LARP7 overexpression alleviates aortic senescence and atherosclerosis.

Atherosclerosis, characterized by the accumulation of lipid plaques on the inner walls of arteries, is the leading cause of heart attack, stroke and severe ischemic injuries. Senescent cells have been found to accumulate within atherosclerotic lesions and contribute to the progression of atherosclerosis. In our previous study, we discovered that suppressing Larp7 accelerates senescence by inhibiting Sirt1 activity, resulting in increased atherosclerosis in high-fat diet (HFD) fed and ApoE deficient (ApoEKO) mice. However, there has been no direct evidence demonstrating Larp7 per se could attenuate atherosclerosis. To this end, we generated a tetO-controlled and Cre-activated Larp7 gain-of-function mouse. Through RT-PCR and western blotting, we confirmed Larp7 overexpression in the aortas of HFD-fed ApoEKO; Larp7tetO mice. Larp7 overexpression led to increased Sirt1 activity and decreased cellular senescence signals mediated by p53/p65 in the aortas. Additionally, Larp7 overexpression reduced the presence of p16-positive senescent cells in the aortic lesions. Furthermore, Larp7 overexpression resulted in a decrease in pro-inflammatory macrophages and SASP factors. Consequently, Larp7 overexpression led to a reduction in the area of atherosclerotic lesions in HFD-fed ApoEKO; Larp7tetO mice. In summary, our study provides evidence that Larp7 overexpression holds promise as an approach to inhibit cellular senescence and prevent atherosclerosis.

Reactive oxygen species (ROS) modulate nitrogen signaling using temporal transcriptome analysis in foxtail millet.

Reactive oxygen species (ROS) is a chemically reactive chemical substance containing oxygen and a natural by-product of normal oxygen metabolism. Excessive ROS affect the growth process of crops, which will lead to the decrease of yield. Nitrogen, as a critical nutrient element in plants and plays a vital role in plant growth and crop production. Nitrate is the primary nitrogen source available to plants in agricultural soil and various natural environments. However, the molecular mechanism of ROS-nitrate crosstalk is still unclear. In this study, we used the foxtail millet (Setaria italica L.) as the material to figure it out. Here, we show that excessive NaCl inhibits nitrate-promoted plant growth and nitrogen use efficiency (NUE). NaCl induces ROS accumulation in roots, and ROS inhibits nitrate-induced gene expression in a short time. Surprisingly, low concentration ROS slight promotes and high concentration of ROS inhibits foxtail millet growth under long-term H2O2 treatment. These results may open a new perspective for further exploration of ROS-nitrate signaling pathway in plants.

Chemiluminescent Conjugated Polymer Nanoparticles for Deep-Tissue Inflammation Imaging and Photodynamic Therapy of Cancer.

Deep-tissue optical imaging and photodynamic therapy (PDT) remain a big challenge for the diagnosis and treatment of cancer. Chemiluminescence (CL) has emerged as a promising tool for biological imaging and in vivo therapy. The development of covalent-binding chemiluminescence agents with high stability and high chemiluminescence resonance energy transfer (CRET) efficiency is urgent. Herein, we design and synthesize an unprecedented chemiluminescent conjugated polymer PFV-Luminol, which consists of conjugated polyfluorene vinylene (PFV) main chains and isoluminol-modified side chains. Notably, isoluminol groups with chemiluminescent ability are covalently linked to main chains by amide bonds, which dramatically narrow their distance, greatly improving the CRET efficiency. In the presence of pathologically high levels of various reactive oxygen species (ROS), especially singlet oxygen (1O2), PFV-Luminol emits strong fluorescence and produces more ROS. Furthermore, we construct the PFV-L@PEG-NPs and PFV-L@PEG-FA-NPs nanoparticles by self-assembly of PFV-Luminol and amphiphilic copolymer DSPE-PEG/DSPE-PEG-FA. The chemiluminescent PFV-L@PEG-NPs nanoparticles exhibit excellent capabilities for in vivo imaging in different inflammatory animal models with great tissue penetration and resolution. In addition, PFV-L@PEG-FA-NPs nanoparticles show both sensitive in vivo chemiluminescence imaging and efficient chemiluminescence-mediated PDT for antitumors. This study paves the way for the design of chemiluminescent probes and their applications in the diagnosis and therapy of diseases.

D-BJH: The Intrinsic Model for Characterizing the Pore Size Distribution of Porous Materials.

A novel approach, the differential Barrett-Joyner-Halenda model (D-BJH), is proposed to address the limitations of the traditional BJH model in determining the pore size distribution (PSD). This method integrates multilayer adsorption and capillary condensation processes using advanced numerical techniques, notably, a Galerkin-based framework for solving the differential BJH equations. The D-BJH model offers a precise analytical framework, establishing itself as a benchmark in adsorption theory. It enables accurate PSD calculations and provides robust theoretical support for interpreting adsorption isotherms. Additionally, a simplified D-BJH method allows for direct point-by-point PSD calculation, reducing computational complexity and eliminating cumulative errors inherent in traditional methods like BJH, DH, CI, and VBS. The D-BJH model demonstrates that PSD is directly related to the differential function of the isotherm and pore size concerning relative pressure. Comparative analyses with BJH, DH, and NLDFT models show that D-BJH effectively explains fundamental adsorption mechanisms, such as the "spurious peak" observed in desorption branches. This work expands the applicability of the BJH model, proving that both the D-BJH model and its simplified method are accurate and comprehensive for characterizing the pore structures of microporous and mesoporous materials.

Identification of systemic nitrogen signaling in foxtail millet (Setaria italica) roots based on split-root system and transcriptome analysis.

KEY MESSAGE: The study established split-root system (SRS) in foxtail millet, and identified the molecular regulatory mechanisms and metabolic pathways related to systemic nitrogen signaling based on this system and transcriptome analysis. The growth of crops is primarily constrained by the availability of nitrogen (N), an essential nutrient. Foxtail millet (Setaria italica L.) is a significant orphan crop known for its strong tolerance to barren conditions. Despite this, the signaling pathway of nitrogen in foxtail millet remains largely unexplored. Identifying the candidate genes responsible for nitrogen response in foxtail millet is crucial for enhancing its agricultural productivity. This study utilized the split-root system (SRS) in foxtail millet to uncover genes associated with Systemic Nitrogen Signaling (SNS). Transcriptome analysis of the SRS revealed 2158 differentially expressed genes (DEGs) implicated in SNS, including those involved in cytokinin synthesis, transcription factors, E3 ubiquitin ligase, and ROS metabolism. Silencing of SiIPT5 and SiATL31 genes through RNAi in transgenic plants resulted in reduced SNS response, indicating their role in the nitrogen signaling pathway of foxtail millet. Furthermore, the induction of ROS metabolism-related genes in response to KNO3 of the split-root System (Sp.KNO3) suggests a potential involvement of ROS signaling in the SNS of foxtail millet. Overall, this study sheds light on the molecular regulatory mechanisms and metabolic pathways of foxtail millet in relation to SNS.

Free-space coupled, large-active-area superconducting microstrip single-photon detector for photon-counting time-of-flight imaging.

Numerous applications at the photon-starved regime require a free-space coupling single-photon detector with a large active area, low dark count rate (DCR), and superior time resolutions. Here, we developed a superconducting microstrip single-photon detector (SMSPD), with a large active area of 260 µm in diameter, a DCR of ∼5k c p s, and a low time jitter of ∼171p s, operated at a near-infrared of 1550 nm and a temperature of ∼2.0K. As a demonstration, we applied the detector to a single-pixel galvanometer scanning system and successfully reconstructed the object information in depth and intensity using a time-correlated photon counting technology.

Single Image Super-Resolution via Wide-Activation Feature Distillation Network.

Feature extraction plays a pivotal role in the context of single image super-resolution. Nonetheless, relying on a single feature extraction method often undermines the full potential of feature representation, hampering the model's overall performance. To tackle this issue, this study introduces the wide-activation feature distillation network (WFDN), which realizes single image super-resolution through dual-path learning. Initially, a dual-path parallel network structure is employed, utilizing a residual network as the backbone and incorporating global residual connections to enhance feature exploitation and expedite network convergence. Subsequently, a feature distillation block is adopted, characterized by fast training speed and a low parameter count. Simultaneously, a wide-activation mechanism is integrated to further enhance the representational capacity of high-frequency features. Lastly, a gated fusion mechanism is introduced to weight the fusion of feature information extracted from the dual branches. This mechanism enhances reconstruction performance while mitigating information redundancy. Extensive experiments demonstrate that the proposed algorithm achieves stable and superior results compared to the state-of-the-art methods, as evidenced by quantitative evaluation metrics tests conducted on four benchmark datasets. Furthermore, our WFDN excels in reconstructing images with richer detailed textures, more realistic lines, and clearer structures, affirming its exceptional superiority and robustness.

Millimeter-scale active area superconducting microstrip single-photon detector fabricated by ultraviolet photolithography.

The effective and convenient detection of single photons via advanced detectors with a large active area is becoming significant for quantum and classical applications. This work demonstrates the fabrication of a superconducting microstrip single-photon detector (SMSPD) with a millimeter-scale active area via the use of ultraviolet (UV) photolithography. The performances of NbN SMSPDs with different active areas and strip widths are characterized. SMSPDs fabricated by UV photolithography and electron beam lithography with small active areas are also compared from the aspects of the switching current density and line edge roughness. Furthermore, an SMSPD with an active area of 1 mm × 1 mm is obtained via UV photolithography, and during operation at 0.85 K, it exhibits near-saturated internal detection efficiency at wavelengths up to 800 nm. At a wavelength of 1550 nm, the detector exhibits a system detection efficiency of ∼5% (7%) and a timing jitter of 102 (144) ps, when illuminated with a light spot of ∼18 (600) µm in diameter, respectively.

High-efficiency broadband fiber-to-chip coupler using a 3D nanoprinting microfiber.

We propose a method for coupling a tapered optical fiber to an inverted tapered SiN waveguide by fabricating a microfiber using 3D nanoprinting lithography. The microfiber consists of three parts: a tapered cladding cap, an S-bend, and a straight part, all composed of high-refractive-index material. Light is adiabatically coupled from the tapered fiber to the printed microfiber through the cladding cap. The light is then transmitted through the S-bend and the straight part with low loss and is finally coupled to the waveguide through the evanescent field. In the simulation, our design can achieve a high coupling efficiency (TE mode) of ∼97% at a wavelength of 1542 nm with a wide bandwidth of ∼768n m at the 1-dB cutoff criterion.

Multi-Phase Fusion for Pedestrian Localization Using Mass-Market GNSS and MEMS Sensors.

Precise pedestrian positioning based on smartphone-grade sensors has been a research hotspot for several years. Due to the poor performance of the mass-market Micro-Electro-Mechanical Systems (MEMS) Magnetic, Angular Rate, and Gravity (MARG) sensors, the standalone pedestrian dead reckoning (PDR) module cannot avoid long-time heading drift, which leads to the failure of the entire positioning system. In outdoor scenes, the Global Navigation Satellite System (GNSS) is one of the most popular positioning systems, and smartphone users can use it to acquire absolute coordinates. However, the smartphone's ultra-low-cost GNSS module is limited by some components such as the antenna, and so it is susceptible to serious interference from the multipath effect, which is a main error source of smartphone-based GNSS positioning. In this paper, we propose a multi-phase GNSS/PDR fusion framework to overcome the limitations of standalone modules. The first phase is to build a pseudorange double-difference based on smartphone and reference stations, the second phase proposes a novel multipath mitigation method based on multipath partial parameters estimation (MPPE) and a Double-Difference Code-Minus-Carrier (DDCMC) filter, and the third phase is to propose the joint stride lengths and heading estimations of the two standalone modules, to reduce the long-time drift and noise. The experimental results demonstrate that the proposed multipath error estimation can effectively suppress the double-difference multipath error exceeding 4 m, and compared to other methods, our fusion method achieves a minimum error RMSE of 1.63 m in positioning accuracy, and a minimum error RMSE of 4.71 m in long-time robustness for 20 min of continuous walking.

Exosomal Wnt7a from a low metastatic subclone promotes lung metastasis of a highly metastatic subclone in the murine 4t1 breast cancer.

BACKGROUND: Patients with triple-negative breast cancer (TNBC) often have poorer prognosis than those with other subtypes because of its aggressive behaviors. Cancer cells are heterogeneous, and only a few highly metastatic subclones metastasize. Although the majority of subclones may not metastasize, they could contribute by releasing factors that increase the capacity of highly metastatic cells and/or provide a favorable tumor microenvironment (TME). Here, we analyzed the interclonal communication in TNBC which leads to efficient cancer progression, particularly lung metastasis, using the polyclonal murine 4T1 BC model. METHODS: We isolated two 4T1 subclones, LM.4T1 and HM.4T1 cells with a low and a high metastatic potential, respectively, and examined the effects of LM.4T1 cells on the behaviors of HM.4T1 cells using the cell scratch assay, sphere-forming assay, sphere invasion assay, RT-qPCR, and western blotting in vitro. We also examined the contribution of LM.4T1 cells to the lung metastasis of HM.4T1 cells and TME in vivo. To identify a critical factor which may be responsible for the effects by LM.4T1 cells, we analyzed the data obtained from the GEO database. RESULTS: Co-injection of LM.4T1 cells significantly augmented lung metastases by HM.4T1 cells. LM.4T1-derived exosomes promoted the migration and invasion of HM.4T1 cells in vitro, and blocking the secretion of exosome abrogated their effects on HM.4T1 cells. Analyses of data obtained from the GEO database suggested that Wnt7a might be a critical factor responsible for the enhancing effects. In fact, a higher level of Wnt7a was detected in LM.4T1 cells, especially in exosomes, than in HM.4T1 cells, and deletion of Wnt7a in LM.4T1 cells significantly decreased the lung metastasis of HM.4T1 cells. Further, treatment with Wnt7a increased the spheroid formation by HM.4T1 cells via activation of the PI3K/Akt/mTOR signaling pathway. Finally, infiltration of αSMA-positive fibroblasts and angiogenesis was more prominent in tumors of LM.4T1 cells and deletion of Wnt7a in LM.4T1 cells markedly reduced angiogenesis. CONCLUSIONS: We demonstrated, for the first time, that a low metastatic subclone can enhance lung metastasis of highly metastatic subclone via exosomal Wnt7a and propose Wnt7a as a molecular target to treat TNBC patients.

Se-H-free As2Se3 fiber and its spectral applications in the mid-infrared.

The complete removal of the impurities like Se-H in Se-based chalcogenide glasses has been challenging in the development of highly transparent chalcogenide glass fiber. In this paper, several purification methods, including dynamic distillation, static distillation, and combined distillation method, were adopted with an aim of purifying arsenic selenide glass with ultra-low content of the impurities. The experimental results demonstrated that the Se-H can be completely eliminated in the arsenic selenide glass host and fiber without the introduction of any chloride. We further explored the applications of such low loss and Se-H-free chalcogenide glass fiber in the mid-infrared. It was found that, using such a Se-H free fiber, a flattened supercontinuum spectrum above the -30 dB level from 1.2 to 13 µm was generated from the Se-H free fiber with a 5.5 µm laser pumping. The sensitivity was found to be improved 5.1 times for CO2 gas in the 3 to 6 µm wavelength range.

Comparison of femoral mechanics before and after internal fixation removal and the effect of sclerosis on femoral stress: a finite element analysis.

BACKGROUND: Femoral neck fractures are a common traumatic injury. The removal of the internal fixation remains controversial, especially in terms of mechanical stability. Moreover, collapsed necrosis of the femoral head continues to occur after fracture healing. We believe that sclerotic cancellous bone (SCB) formation around the screw is associated with femoral head necrosis. We aimed to compare mechanical features before and after implant removal and determine the effect of SCB formation on stress distribution. METHODS: Cylindrical cancellous bone sections were collected from a relatively normal region and an SCB region of a necrotic femoral head, and their elastic moduli were measured. Four femoral finite element models were developed: a) femoral neck fracture healing with implants, b) fracture healing without implants, c) sclerosis around the screw with implants, and d) sclerosis around the screw without implants. RESULTS: The maximum von Mises peak stresses of models a and b were 66.643 MPa and 63.76 MPa, respectively, and were concentrated in the upper lateral femur. The main stress was scattered at the lowest screw tail, femoral calcar region, and lateral femur shaft. Moreover, coronal plane strain throughout the screw paths near the femoral head in models a and b was mostly in the range of 1000-3000 µÎµ. The maximum stress concentrations in models c and d were located at the lower femoral head and reached 91.199 MPa and 78.019 MPa, respectively. CONCLUSIONS: The stresses in the sclerotic model around the cannulated screws are more concentrated on the femoral head than in the healing model without sclerotic bone. The overall stresses in the healing femoral neck fracture model were essentially unchanged before and after removal of the internal fixation.

Mesoporous Polymeric Cyanamide-Triazole-Heptazine Photocatalysts for Highly-Efficient Water Splitting.

Conjugated polymers are promising light harvesters for water reduction/oxidation due to their simple synthesis and adjustable bandgap. Herein, both cyanamide and triazole functional groups are first incorporated into a heptazine-based carbon nitride (CN) polymer, resulting in a mesoporous conjugated cyanamide-triazole-heptazine polymer (CTHP) with different compositions by increasing the quantity of cyanamide/triazole units in the CN backbone. Varying the compositions of CTHP modulates its electronic structures, mesoporous morphologies, and redox energies, resulting in a significantly improved photocatalytic performance for both H2 and O2 evolution under visible light irradiation. A remarkable H2 evolution rate of 12723 µmol h-1 g-1 is observed, resulting in a high apparent quantum yield of 11.97% at 400 nm. In parallel, the optimized photocatalyst also exhibits an O2 evolution rate of 221 µmol h-1  g-1 , 9.6 times higher than the CN counterpart, with the value being the highest among the reported CN-based bifunctional photocatalysts. This work provides an efficient molecular engineering approach for the rational design of functional polymeric photocatalysts.

Correlation of skull morphology and bite force in a bird-eating bat (Ia io; Vespertilionidae).

BACKGROUND: Genetic and ecological factors influence morphology, and morphology is compatible with function. The morphology and bite performance of skulls of bats show a number of characteristic feeding adaptations. The great evening bat, Ia io (Thomas, 1902), eats both insects and birds (Thabah et al. J Mammal 88: 728-735, 2007), and as such, it is considered to represent a case of dietary niche expansion from insects to birds. How the skull morphology or bite force in I. io are related to the expanded diet (that is, birds) remains unknown. We used three-dimensional (3D) geometry of the skulls and measurements of bite force and diets from I. io and 13 other species of sympatric or closely related bat species to investigate the characteristics and the correlation of skull morphology and bite force to diets. RESULTS: Significant differences in skull morphology and bite force among species and diets were observed in this study. Similar to the carnivorous bats, bird-eaters (I. io) differed significantly from insectivorous bats; I. io had a larger skull size, taller crania, wider zygomatic arches, shorter but robust mandibles, and larger bite force than the insectivores. The skull morphology of bats was significantly associated with bite force whether controlling for phylogeny or not, but no significant correlations were found between diets and the skulls, or between diets and residual bite force, after controlling for phylogeny. CONCLUSIONS: These results indicated that skull morphology was independent of diet, and phylogeny had a greater impact on skull morphology than diet in these species. The changes in skull size and morphology have led to variation in bite force, and finally different bat species feeding on different foods. In conclusion, I. io has a larger skull size, robust mandibles, shortened dentitions, longer coronoid processes, expanded angular processes, low condyles, and taller cranial sagittal crests, and wider zygomatic arches that provide this species with mechanical advantages; their greater bite force may help them use larger and hard-bodied birds as a dietary component.

Differentiating between malignant and benign solid solitary pulmonary lesions: are intravoxel incoherent motion and diffusion kurtosis imaging superior to conventional diffusion-weighted imaging?

OBJECTIVE: To quantitatively compare the diagnostic values of various diffusion parameters obtained from mono- and biexponential diffusion-weighted imaging (DWI) models and diffusion kurtosis imaging (DKI) in differentiating between benign and malignant solitary pulmonary lesions (SPLs). METHODS: Multiple b-value DWIs and DKIs were performed in 89 patients with SPL by using a 3-T magnetic resonance (MR) imaging unit. The apparent diffusion coefficient (ADC) of various b-value sets, true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), apparent diffusional kurtosis (Kapp), and kurtosis-corrected diffusion coefficient (Dapp) were calculated and compared between the malignant and benign groups using a Mann-Whitney U test. Receiver-operating characteristic analysis was performed for all parameters. RESULT: The ADC(0, 150) values of malignant tumors were lower than those of the benign group (p = 0.01). The ADC(0, 300), ADC(0, 500), ADC(0, 600), ADC(0, 800), ADC(0, 1000), ADCtotal, D, and Dapp of malignant tumors were significantly lower than those of benign lesions (all p < 0.001). D*, f, and Kapp showed no statistically significant differences between the two groups. ADCtotal showed the highest area under the curve (AUC = 0.862), followed by ADC(0, 800)(AUC = 0.844), ADC(0, 600)(AUC = 0.843), D(AUC = 0.834), ADC(0, 1000)(AUC = 0.834) and ADC(0, 500)(AUC = 0.824), Dapp(AUC = 0.796), and ADC(0, 300) (AUC = 0.773). However, the difference in diagnostic efficacy among these parameters was not statistically significant (p > 0.05). CONCLUSION: Intravoxel incoherent motion (IVIM) and DKI-derived parameters have similar performance compared with conventional ADC in differentiating SPLs. KEY POINTS: • Mono- and biexponential DWI and DKI are feasible for differentiating SPLs. • ADC (0, ≥500) has better performance than ADC (0, <500) in assessing SPLs. • IVIM and DKI have similar performance compared with conventional DWI in differentiating SPLs.

A State Optimization Model Based on Kalman Filtering and Robust Estimation Theory for Fusion of Multi-Source Information in Highly Non-linear Systems.

Consistent state estimation is a vital requirement in numerous real life applications from localization to multi-source information fusion. The Kalman filter and its variants have been successfully used for solving state estimation problems. Kalman filtering-based estimators are dependent upon system model assumptions. A deviation from defined assumptions may lead to divergence or failure of the system. In this work, we propose a Kalman filtering-based robust state estimation model using statistical estimation theory. Its primary intention is for multiple source information fusion, although it is applicable to most non-linear systems. First, we propose a robust state prediction model to maintain state constancy over time. Secondly, we derive an error covariance estimation model to accept deviations in the system error assumptions. Afterward, an optimal state is attained in an iterative process using system observations. A modified robust MM estimation model is executed within every iteration to minimize the impact of outlying observation and approximation errors by reducing their weights. For systems having a large number of observations, a subsampling process is introduced to intensify the optimized solution redundancy. Performance is evaluated for numerical simulation and real multi sensor data. Results show high precision and robustness of proposed scheme in state estimation.

Statistical Multipath Model Based on Experimental GNSS Data in Static Urban Canyon Environment.

A deep understanding of multipath characteristics is essential to design signal simulators and receivers in global navigation satellite system applications. As a new constellation is deployed and more applications occur in the urban environment, the statistical multipath models of navigation signal need further study. In this paper, we present statistical distribution models of multipath time delay, multipath power attenuation, and multipath fading frequency based on the experimental data in the urban canyon environment. The raw data of multipath characteristics are obtained by processing real navigation signal to study the statistical distribution. By fitting the statistical data, it shows that the probability distribution of time delay follows a gamma distribution which is related to the waiting time of Poisson distributed events. The fading frequency follows an exponential distribution, and the mean of multipath power attenuation decreases linearly with an increasing time delay. In addition, the detailed statistical characteristics for different elevations and orbits satellites is studied, and the parameters of each distribution are quite different. The research results give useful guidance for navigation simulator and receiver designers.

A Role for Tubular Necroptosis in Cisplatin-Induced AKI.

Cell death and inflammation in the proximal tubules are the hallmarks of cisplatin-induced AKI, but the mechanisms underlying these effects have not been fully elucidated. Here, we investigated whether necroptosis, a type of programmed necrosis, has a role in cisplatin-induced AKI. We found that inhibition of any of the core components of the necroptotic pathway-receptor-interacting protein 1 (RIP1), RIP3, or mixed lineage kinase domain-like protein (MLKL)-by gene knockout or a chemical inhibitor diminished cisplatin-induced proximal tubule damage in mice. Similar results were obtained in cultured proximal tubular cells. Furthermore, necroptosis of cultured cells could be induced by cisplatin or by a combination of cytokines (TNF-α, TNF-related weak inducer of apoptosis, and IFN-γ) that were upregulated in proximal tubules of cisplatin-treated mice. However, cisplatin induced an increase in RIP1 and RIP3 expression in cultured tubular cells in the absence of cytokine release. Correspondingly, overexpression of RIP1 or RIP3 enhanced cisplatin-induced necroptosis in vitro. Notably, inflammatory cytokine upregulation in cisplatin-treated mice was partially diminished in RIP3- or MLKL-deficient mice, suggesting a positive feedback loop involving these genes and inflammatory cytokines that promotes necroptosis progression. Thus, our data demonstrate that necroptosis is a major mechanism of proximal tubular cell death in cisplatin-induced nephrotoxic AKI.

Statistical and machine learning analysis for the application of microbially induced carbonate precipitation as a physical barrier to control seawater intrusion.

Seawater intrusion in coastal aquifers is a significant problem that can be addressed through the construction of subsurface dams or physical cut-off barriers. An alternative method is the use of microbially induced carbonate precipitation (MICP) to reduce the hydraulic conductivity of the porous medium and create a physical barrier. However, the effectiveness of this method depends on various factors, and the scientific literature presents conflicting results, making it challenging to generalise the findings. To overcome this challenge, a statistical and machine learning (ML) approach is employed to infer the causes for the reduction in hydraulic conductivity and identify the optimum MICP parameters for preventing seawater intrusion. The study involves data curation, exploratory analysis, and the development of various models to fit the input data (k-Nearest Neighbours - kNN, Support Vector Regression - SVR, Random Forests - RF, Gradient Boosting - XgBoost, Linear model with interaction terms, Ensemble learning algorithms with weighted averages - EnL-WA and stacking - EnL-Stack). The models performed reasonably well in the region where permeability reduction is sensitive to carbonate increase capturing the permeability reduction profile with respect to cementation level while demonstrating that they can be used in initial assessments of the specific conditions (e.g., soil properties). The best performing algorithms were the EnL-Stack and RF followed by XgBoost and SVR. The MICP method is effective in reducing hydraulic conductivity provided that the various biochemical parameters are optimised. Critical biochemical parameters for successful MICP formulations are the bacterial optical density, the urease activity, calcium chloride concentration and flow rate as well as the interaction terms across the properties of the porous media and the biochemical parameters. The models were used to identify the optimum MICP formulation for various porous media properties and the maximum permeability reduction profiles across cementation levels have been derived.