CXCL1/IGHG1 signaling enhances crosstalk between tumor cells and tumor-associated macrophages to promote MC-LR-induced colorectal cancer progression.

Microcystin-leucine arginine (MC-LR) is a common cyantotoxin produced by hazardous cyanobacterial blooms, and eutrophication is increasing the contamination level of MC-LR in drinking water supplies and aquatic foods. MC-LR has been linked to colorectal cancer (CRC) progression associated with tumor microenvironment, however, the underlying mechanism is not clearly understood. In present study, by using GEO, KEGG, GESA and ImmPort database, MC-LR related differentially expressed genes (DEGs) and pathway- and gene set-enrichment analysis were performed. Of the three identified DEGs (CXCL1, GUCA2A and GDF15), CXCL1 was shown a positive association with tumor infiltration, and was validated to have a dominantly higher upregulation in MC-LR-treated tumor-associated macrophages (TAMs) rather than in MC-LR-treated CRC cells. Both CRC cell/macrophage co-culture and xenograft mouse models indicated that MC-LR stimulated TAMs to secrete CXCL1 resulting in promoted proliferation, migration, and invasion capability of CRC cells. Furtherly, IP-MS assay found that interaction between TAMs-derived CXCL1 and CRC cell-derived IGHG1 may enhance CRC cell proliferation and migration after MC-LR treatment, and this effect can be attenuated by silencing IGHG1 in CRC cell. In addition, molecular docking analysis, co-immunoprecipitation and immunofluorescence further proved the interactions between CXCL1 and IGHG1. In conclusion, CXCL1 secreted by TAMs can trigger IGHG1 expression in CRC cells, which provides a new clue in elucidating the mechanism of MC-LR-mediated CRC progression.

Microcystin-leucine-arginine impairs bone microstructure and biomechanics by activating osteoimmune response and inhibiting osteoblasts maturation in developing rats.

Microcystin-LR (MC-LR) affects bone health in adult mice via osteo-immunomodulation. However, its effect on osteoblasts and bone development is unclear. This study investigated the effect of MC-LR on bone osteoimmune and osteoblasts in the developing period. 18 Four-week-old male Sprague Dawley rats were divided into two groups (n = 9 per group) and exposed to 0 (control) and 1 µg/kg b.w. MC-LR (exposure) by intraperitoneal injection for four weeks. The heart blood was collected for serological examination, and the femur for morphological, histopathological, and biomechanical analysis. MC-LR exposure significantly weakened bone microstructures (bone volume, bone volume/total volume, bone trabecular number, connectivity density) and biomechanics (maximum loads and maximum deflection) (P < 0.05). Besides, MC-LR decreased serum procollagen type І car-boxy-terminal propeptide, osteocalcin, bone morphogenetic protein-2, osteoprotegerin, and receptor activator of nuclear factor κB ligand, while elevating osteoclasts number, matrix metalloproteinase-9, ß-catenin, Runt-related transcription factor 2, and osterix in bone, and bone alkaline phosphate, C-terminal cross-linked telopeptide of type-I collagen, tartrate-resistant acid phosphatase-5b in serum (P < 0.05). Moreover, MC-LR increased CD4+ T-cells, CD4+/CD8+, M1 and M2 macrophages, and cells apoptosis in the bone marrow, interleukin-6, interleukin-17, and tumor necrosis factor-α in serum, decreased serum interleukin-10 (P < 0.05). Overall, MC-LR can promote bone resorption by activating osteoclasts via osteoimmunology, which may involve macrophages besides lymphocytes. MC-LR may inhibit bone formation by stopping the osteoblasts at an immature stage. Thus, MC-LR weakened bone microstructure and biomechanics in developing period. Its risk on bone development needs further study.

Mixed exposure effect of seminal metals on semen quality, mediation of total antioxidant capacity, and moderation of GSTM1/GSTT1 gene deletion in Chinese reproductive-aged men.

BACKGROUND: The effects of metal exposure on semen quality and the role of oxidative damage in this process remain unclear. METHODS: We recruited 825 Chinese male volunteers, and 12 seminal metals (Mn, Cu, Zn, Se, Ni, Cd, Pb, Co, Ag, Ba, Tl, and Fe), the total antioxidant capacity (TAC), and reduced glutathione were measured. Semen parameters and GSTM1/GSTT1-null genotypes were also detected. Bayesian kernel machine regression (BKMR) was applied to evaluate the effect of the mixed exposure to metals on semen parameters. The mediation of TAC and moderation of GSTM1/GSTT1 deletion were analyzed. RESULTS: Most seminal metal concentrations were correlated with each other. The BKMR models revealed a negative association between the semen volume and metal mixture, with Cd (cPIP = 0.60) and Mn (cPIP = 0.10) as the major contributors. Compared to fixing all scaled metals at their median value (50th percentiles), fixing the scaled metals at their 75th percentiles decreased the TAC by 2.17 units (95%CI: -2.60, -1.75). Mediation analysis indicated that Mn decreased the semen volume, with 27.82% of this association mediated by TAC. Both the BKMR and multi-linear models showed that seminal Ni was negatively correlated with sperm concentration, total sperm count, and progressive motility, which was modified by GSTM1/GSTT1. Furthermore, Ni and the total sperm count showed a negative association in GSTT1 and GSTM1 null males (ß[95%CI]: 0.328 [-0.521, -0.136]) but not in males with GSTT1 and/or GSTM1. Although Fe and the sperm concentration and total sperm count were positively correlated, they showed inverse "U" shapes in univariate analysis. CONCLUSION: Exposure to the 12 metals was negatively associated with semen volume, with Cd and Mn as the major contributors. TAC may mediate this process. GSTT1 and GSTM1 can modify the reduction in the total sperm count caused by seminal Ni exposure.

Comparing the cooling effectiveness of operationalisable urban surface combination scenarios for summer heat mitigation.

Extreme summer heat in cities exacerbates the vulnerability of urban communities to heatwaves. Vegetative and reflective urban surfaces can help reduce urban heat. This study investigated the impacts of urban trees, green roofs and cool roofs on heat mitigation during average and extreme summer conditions in temperate oceanic Melbourne, Australia. We simulated the city climate using 'The Air Pollution Model' (TAPM) at a 1 km spatial resolution over 10 years, which according to our review of the literature, was the most prolonged period for simulation in Melbourne. During a widespread heatwave event, some of the tested scenarios with combined surface parameters could reduce the extreme values of the energy budget components- sensible heat, latent heat, and storage heat fluxes up to seasonal averages compared to the existing situation for Melbourne (control). The scenario with the highest (reasonable maximum) ground-level vegetation, green roofs, and cool roofs could reduce air temperatures up to 2.4 °C. The simulations suggest that a combined strategy with vegetative and high-albedo surfaces will deliver higher effectiveness with maximum cooling benefits and cost-effectiveness than individual strategies in cities. These results suggest the importance of collaborative strategic planning of urban surfaces to make cities healthier, sustainable, and liveable.

Extreme fire weather is the major driver of severe bushfires in southeast Australia.

In Australia, the proportion of forest area that burns in a typical fire season is less than for other vegetation types. However, the 2019-2020 austral spring-summer was an exception, with over four times the previous maximum area burnt in southeast Australian temperate forests. Temperate forest fires have extensive socio-economic, human health, greenhouse gas emissions, and biodiversity impacts due to high fire intensities. A robust model that identifies driving factors of forest fires and relates impact thresholds to fire activity at regional scales would help land managers and fire-fighting agencies prepare for potentially hazardous fire in Australia. Here, we developed a machine-learning diagnostic model to quantify nonlinear relationships between monthly burnt area and biophysical factors in southeast Australian forests for 2001-2020 on a 0.25° grid based on several biophysical parameters, notably fire weather and vegetation productivity. Our model explained over 80% of the variation in the burnt area. We identified that burnt area dynamics in southeast Australian forest were primarily controlled by extreme fire weather, which mainly linked to fluctuations in the Southern Annular Mode (SAM) and Indian Ocean Dipole (IOD), with a relatively smaller contribution from the central Pacific El Niño Southern Oscillation (ENSO). Our fire diagnostic model and the non-linear relationships between burnt area and environmental covariates can provide useful guidance to decision-makers who manage preparations for an upcoming fire season, and model developers working on improved early warning systems for forest fires.

An optimized method for intratracheal instillation in mice.

Non-invasive intratracheal instillation is an important method for direct exposure of the respiratory tract which is commonly used in toxicology, environmental science, and other research fields. However, there is no standard operating process for non-invasive intratracheal instillation. To keep the reliability and accuracy of intratracheal instillation is vital, especially, for animal models of sub-chronic or chronic exposure which may need repeated operations performed on many animals. In this study, we improved the intratracheal instillation operation and verified the accuracy and reliability of this method. Adult female BALB/c mice were treated with ink solution, normal saline and PM2.5 suspension by the described intratracheal instillation method. After a short recovery, the mice were killed. The distribution of ink in the lungs and gastrointestinal tract of the mice was observed anatomically, and the dispersion of PM2.5 in the lungs and the status of lung injury were observed by pathological staining after 24 h. Scattered ink blots were observed in the lungs of the mice with instillation inks, but not in their gastrointestinal tract. Pathological staining of mouse lung showed that PM2.5 was distributed at the end of bronchiole and alveolar cavity, and caused diffuse acute lung injury in the mice. This study shows that the non-invasive intratracheal instillation method has good accuracy and reliability, which can reduce the use of mice, do less harm to the mice, and then improve 3R animal welfare. This method can be applied to establish a mouse model of short-term or long-term exposure through the respiratory tract.

Drinking Natural Mineral Water Maintains Bone Health in Young Rats With Metabolic Acidosis.

Introduction: Metabolic acidosis affects bone health. It remains unclear whether drinking natural mineral water is better for maintaining bone health in the youth with metabolic acidosis. Materials and Methods: Sixty young female rats (3-weeks-old) were randomly divided into three groups and drank purified water (PW, as control), bicarbonate-rich natural mineral water (Bic-NMW), or sulfate-rich natural mineral water (Sul-NMW), which, respectively, contained calcium (0.17, 155, and 175 mg/L), bicarbonate (0.1360, and 139 mg/L) and sulfate (0, 35.6, and 532 mg/L), for 16 weeks. In the last 3 weeks, metabolic acidosis was induced in 10 rats per group by adding NH4Cl (0.28 mM) to drinking water. The rats' blood, urine, and femur were collected for assessing acid-base status, calcium metabolism, bone microstructure, and strength. The difference between the three groups was determined using one-way ANOVA followed by the Student-Newman-Keuls test or Dunnett's T3 test. Results: Compared with the PW rats, the Bic-NMW rats and the Sul-NMW rats had less urine net acid excretion (-1.51, 0.20 vs. 10.77, EQ/L), higher bone mineral density (442.50, 407.49 vs. 373.28, mg/mm3), growth cartilage width (271.83, 283.83 vs. 233.27, µm) and cortical trabecular area (9.33, 9.55 vs. 5.05, mm2), and smaller cortical marrow cavity area (5.40, 5.49 vs. 7.27, mm2) in the femur (P < 0.05). Besides, the Bic-NMW rats had less serum calcium (2.53 vs. 2.68, mmol/L) and C-terminal cross-linked telopeptide of type-I collagen (1.35 vs. 1.93, ng/mL), and higher serum calcitonin (0.61 vs. 0.39, µg/L), femoral trabecular thickness (0.10 vs. 0.09, µm), bone volume/total volume (0.42 vs. 0.34, %), cortical bone area (15.91 vs. 12.80, mm2), and ultimate stress (35.12 vs. 29.32, MPa) (P < 0.05). The Sul-NMW rats had more osteoclasts (22.50 vs. 11.54, cells/field) (P < 0.05). Conclusions: Drinking natural mineral water, especially bicarbonate-rich natural mineral water, is effective in improving bone health in young rats with metabolic acidosis. These benefits include maintaining bone mineral density, and improving bone microstructure and biomechanical properties via moderating metabolic acidosis.

HOXB4 Mis-Regulation Induced by Microcystin-LR and Correlated With Immune Infiltration Is Unfavorable to Colorectal Cancer Prognosis.

Microcystin-LR (MC-LR) exists widely in polluted food and water in humid and warm areas, and facilitates the progression of colorectal cancer (CRC). However, the molecular mechanism associated with the MC-LR-induced CRC progression remains elusive. The purpose of this study is to explore the role of the hub genes associated with MC-LR-induced CRC development at the molecular, cellular and clinical levels through bioinformatics and traditional experiments. By utilizing R, we screened and investigated the differentially expressed genes (DEGs) between the MC-LR and the control groups with the GEO, in which, HOXB4 highly expressed in MC-LR-treated group was identified and further explored as a hub gene. With the aid of TCGA, GEPIA, HPA, UALCAN, Cistrome, and TIMER, the increased mRNA and protein levels of HOXB4 in CRC tissue were found to be positively associated with high tumor stage and poor prognosis, and were linked to immune infiltration, especially tumor-associated macrophages and cancer-associated fibroblasts. Cox regression analysis and nomogram prediction model indicated that high HOXB4 expression was correlated to poor survival probability. To elucidate the mechanism of high HOXB4 expression induced by MC-LR, we overlapped the genes involved in the MC-LR-mediated CRC pathways and the HOXB4-correlated transcription genes. Importantly, C-myc instead of PPARG and RUNX1 promoted the high expression of HOXB4 through experiment validation, and was identified as a key target gene. Interestingly, C-myc was up-regulated by HOXB4 and maintained cell cycle progression. In addition, MC-LR was proved to up-regulate HOXB4 expression, thus promoting proliferation and migration of Caco2 cells and driving the cell cycle progression. In conclusion, MC-LR might accelerate CRC progression. In the process, MC-LR induced C-myc augmentation elevates the high expression of HOXB4 through increasing the S phase cell proportion to enhance Caco2 cell proliferation. Therefore, HOXB4 might be considered as a potential prognostic biomarker for CRC.

Chronic nickel (II) exposure induces the stemness properties of cancer cells through repressing isocitrate dehydrogenase (IDH1).

BACKGROUND: Nickel is a component of biomedical alloys that is released during corrosion or friction and causes cytotoxicity, mutation, differentiation or even carcinogenesis in tissues. However, the mechanisms underlying the potential hazards of Nickel-containing alloys implanted in the human body by surgery remain uncertain. OBJECTIVE: To study the effect of Ni(II) (NiCl2•6H2O) on cancer cells. METHODS: A549 and RKO cells were treated with various concentrations of Ni(II) to determine the effect of Ni(II) on cellular viability using a CCK8 assay. Flow cytometry was performed to analyze the effect of Ni(II) on apoptosis and the cell cycle. Sphere-forming assays were conducted to examine the stemness properties of A549 and RKO cells. Western blotting was to evaluate the expression levels of SOX2, IDH1, HIF-1ɑ and ß-catenin. The expression of isocitrate dehydrogenase (IDH1) in rectum adenocarcinoma (READ) was analyzed by Gene Expression Profiling Interactive Analysis (GEPIA). Kaplan-Meier analysis was used to calculate the correlation between survival and IDH1 expression. RESULTS: Long-term exposure (120 days) to 100 µM Ni(II) significantly repressed cell proliferation, decreased colony formation and arrested the cell cycle at the G0/G1 phase. In addition, the stem-like traits of A549 and RKO cells were significantly augmented. Ni(II) also significantly decreased the protein expression of IDH1 and the synthesis rate of NAPDH, which competitively inhibited α-ketoglutarate (α-KG) generation. The downregulation of IDH1 not only promoted ß-catenin accumulation in the cell nucleus in a HIF-1ɑ signaling-dependent manner but also induced the expression of the transcription factor SOX2 to maintain the stemness properties of cancer cells. Moreover, IDH1 expression negatively correlated with the clinicopathologic characteristics of READ. CONCLUSION: These findings demonstrate that chronic and continuous release of Ni(II) to the microenvironment suppresses IDH1 expression and augments the stemness properties of cancer cells via the activation HIF-1ɑ/ß-catenin/SOX2 pathway to enhance local tumor recurrence in patients with implanted Nickel-containing alloys at surgical sites.

Breaking the Linear Scaling Relationship by Compositional and Structural Crafting of Ternary Cu-Au/Ag Nanoframes for Electrocatalytic Ethylene Production.

Electrocatalytic conversion of carbon dioxide into high-value multicarbon (C2+ ) chemical feedstocks offers a promising avenue to liberate the chemical industry from fossil-resource dependence and eventually close the anthropogenic carbon cycle but is severely impeded by the lack of high-performance catalysts. To break the linear scaling relationship of intermediate binding and minimize the kinetic barrier of CO2 reduction reactions, ternary Cu-Au/Ag nanoframes were fabricated to decouple the functions of CO generation and C-C coupling, whereby the former is promoted by the alloyed Ag/Au substrate and the latter is facilitated by the highly strained and positively charged Cu domains. Thus, C2 H4 production in an H-cell and a flow cell occurred with high Faradic efficiencies of 69±5 and 77±2 %, respectively, as well as good electrocatalytic stability and material durability. In situ IR and DFT calculations unveiled two competing pathways for C2 H4 generation, of which direct CO dimerization is energetically favored.

Application of improved ELM algorithm in the prediction of earthquake casualties.

BACKGROUND: Earthquake casualties prediction is a basic work of the emergency response. Traditional forecasting methods have strict requirements on sample data and lots of parameters are required to be set manually, which can result in poor results with low prediction accuracy and slow learning speed. METHOD: In this paper, the Extreme Leaning Machine (ELM) is introduced into the earthquake disaster casualty predictions with the purpose of improving the prediction accuracy. However, traditional ELM model still has the problems of poor network structure stability and low prediction accuracy. So an Adaptive Chaos Particle Swarm Optimization (ACPSO) is proposed to the optimize traditional ELM's network parameters to enhance network stability and prediction accuracy, and the improved ELM model is applied to earthquake disaster casualty prediction. RESULTS: The experimental results show that the earthquake disaster casualty prediction model based on ACPSO-ELM algorithm has better stability and prediction accuracy. CONCLUSION: ACPSO-ELM algorithm has better practicality and generalization in earthquake disaster casualty prediction.

Octahedral gold-silver nanoframes with rich crystalline defects for efficient methanol oxidation manifesting a CO-promoting effect.

Three-dimensional bimetallic nanoframes with high spatial diffusivity and surface heterogeneity possess remarkable catalytic activities owing to their highly exposed active surfaces and tunable electronic structure. Here we report a general one-pot strategy to prepare ultrathin octahedral Au3Ag nanoframes, with the formation mechanism explicitly elucidated through well-monitored temporal nanostructure evolution. Rich crystalline defects lead to lowered atomic coordination and varied electronic states of the metal atoms as evidenced by extensive structural characterizations. When used for electrocatalytic methanol oxidation, the Au3Ag nanoframes demonstrate superior performance with a high specific activity of 3.38 mA cm-2, 3.9 times that of the commercial Pt/C. More intriguingly, the kinetics of methanol oxidation on the Au3Ag nanoframes is counter-intuitively promoted by carbon monoxide. The enhancement is ascribed to the altered reaction pathway and enhanced OH- co-adsorption on the defect-rich surfaces, which can be well understood from the d-band model and comprehensive density functional theory simulations.

Risk assessment of earthquake network public opinion based on global search BP neural network.

BACKGROUND: The article proposes a network public opinion risk assessment model for earthquake disasters, which can provide an effective support for emergency departments of China. METHOD: It uses the accelerated genetic algorithm (AGA) to improve BP neural network. The main contents: This article selects 10 indexes by using the methods of the principal component analysis (PCA) and cumulative contribution (CC) to assess the risk of the earthquake network public opinion. The article designs a BP algorithm to measure the risk degree of the earthquake network public opinion and uses AGA to improve the BP model for parameter optimization. RESULTS: The experiment results of the improved BP model shows that its global error is 7.12×10, and the error is reduced to 22.35%, which showed the improving BP model has advantages in convergence speed and evaluation accuracy. CONCLUSION: The risk assessment method of network public opinion can be used in the practice of earthquake disaster decision.

Bandgap engineering of a lead-free defect perovskite Cs3Bi2I9 through trivalent doping of Ru3.

Inorganic defect halide compounds such as Cs3Bi2I9 have been regarded as promising alternatives to overcome the instability and toxicity issues of conventional perovskite solar cells. However, their wide indirect bandgaps and deep defect states severely limit their photoelectronic conversion efficiency when implemented in devices. Trivalent cation substitution has been proposed by previous calculations allowing the engineering of their band structures, but experimental evidences are still lacking. Herein we use the trivalent cation Ru3+ to partially replace Bi3+ in Cs3Bi2I9, and reveal their structural and optoelectronic properties, as well as the environmental stability. The Ru-doped Cs3Bi2I9 shows a decreasing bandgap with the increasing doping levels and an overall up-shift of band structure, owing to the dopant-induced defect states and thus enhanced phonon-electron coupling. As a result, upon Ru3+ doping, the narrowed bandgap and the upward shift of the band structures might facilitate and broaden their applications in optoelectronic devices.

Mining unexpected temporal associations: applications in detecting adverse drug reactions.

In various real-world applications, it is very useful mining unanticipated episodes where certain event patterns unexpectedly lead to outcomes, e.g., taking two medicines together sometimes causing an adverse reaction. These unanticipated episodes are usually unexpected and infrequent, which makes existing data mining techniques, mainly designed to find frequent patterns, ineffective. In this paper, we propose unexpected temporal association rules (UTARs) to describe them. To handle the unexpectedness, we introduce a new interestingness measure, residual-leverage, and develop a novel case-based exclusion technique for its calculation. Combining it with an event-oriented data preparation technique to handle the infrequency, we develop a new algorithm MUTARC to find pairwise UTARs. The MUTARC is applied to generate adverse drug reaction (ADR) signals from real-world healthcare administrative databases. It reliably shortlists not only six known ADRs, but also another ADR, flucloxacillin possibly causing hepatitis, which our algorithm designers and experiment runners have not known before the experiments. The MUTARC performs much more effectively than existing techniques. This paper clearly illustrates the great potential along the new direction of ADR signal generation from healthcare administrative databases.

Scalable model-based clustering for large databases based on data summarization.

The scalability problem in data mining involves the development of methods for handling large databases with limited computational resources such as memory and computation time. In this paper, two scalable clustering algorithms, bEMADS and gEMADS, are presented based on the Gaussian mixture model. Both summarize data into subclusters and then generate Gaussian mixtures from their data summaries. Their core algorithm, EMADS, is defined on data summaries and approximates the aggregate behavior of each subcluster of data under the Gaussian mixture model. EMADS is provably convergent. Experimental results substantiate that both algorithms can run several orders of magnitude faster than expectation-maximization with little loss of accuracy.

An efficient self-organizing map designed by genetic algorithms for the traveling salesman problem.

As a typical combinatorial optimization problem, the traveling salesman problem (TSP) has attracted extensive research interest. In this paper, we develop a self-organizing map (SOM) with a novel learning rule. It is called the integrated SOM (ISOM) since its learning rule integrates the three learning mechanisms in the SOM literature. Within a single learning step, the excited neuron is first dragged toward the input city, then pushed to the convex hull of the TSP, and finally drawn toward the middle point of its two neighboring neurons. A genetic algorithm is successfully specified to determine the elaborate coordination among the three learning mechanisms as well as the suitable parameter setting. The evolved ISOM (eISOM) is examined on three sets of TSP to demonstrate its power and efficiency. The computation complexity of the eISOM is quadratic, which is comparable to other SOM-like neural networks. Moreover, the eISOM can generate more accurate solutions than several typical approaches for TSP including the SOM developed by Budinich, the expanding SOM, the convex elastic net, and the FLEXMAP algorithm. Though its solution accuracy is not yet comparable to some sophisticated heuristics, the eISOM is one of the most accurate neural networks for the TSP.