Minimizing energy footprint of seawater desalination system via wind power generation in coastal areas.

Wind power has become an essential direction for transforming energy structures in energy-intensive seawater desalination under the dual goals of carbon peaking and carbon neutrality. In this study, the energy footprint of the case project is analyzed by combining the hybrid life cycle analysis and environmentally extended input-output modeling, which is compared with the traditional thermal desalination processes from the whole life cycle perspective. The analysis revealed that the total energy consumption of the seawater desalination driven by wind power generation can be reduced by 79.77% compared with the traditional thermal drive mode under the same water production scale. Although the energy consumption in the construction phase accounts for 24.97% of the total, the energy consumption per unit of water production can be reduced by about 80% after adopting wind power technologies. The payback period is 7.2 years, that is, the energy consumption can be balanced after around 7 years during the operation phase. The results showed that the wind-driven seawater desalination system can significantly decrease the energy consumption of the project, which attempts to provide implications for the upgrading of energy-intensive seawater desalination in coastal areas towards low-carbon transition.

Female patients with hepatitis B may exhibit a reduced risk of breast cancer: A review of NHANES data.

Hepatic viral infections and breast cancer (BC) constitute major global health challenges, yet the interconnection between these hepatic infections and BC continues to be ambiguous. Conducting a comprehensive evaluation of the link between hepatitis virus infection and the incidence of BC and leveraging data from the National Health and Nutrition Examination Survey covering the period from 1999 to March 2022, we utilized logistic regression and subgroup analysis, among other methodologies, to execute a cross-sectional investigation. The univariate logistic regression analysis elucidates that individuals classified as non-Hispanic White exhibit a markedly higher incidence of BC at 2.620 (95% confidence interval [CI], 1.117-7.676; P = .045); moreover, advanced age at 1.063 (95% CI, 1.036-1.093; P < .001), elevated educational attainment at 1.962 (95% CI, 1.17-3.366; P = .012), and higher income levels at 2.835 (95% CI, 1.303-7.439; P = .017) emerge as significant predisposing factors for BC. In contrast, a greater number of live births significantly diminishes the risk of BC, reducing the incidence to 81.1% with each additional birth. Pertaining to hepatitis and vaccination status, our analysis distinctly demonstrates that only hepatitis B at 0.110 (95% CI, 0.018-0.353; P = .002) bears a significant inverse relationship with BC risk, suggesting a protective effect. The multivariate logistic regression analysis further reveals a negative association between hepatitis B infection and BC incidence, whereas hepatitis B vaccination shows a positive correlation with the disease incidence. After adjusting for all covariates, model 3 delineates odds ratios (95% CI) as follows: 0.14 (0.02-0.50; P = .009) and 1.92 (0.99-3.62; P = .046). Our investigation uncovers that within the general populace, there exists an inverse correlation between hepatitis B infection and BC incidence; in addition, the administration of the hepatitis B virus vaccine is potentially positively associated with the prevalence of BC.

Review of energy self-circulation systems integrating biogas utilization with Powerfuels production in global livestock industry.

Energy self-circulation systems, defined as energy systems incorporating the recycling utilization of waste biomass, have been proposed to reduce greenhouse gases emissions from livestock sector. In this study, a comprehensive review of the situation and challenges of biogas utilization in the livestock industry was provided. Moreover, two technological routes were proposed for a circular livestock system combined with Powerfuels production (CP-CLS), starting from biogas combustion for power generation and steam reforming to the sustainable development path of synthesizing, storing, and utilizing Powerfuels. The self-circulation capability and comprehensive benefits of the CP-CLS life cycle was discussed, along with future application scenarios and proposed standards for Powerfuels. To realize this potential, continuous research, development, and policy support are crucial. This study envisions the next generation of energy self-circulation systems, which expects to reduce the negative effect of livestock industry on climate change and promote sustainable development.

Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: a cross-sectional survey and Mendelian randomization analysis.

Background and objective: Heavy metals, ubiquitous in the environment, pose a global public health concern. The correlation between these and diabetic kidney disease (DKD) remains unclear. Our objective was to explore the correlation between heavy metal exposures and the incidence of DKD. Methods: We analyzed data from the NHANES (2005-2020), using machine learning, and cross-sectional survey. Our study also involved a bidirectional two-sample Mendelian randomization (MR) analysis. Results: Machine learning reveals correlation coefficients of -0.5059 and - 0.6510 for urinary Ba and urinary Tl with DKD, respectively. Multifactorial logistic regression implicates urinary Ba, urinary Pb, blood Cd, and blood Pb as potential associates of DKD. When adjusted for all covariates, the odds ratios and 95% confidence intervals are 0.87 (0.78, 0.98) (p = 0.023), 0.70 (0.53, 0.92) (p = 0.012), 0.53 (0.34, 0.82) (p = 0.005), and 0.76 (0.64, 0.90) (p = 0.002) in order. Furthermore, multiplicative interactions between urinary Ba and urinary Sb, urinary Cd and urinary Co, urinary Cd and urinary Pb, and blood Cd and blood Hg might be present. Among the diabetic population, the OR of urinary Tl with DKD is a mere 0.10, with a 95%CI of (0.01, 0.74), urinary Co 0.73 (0.54, 0.98) in Model 3, and urinary Pb 0.72 (0.55, 0.95) in Model 2. Restricted Cubic Splines (RCS) indicate a linear linkage between blood Cd in the general population and urinary Co, urinary Pb, and urinary Tl with DKD among diabetics. An observable trend effect is present between urinary Pb and urinary Tl with DKD. MR analysis reveals odds ratios and 95% confidence intervals of 1.16 (1.03, 1.32) (p = 0.018) and 1.17 (1.00, 1.36) (p = 0.044) for blood Cd and blood Mn, respectively. Conclusion: In the general population, urinary Ba demonstrates a nonlinear inverse association with DKD, whereas in the diabetic population, urinary Tl displays a linear inverse relationship with DKD.

Adverse drug events associated with fluorouracil use in patients with metastatic colorectal cancer: a real-world pharmacovigilance study based on the FDA adverse event reporting system.

BACKGROUND: Fluorouracil (5-FU) is widely used to treat metastatic colorectal cancer (mCRC), but real-world safety data is limited. Our study aimed to evaluate 5-FU's safety profile in a large mCRC population using the FAERS database. RESEARCH DESIGN AND METHODS: We conducted disproportionality analyses to identify adverse drug events associated with 5-FU use in mCRC patients from 2004 to 2023. Subgroup analyses, gender difference analyses, and logistic regression were also performed. RESULTS: We identified 1,458 reports with 5-FU as the primary suspected drug, with males accounting for 48.8% of reports. Gastrointestinal disorders were the most common adverse event (864 cases), while pregnancy-related conditions showed the strongest signal intensity (ROR = 2.97). We found 19 preferred terms with positive signals, including ischemic hepatitis (ROR = 59.32), blood iron increased (ROR = 59.32), and stress cardiomyopathy (ROR = 51.94). Males were more susceptible to weight loss and skin toxicity. Most adverse events occurred within the first month of 5-FU administration. CONCLUSION: Our study provides a comprehensive analysis of 5-FU's safety profile in mCRC patients, helping healthcare professionals mitigate risks in clinical practice.

A comprehensive review of natural product-derived compounds acting on P2X7R: The promising therapeutic drugs in disorders.

BACKGROUND: The P2X7 receptor (P2X7R) is known to play a significant role in regulating various pathological processes associated with immune regulation, neuroprotection, and inflammatory responses. It has emerged as a potential target for the treatment of diseases. In addition to chemically synthesized small molecule compounds, natural products have gained attention as an important source for discovering compounds that act on the P2X7R. PURPOSE: To explore the research progress made in the field of natural product-derived compounds that act on the P2X7R. METHODS: The methods employed in this review involved conducting a thorough search of databases, include PubMed, Web of Science and WIKTROP, to identify studies on natural product-derived compounds that interact with P2X7R. The selected studies were then analyzed to categorize the compounds based on their action on the receptor and to evaluate their therapeutic applications, chemical properties, and pharmacological actions. RESULTS: The natural product-derived compounds acting on P2X7R can be classified into three categories: P2X7R antagonists, compounds inhibiting P2X7R expression, and compounds regulating the signaling pathway associated with P2X7R. Moreover, highlight the therapeutic applications, chemical properties and pharmacological actions of these compounds, and indicate areas that require further in-depth study. Finally, discuss the challenges of the natural products-derived compounds exploration, although utilizing compounds from natural products for new drug research offers unique advantages, problems related to solubility, content, and extraction processes still exist. CONCLUSION: The detailed information in this review will facilitate further development of P2X7R antagonists and potential therapeutic strategies for P2X7R-associated disorders.

A 10-m national-scale map of ground-mounted photovoltaic power stations in China of 2020.

We provide a remote sensing derived dataset for large-scale ground-mounted photovoltaic (PV) power stations in China of 2020, which has high spatial resolution of 10 meters. The dataset is based on the Google Earth Engine (GEE) cloud computing platform via random forest classifier and active learning strategy. Specifically, ground samples are carefully collected across China via both field survey and visual interpretation. Afterwards, spectral and texture features are calculated from publicly available Sentinel-2 imagery. Meanwhile, topographic features consisting of slope and aspect that are sensitive to PV locations are also included, aiming to construct a multi-dimensional and discriminative feature space. Finally, the trained random forest model is adopted to predict PV power stations of China parallelly on GEE. Technical validation has been carefully performed across China which achieved a satisfactory accuracy over 89%. Above all, as the first publicly released 10-m national-scale distribution dataset of China's ground-mounted PV power stations, it can provide data references for relevant researchers in fields such as energy, land, remote sensing and environmental sciences.

Does proton pump inhibitors use increase risk of digestive tumors?: A 2-sample Mendelian randomization study.

The objective of this study was to explore the causal relationship between the use of proton pump inhibitors (PPIs) and 16 types of digestive system tumors. We utilized a 2-sample Mendelian randomization (MR) approach to investigate this relationship. We obtained exposure and outcome data from the UK Biobank and the Finland Biobank, respectively. The genetic data used in the analysis were derived from genome-wide association studies (GWAS) studies conducted on European populations. We screened single nucleotide polymorphisms significantly associated with the use of omeprazole, a commonly used PPIs, as instrumental variables. We then performed MR analyses using the inverse variance weighting (IVW) method, MR-Egger regression, and the weighted median method to evaluate the causal effect of omeprazole use on the 16 types of digestive system tumors. Our MR analysis revealed a significant causal relationship between the use of omeprazole and pancreatic malignancies, but not with any other types of digestive system tumors. The IVW analysis showed an odds ratio of 4.33E-05 (95%CI: [4.87E-09, 0.38], P = .03) and the MR-Egger analysis showed an odds ratio of 5.81E-11 (95%CI: [2.82E-20, 0.12], P = .04). We found no significant heterogeneity or pleiotropy, and sensitivity analysis confirmed the robustness of our results. Furthermore, statistical power calculations suggested that our findings were reliable. Conclusion The use of PPIs is a protective factor for pancreatic malignancies, but no causal relationship has been found with other digestive system tumors.

Simultaneous magnetic field and temperature measurement with high resolution based on cascaded microwave photonic filters.

A simultaneous magnetic field and temperature sensing scheme based on cascaded microwave photonic filters (MPFs) with high resolution is proposed and experimentally demonstrated. A polarization maintaining fiber bonded with a giant magnetostrictive material acts both as a magnetic field sensing probe and an important unit of a dispersion-induced MPF. A 500 m single mode fiber in a two-tap MPF is used to perform temperature compensation. The power fading frequency of the dispersion-induced MPF and the dip frequency of the two-tap MPF are selected to monitor the magnetic field and temperature changes. When temperature changes, both power fading frequency and dip frequency will change. While only power fading frequency shifts as magnetic field changes. Consequently, dual parameter sensing can be achieved by monitoring the characteristic microwave frequencies of the two MPFs. The temperature cross-sensitivity is well resolved in this way. In the experiment, the microwave frequency changes 5.84 MHz as external magnetic field increases by 1 mT. The corresponded theoretical resolution can reach 0.17 nT, which is only limited by the minimum resolution of vector network analyzer.

The robustness and disturbance within China's industrial complex network under carbon border tariffs.

Since the European Commission proposed in July 2021 to implement a Carbon Border Adjustment Mechanism (CBAM), the impact mechanism has received increasing attention worldwide. This study aims to analyze the impact of carbon border tariffs on China's carbon-intensive industries and simulate the risk transmission within China's industrial complex network based on the complex network modeling and cascading failure analysis. The results showed that the industries subject to carbon border tariffs played an essential role in China's entire industrial structure, which is closely related to industries including construction, metal, and manufacturing. If the carbon border tariffs are imposed on the steel industry, China's relevant industries will be reduced by 1.29%, followed by the fertilizer industry and non-ferrous metal industry with proportions of 1.11% and 0.95%, respectively. When the industrial transmission threshold reaches 0.8, the export shocks will affect the entire industrial network, leading to a rapid growth in the number of infected industries. By depicting the industrial linkage and impact mechanism of carbon border tariffs, this study is expected to provide practical suggestions and implications for carbon-intensive industries towards sustainable low-carbon transition under carbon border tariffs.

TPN10475 alleviates concanavalin A-induced autoimmune hepatitis by limiting T cell development and function through inhibition of PI3K-AKT pathway.

Autoimmune hepatitis (AIH) is an inflammatory liver disease in which the autoimmune system instigates an attack on the liver, causing inflammation and liver injury, and its incidence has increased worldwide in recent years. The mouse model of acute hepatitis established by concanavalin A (Con A) is a typical and recognized mouse model for the study of T-cell-dependent liver injury. In this study, we aimed to investigate whether the artemisinin derivative TPN10475 could alleviate AIH and its possible mechanisms. TPN10475 effectively inhibited lymphocyte proliferation and IFN-γ+ T cells production in vitro, alleviated liver injury by decreasing infiltrating inflammatory T cells producing IFN-γ in the liver and peripheral immune tissues, and demonstrated that TPN10475 weakened the activation and function of T cells by inhibiting PI3K-AKT signaling pathway. These results suggested that TPN10475 may be a potential drug for the treatment of AIH, and the inhibition of PI3K-AKT signaling pathway may provide new ideas for the study of the pathogenesis of AIH.

The novel small molecule TPN10518 alleviates EAE pathogenesis by inhibiting AP1 to depress Th1/Th17 cell differentiation.

Multiple sclerosis (MS) is one of the most common autoimmune diseases of central nervous system (CNS) demyelination. Experimental autoimmune encephalomyelitis (EAE) is the most classic animal model for simulating the onset of clinical symptoms in MS. Previous research has reported the anti-inflammatory effects of artemisinin on autoimmune diseases. In our study, we identified a novel small molecule, TPN10518, an artemisinin derivative, which plays a protective role on the EAE model. We found that TPN10518 reduced CNS inflammatory cell infiltration and alleviated clinical symptoms of EAE. In addition, TPN10518 downregulated the production of Th1 and Th17 cells in vivo and in vitro, and decrease the levels of related chemokines. RNA-seq assay combined with the experimental results demonstrated that TPN10518 lowered the mRNA and protein levels of the AP1 subunits c-Fos and c-Jun in EAE mice. It was further confirmed that TPN10518 was dependent on AP1 to inhibit the differentiation of Th1 and Th17 cells. The results suggest that TPN10518 reduces the production of Th1 and Th17 cells through inhibition of AP1 to alleviate the severity of EAE disease. It is expected to be a potential drug for the treatment of MS.

Copper Phthalocyanine Improving Nonaqueous Catalysis of Pseudomonas cepacia Lipase for Ester Synthesis.

The nonaqueous catalysis of lipases is significant for synthesis of high pure esters, but they usually behave low catalytic activity due to denaturation and aggregation of enzyme protein in organic phases. To improve the nonaqueous catalysis, the inexpensive copper phthalocyanine was taken as a new carrier on which Pseudomonas cepacia lipase was immobilized by physical absorption, and used for synthesis of hexyl acetate, an important flavor, via transesterification of hexanol and vinyl acetate. Results showed that the desired loading was 10-mg lipase immobilized on 10-mg copper phthalocyanine powder. When the immobilized lipase was employed in the reaction system consisted of 1.5-mL hexanol and 1.5-mL vinyl acetate at 37°C and 160 rpm, the conversion was fivefolds of that catalyzed by native lipase after 1 h, and reached 99.0% after 8 h. In six times of 8-h reuses, the immobilized lipase behaved an activity attenuation rate 1.22% h-1, lower than 1.77% h-1 of native lipase, which meant that the immobilized lipase was more stable. Even at the room temperature and the static state without shaking or stirring, the immobilized lipase still brought conversion 42.8% after 10 h and the native lipase gave 20.1%. Obviously, the immobilized lipase is an available biocatalyst in organic phase and has great potential in food industry.

Carboplatin ameliorates the pathogenesis of experimental autoimmune encephalomyelitis by inducing T cell apoptosis.

Apoptosis is a natural physiological process that can maintain the homeostasis of the body and immune system. This process plays an important role in the system's resistance to autoimmune development. Because of the dysfunction of cell apoptosis mechanism, the number of autoreactive cells in the peripheral tissue increases along with their accumulation. This will lead to the development of autoimmune diseases, such as multiple sclerosis (MS). MS is an immune-mediated disease of the central nervous system characterized by severe white matter demyelination. Because of the complexity of its pathogenesis, there is no drug to cure it completely. Experimental autoimmune encephalomyelitis (EAE) is an ideal animal model for the study of MS. Carboplatin (CA) is a second-generation platinum anti-tumor drug. In this study, we attempted to assess whether CA could be used to ameliorate EAE. CA reduced spinal cord inflammation, demyelination, and disease scores in mice with EAE. Moreover, the number and proportion of pathogenic T cells especially Th1 and Th17 in the spleen and draining lymph nodes were reduced in CA-treated EAE mice. Proteomic differential enrichment analysis showed that the proteins related to apoptosis signal changed significantly after CA treatment. CFSE experiment showed that CA significantly inhibited the T cell proliferation. Finally, CA also induced apoptosis in activated T cells and MOG-specific T cells in vitro. Overall, our findings indicated that CA plays a protective role in the initiation and progression of EAE and has the potential to be a novel drug in the treatment of MS.

Optical amplification-free deep reservoir computing-assisted high-baudrate short-reach communication.

An optical amplification-free deep reservoir computing (RC)-assisted high-baudrate intensity modulation direct detection (IM/DD) system is experimentally demonstrated using a 100G externally modulated laser operated in C-band. We transmit 112 Gbaud 4-level pulse amplitude modulation (PAM4) and 100 Gbaud 6-level PAM (PAM6) signals over a 200-m single-mode fiber (SMF) link without any optical amplification. The decision feedback equalizer (DFE), shallow RC, and deep RC are adopted in the IM/DD system to mitigate impairment and improve transmission performance. Both PAM transmissions over a 200-m SMF with bit error rate (BER) performance below 6.25% overhead hard-decision forward error correction (HD-FEC) threshold are achieved. In addition, the BER of the PAM4 signal is below the KP4-FEC limit after 200-m SMF transmission enabled by the RC schemes. Thanks to the use of a multiple-layer structure, the number of weights in deep RC has been reduced by approximately 50% compared with the shallow RC, whereas the performance is comparable. We believe that the optical amplification-free deep RC-assisted high-baudrate link has a promising application in intra-data center communications.

Unveiling characteristics and determinants of China's wind power geographies towards low-carbon transition.

The temporal and spatial patterns of wind power installation and the evaluation of carbon emission reduction potentials are of great significance to promoting China's wind power development planning and dual carbon targets achievement. This study analyzes the temporal and spatial characteristics, identifies main driving factors, and measures carbon emission reduction potentials of China's wind power installation by province based on spatial autocorrelation analysis and spatial econometric model. Overall, China's wind power installed capacity increased rapidly from 346 MW in 2000 to 279,550 MW in 2020, basically showing a significant positive spatial correlation during 2000 and 2020. Regarding driving factors of wind power installation, the technological factors and environmental factors were the main positive factors for wind power installation, and the economic factors and resource endowments showed positive spatial spillover effects. Regarding carbon emission reduction potentials, the carbon emission reduction potentials of China's wind power installation increased by year, among which Northwest China gradually accelerated Northeast China after 2015. Based on China's wind power evolution characteristics and carbon emission reduction potentials, this study attempts to provide quantitative supports and policy implications to promote sustainable development of wind power industry and the achievement of carbon peak and carbon neutrality within China.

TPN10466 ameliorates Concanavalin A-induced autoimmune hepatitis in mice via inhibiting ERK/JNK/p38 signaling pathway.

Autoimmune hepatitis (AIH) eventually progresses to liver fibrosis, cirrhosis, and even hepatocellular carcinoma, causing irreversible damage to the liver. Concanavalin A-induced hepatitis in mice is a well-established model with pathophysiology similar to that of immune-mediated liver injury in human viral and autoimmune hepatitis, and it has been widely used to explore the pathogenesis and clinical treatment of human immune hepatitis. Artemisinin has been shown to exhibit anti-inflammatory effects through unclear mechanisms. In this study, we aimed to assess the effect of the artemisinin derivative TPN10466 on AIH. In vitro studies showed that TPN10466 dose dependently inhibited the percentage of IFN-γ-producing T cells. Further studies showed that TPN10466 attenuated the disease severity of AIH by downregulating the ability of lymphocytes to secrete IFN-γ and by reducing lymphocyte number in the liver. In addition, we found that TPN10466 treatment reduced T-cell responses by inhibiting JNK, ERK, and p38 pathways. In conclusion, our work suggests that TPN10466 provides protection against the autoimmune disease AIH by suppressing the inflammatory response of T cells, suggesting that TPN10466 may be a promising potential agent for the treatment of AIH.

Identifying greenhouse gas emission reduction potentials through large-scale photovoltaic-driven seawater desalination.

To widely promote freshwater production through seawater desalination, renewable energy is expected to replace traditional fossil energy to drive seawater desalination. Based on the input list of components and materials, this study attempts to quantify greenhouse gas (GHG) emissions of photovoltaic-driven seawater desalination projects through replacing traditional thermal power plants and evaluate GHG emission reduction potentials by comparing the thermal- and photovoltaic-driven seawater desalination projects. The GHG emission of photovoltaic-driven seawater desalination project could be reduced by 94.97 % compared with the thermal-driven seawater desalination project, and the GHG emission per unit water production is reduced by 9.8 kg CO2-eq/ton, which could greatly reduce GHG emissions in the whole life cycle. In addition, it is estimated that the large-scale implementation of photovoltaic power stations in LT-MED seawater desalination project can reduce GHG emissions from 1.61E+05 to 3.86E+06 t CO2-eq per year. Through the payback period assessment, the combination of photovoltaic power stations and thermal power plants to drive the seawater desalination project can offset the GHG emission of 7.94E+03 t CO2-eq, and the payback period of photovoltaic-driven seawater desalination project is estimated to be 0.33 years. Using renewable energy instead of traditional thermal energy can reduce the fossil fuel combustion and GHG emissions during the water desalination process, which provides essential references for the low-carbon transition and energy saving in seawater desalination projects in China's coastal areas.

Simultaneous modulation format identification and OSNR monitoring based on optoelectronic reservoir computing.

An approach for simultaneous modulation format identification (MFI) and optical signal-to-noise ratio (OSNR) monitoring in digital coherent optical communications is proposed based on optoelectronic reservoir computing (RC) and the signal's amplitude histograms (AHs) obtained after the adaptive post-equalization. The optoelectronic RC is implemented using a Mach-Zehnder modulator and optoelectronic delay feedback loop. We investigate the performance of the proposed model with the number of symbols, bins of AHs and the hyperparameters of optoelectronic RC. The results show that 100% MFI accuracy can be achieved simultaneously with accurate OSNR estimation for different modulation formats under study. The lowest achievable OSNR estimation mean absolute errors for the dual-polarization (DP)-quadrature phase-shift keying signal, the DP-16-ary quadrature amplitude modulation (16QAM) signal, and the DP-64QAM signal are 0.2 dB, 0.32 dB and 0.53 dB, respectively. The robustness of the proposed scheme is also evaluated when the optoelectronic RC is in presence of additive white Gaussian noises. Then, a proof of concept experiment is demonstrated to further verify our proposed method. The proposed approach offers a potential solution for next-generation intelligent optical performance monitoring in the physical layer.