrol was used instead of cholesterol as a novel nanoliposome stabilizer to construct a resveratrol blank liposome (RBL) system. The RBL system was used to protect the bacteriocin CAMT6 to create bacteriocin-loaded nanoliposomes (BLLs). The RBLs and BLLs had favourable particle sizes (172.71 nm and 150.47 nm), polydispersity index (PDI) values (0.150 and 0.120) and zeta potentials (-41.54 mV and -43.53 mV, respectively). According to Differential scanning colourimetry (DSC) and X-ray diffraction (XRD) analyses, resveratrol altered the structure of the phospholipid layer. The phospholipid layers of the RBLs and BLLs had higher mobility when resveratrol was used as a stabilizer instead of cholesterol. Structurally, resveratrol was inserted egg yolk lecithin to constitute an RBL. CAMT6 was loaded in BLLs with spherical and shell-core structures. The BLL encapsulation efficiency was 97.32 % and exhibited three release phases, with the release rates reaching 62 %. In experiments with milk, the BLLs effectively protected the anti-Listeria activity of CAMT6. In summary, resveratrol is a suitable nanoliposome stabilizer and the proposed RBL system is an excellent way to improve the stability of water-soluble preservatives, such as bacteriocins, in complex food environments.

Evolutionary Multitasking for Multiobjective Optimization With Subspace Alignment and Adaptive Differential Evolution.

In contrast to the traditional single-tasking evolutionary algorithms, evolutionary multitasking (EMT) travels in the search space of multiple optimization tasks simultaneously. Through sharing knowledge across the tasks, EMT is able to enhance solving the optimization tasks. However, if knowledge transfer is not properly carried out, the performance of EMT might become unsatisfactory. To address this issue and improve the quality of knowledge transfer among the tasks, a novel multiobjective EMT algorithm based on subspace alignment and self-adaptive differential evolution (DE), namely, MOMFEA-SADE, is proposed in this article. Particularly, a mapping matrix obtained by subspace learning is used to transform the search space of the population and reduce the probability of negative knowledge transfer between tasks. In addition, DE characterized by a self-adaptive trial vector generation strategy is introduced to generate promising solutions based on previous experiences. The experimental results on multiobjective multi/many-tasking optimization test suites show that MOMFEA-SADE is superior or comparable to other state-of-the-art EMT algorithms. MOMFEA-SADE also won the Competition on Evolutionary Multitask Optimization (the multitask multiobjective optimization track) within IEEE 2019 Congress on Evolutionary Computation.

Diabetes mellitus promoted lymph node metastasis in gastric cancer: a 15-year single-institution experience.

BACKGROUND: Previous studies have revealed that diabetes mellitus (DM) promotes disease progress of gastric cancer (GC). This study aimed to further investigating whether DM advanced lymph nodes (LNs) metastasis in GC. METHODS: The clinicopathologic data of GC patients with >15 examined LN (ELN) between October 2004 and December 2019 from a prospectively maintained database were included. The observational outcomes included the number (N3b status) and anatomical distribution (N3 stations) of metastatic LN (MLN). RESULTS: A total of 2142 eligible patients were included in the study between October 2004 and December 2019. N3 stations metastasis (26.8% in DM vs. 19.3% in non-DM, P  = 0.026) and N3b status (18.8% in DM vs. 12.8% in non-DM, P  = 0.039) were more advanced in the DM group, and multivariate logistic regression analyses confirmed that DM was an independent factor of developing N3 stations metastasis (odds ratio [OR] = 1.771, P  = 0.011) and N3b status (OR = 1.752, P  = 0.028). Also, multivariate analyses determined DM was independently associated with more MLN (ß = 1.424, P  = 0.047). The preponderance of N3 stations metastasis (DM vs. non-DM, T1-2: 2.2% vs. 4.9%, T3: 29.0% vs. 20.3%, T4a: 38.9% vs. 25.8%, T4b: 50.0% vs. 36.6%; ELN16-29: 8.6% vs. 10.4%, ELN30-44: 27.9% vs. 20.5%, ELN ≥ 45: 37.7% vs. 25.3%), N3b status (DM vs. non-DM, T1-2: 0% vs. 1.7%, T3: 16.1% vs. 5.1%, T4a: 27.8% vs. 19.1%, T4b: 44.0% vs. 28.0%; ELN16-29: 8.6% vs. 7.9%, ELN30-44: 18.0% vs. 11.8%, ELN ≥ 45: 26.4% vs. 17.3%), and the number of MLN (DM vs. non-DM, T1-2: 0.4 vs. 1.1, T3: 8.6 vs. 5.2, T4a: 9.7 vs. 8.6, T4b: 17.0 vs. 12.8; ELN16-29: 3.6 vs. 4.6, ELN30-44: 5.8 vs. 5.5, ELN ≥ 45: 12.0 vs. 7.7) of DM group increased with the advancement of primary tumor depth stage and raising of ELN. CONCLUSIONS: DM was an independent risk factor for promoting LN metastasis. The preponderance of LN involvement in the DM group was aggravated with the advancement of tumor depth.

Overexpression of an Orchid (Dendrobium nobile) SOC1/TM3-Like Ortholog, DnAGL19, in Arabidopsis Regulates HOS1-FT Expression.

Flowering in the appropriate season is critical for successful reproduction in angiosperms. The orchid species, Dendrobium nobile, requires vernalization to achieve flowering in the spring, but the underlying regulatory network has not been identified to date. The MADS-box transcription factor DnAGL19 was previously identified in a study of low-temperature treated D. nobile buds and was suggested to regulate vernalization-induced flowering. In this study, phylogenetic analysis of DnAGL9 and the MADS-box containing proteins showed that DnAGL19 is phylogenetically closely related to the SOC1-like protein from orchid Dendrobium Chao Parya Smile, DOSOC1. The orchid clade closed to but is not included into the SOC1-1/TM3 clades associated with either eudicots or monocots, suggesting that DnAGL19 is an SOC1-1/TM3-like ortholog. DnAGL19 was found to be highly expressed in pseudobulbs, leaves, roots, and axillary buds but rarely in flowers, and to be substantially upregulated in axillary buds by prolonged low-temperature treatments. Overexpression of DnAGL19 in Arabidopsis thaliana resulted in a small but significantly reduced time to bolting, suggesting that flowering time was slightly accelerated under normal growth conditions. Consistent with this, the A. thaliana APETELA1 (AP1) gene was expressed at an earlier stage in transgenic lines than in wild type plants, while the FLOWERING LOCUS T (FT) gene was suppressed, suggesting that altered regulations on these transcription factors caused the weak promotion of flowering. HIGH EXPRESSION OF OSMOTICALLY RESPONSIVE GENE 1 (HOS1) was slightly activated under the same conditions, suggesting that the HOS1-FT module may be involved in the DnAGL19-related network. Under vernalization conditions, FT expression was significantly upregulated, whereas HOS1 expression in the transgenic A. thaliana has a level similar to that in wild type. Taken together, these results suggest that DnAGL19 controls the action of the HOS1-FT module depending on temperature cues, which could contribute to regulation of D. nobile flowering time. These data provide insights into how flowering is fine-tuned in D. nobile to acclimate the plant to seasonal changes in temperature.