Country-specific net-zero strategies of the pulp and paper industry.

The pulp and paper industry is an important contributor to global greenhouse gas emissions1,2. Country-specific strategies are essential for the industry to achieve net-zero emissions by 2050, given its vast heterogeneities across countries3,4. Here we develop a comprehensive bottom-up assessment of net greenhouse gas emissions of the domestic paper-related sectors for 30 major countries from 1961 to 2019-about 3.2% of global anthropogenic greenhouse gas emissions from the same period5-and explore mitigation strategies through 2,160 scenarios covering key factors. Our results show substantial differences across countries in terms of historical emissions evolution trends and structure. All countries can achieve net-zero emissions for their pulp and paper industry by 2050, with a single measure for most developed countries and several measures for most developing countries. Except for energy-efficiency improvement and energy-system decarbonization, tropical developing countries with abundant forest resources should give priority to sustainable forest management, whereas other developing countries should pay more attention to enhancing methane capture rate and reducing recycling. These insights are crucial for developing net-zero strategies tailored to each country and achieving net-zero emissions by 2050 for the pulp and paper industry.

Novel anthropometric indicators of visceral obesity predict the severity of hyperlipidemic acute pancreatitis.

BACKGROUND: Obesity substantially contributes to the onset of acute pancreatitis (AP) and influences its progression to severe AP. Although body mass index (BMI) is a widely used anthropometric parameter, it fails to delineate the distribution pattern of adipose tissue. To circumvent this shortcoming, the predictive efficacies of novel anthropometric indicators of visceral obesity, such as lipid accumulation products (LAP), cardiometabolic index (CMI), body roundness index (BRI), visceral adiposity index (VAI), A Body Shape Index (ABSI), and Chinese visceral adiposity index (CVAI) were examined to assess the severity of AP. METHOD: The body parameters and laboratory indices of 283 patients with hyperlipidemic acute pancreatitis (HLAP) were retrospectively analysed, and the six novel anthropometric indicators of visceral obesity were calculated. The severity of HLAP was determined using the revised Atlanta classification. The correlation between the six indicators and HLAP severity was evaluated, and the predictive efficacy of the indicators was assessed using area under the curve (AUC). The differences in diagnostic values of the six indicators were also compared using the DeLong test. RESULTS: Patients with moderate to severe AP had higher VAI, CMI, and LAP than patients with mild AP (all P < 0.001). The highest AUC in predicting HLAP severity was observed for VAI, with a value of 0.733 and 95% confidence interval of 0.678-0.784. CONCLUSIONS: This study demonstrated significant correlations between HLAP severity and VAI, CMI, and LAP indicators. These indicators, particularly VAI, which displayed the highest predictive power, were instrumental in forecasting and evaluating the severity of HLAP.

Worm Generator: A System for High-Throughput in Vivo Screening.

Large-scale screening of molecules in organisms requires high-throughput and cost-effective evaluating tools during preclinical development. Here, a novel in vivo screening strategy combining hierarchically structured biohybrid triboelectric nanogenerators (HB-TENGs) arrays with computational bioinformatics analysis for high-throughput pharmacological evaluation using Caenorhabditis elegans is described. Unlike the traditional methods for behavioral monitoring of the animals, which are laborious and costly, HB-TENGs with micropillars are designed to efficiently convert animals' behaviors into friction deformation and result in a contact-separation motion between two triboelectric layers to generate electrical outputs. The triboelectric signals are recorded and extracted to various bioinformation for each screened compound. Moreover, the information-rich electrical readouts are successfully demonstrated to be sufficient to predict a drug's identity by multiple-Gaussian-kernels-based machine learning methods. This proposed strategy can be readily applied to various fields and is especially useful in in vivo explorations to accelerate the identification of novel therapeutics.

Rethinking industrial land-use in American rust cities towards sustainability based on a block-level model.

Urban land is a fundamental but scarce resource that carries intensive human socio-economic activities. The demographic decline and housing vacancy issues that emerged with de-industrialization have raised concerns regarding the sustainable utilization of urban land resources, particularly in the American Rust Belt region. In this context, a comprehensive analysis of industrial land use can offer valuable insights to support the sustainable planning of shrinking cities. However, existing urban land research exhibits insufficient resolution at the sectoral scale and impedes the evaluation of industrial land use efficiency within the urban context. To address this gap, we established an integrated land use estimation framework for economic sectors based on multi-source data, which enables the assessment of land use efficiency at a finer sectoral scale. The method was then applied to the city of Detroit, Cleveland, and Pittsburgh. The results demonstrate that the current industrial land mix in the three cities is dominated by service-providing industries, but the land usage by goods-producing sectors in these cities presents a relatively high level of efficiency. The Moran's I value indicates a clustered tendency for the main economic sectors. The land use area results reveal that Other Services occupies the most land area in Detroit (2.29 million m2) and Cleveland (2.04 million m2). While in Pittsburgh, Professional Scientific and Technical Services (1.44 million m2) is the largest. In terms of the economic output, Management of Companies and Enterprises is the most efficient sector in Detroit (20.28 thousand $/m2) and Cleveland (29.43 thousand $/m2), while Pittsburgh's Public Administration (11.73 thousand $/m2) is the most efficient. As many other cities in the world are about to enter the era of de-industrialization or low growth, the outcomes can also serve as a reference to guide their sustainable revitalization in line with the SDGs.

Machine learning for predicting the risk stratification of 1-5 cm gastric gastrointestinal stromal tumors based on CT.

BACKGROUD: To predict the malignancy of 1-5 cm gastric gastrointestinal stromal tumors (GISTs) by machine learning (ML) on CT images using three models - Logistic Regression (LR), Decision Tree (DT) and Gradient Boosting Decision Tree (GBDT). METHODS: 231 patients from Center 1 were randomly assigned into the training cohort (n = 161) and the internal validation cohort (n = 70) in a 7:3 ratio. The other 78 patients from Center 2 served as the external test cohort. Scikit-learn software was used to build three classifiers. The performance of the three models were evaluated by sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV) and area under the curve (AUC). Diagnostic differences between ML models and radiologists were compared in the external test cohort. Important features of LR and GBDT were analyzed and compared. RESULTS: GBDT outperformed LR and DT with the largest AUC values (0.981 and 0.815) in the training and internal validation cohorts and the greatest accuracy (0.923, 0.833 and 0.844) across all three cohorts. However, LR was found to have the largest AUC value (0.910) in the external test cohort. DT yielded the worst accuracy (0.790 and 0.727) and AUC values (0.803 and 0.700) in both the internal validation cohort and the external test cohort. GBDT and LR performed better than radiologists. Long diameter was demonstrated to be the same and most important CT feature for GBDT and LR. CONCLUSIONS: ML classifiers, especially GBDT and LR with high accuracy and strong robustness, were considered to be promising in risk classification of 1-5 cm gastric GISTs based on CT. Long diameter was found the most important feature for risk stratification.

Coupled impacts of climate and land use changes on regional ecosystem services.

Ecosystem services (ES) are key to maintaining sustainable regional development. Climate change and land cover and land use change (LULC) are one of the main factors leading to changes in regional ecosystem services. Existing studies have simulated regional ES changes under different future scenarios, providing valuable guidance for regional sustainable management. However, most studies focus on the effects of individual factors (LULC or climate change) on ES, paying insufficient attention to the coupled effects of the two elements. Yunnan Province is a biodiversity hotspot facing challenges in ES in the context of future climate change and rapid socio-economic development. In order to achieve sustainable management, policies must be developed in advance to address possible future ecological risks. In this study, we simulated the coupled effects of climate change and LULC on six types of ES using the SD, FLUS, and InVEST models. The scenario framework of shared socioeconomic pathways SSP245 and SSP585 was combined with LULC scenario dynamics to assess the changes of ES in 2030 and 2050, identifying sensitive areas and providing a scientific basis for local ecosystem management. In 2020, the eastern part of Yunnan Province was the coldspot area for all ES. Under the future scenarios, Yunnan Province's ES show different loss rates and distinct spatial heterogeneity. Future climate change and LULC changes have a more significant negative impact on water conservation and water quality purification. About 66% of its counties will become sensitive areas for water production services, and 37% of counties will endure reduced water purification functions by more than 50%. According to the analytical results, we then proposed several suggestions to improve regional ES management.

Fabrication of Nb2 O5 /Carbon Submicrostructures for Advanced Lithium-Ion Battery Anodes.

Nb2 O5 possesses superior fast Li+ storage capability for LIB anodes, benefiting from its fast pseudocapacitive behavior and low volumetric change within the cycling processes. However, the poor electric conductivity for Nb2 O5 restricts its reaction kinetics and rate property. Herein, Nb2 O5 /carbon (C) submicrostructures are fabricated by solvothermal method followed by calcination process. The Nb2 O5 /C submicrostructures exhibit outstanding rate behavior and cyclic performance (332 (194) mAh g-1 after 1000 cycles at 1 (5) A g-1 ). The superior electrochemical property is attributed to the distinctive structure for Nb2 O5 /C submicrostructures, in which Nb2 O5 nanoparticles uniformly distributed within Nb2 O5 /C composite can protect Nb2 O5 nanoparticles from agglomeration, and the porous carbon matrix can enhance electron/ion conductivity. This work furnishes a novel strategy for fabricating Nb2 O5 /C submicrostructures with superior Li+ storage performance, which can be potentially used to design other metal oxide/C submicrostructures for second battery anode.

Exports Widen the Regional Inequality of Health Burdens and Economic Benefits in India.

Both the ever-complex international and subnational supply chains could relocate health burdens and economic benefits across India, leading to the widening of regional inequality. Here, we simultaneously track the unequal distribution of fine particle matter (PM2.5) pollution, health costs, and value-added embodied in inter- and intranational exports for Indian states in 2015 by integrating a nested multiregional input-output (MRIO) table constructed based on EXIOBASE and an Indian regional MRIO table, Emissions Database for Global Atmospheric Research (EDGAR), the Community Multi-Scale Air Quality (CMAQ) model, and a concentration-response function. The results showed that the annual premature deaths associated with PM2.5 pollution embodied in inter- and intranational exports were 757,356 and 388,003 throughout India, accounting for 39% and 20% of the total premature deaths caused by PM2.5 pollution, respectively. Richer south and west coastal states received around half of the national Gross Domestic Product (GDP) induced by exports with a quarter of the health burden, while poorer central and east states bear approximately 60% of the health burden with less than a quarter of national GDP. Our findings highlight the role of exports in driving the regional inequality of health burdens and economic benefits. Therefore, tailored strategies (e.g., air pollution compensation, advanced technology transfer, and export structure optimization) could be formulated.

The association of parameters of body composition and laboratory markers with the severity of hypertriglyceridemia-induced pancreatitis.

BACKGROUND: Hypertriglyceridemia has arisen as the third leading cause of acute pancreatitis. This study aimed at exploring the association between the severity of hypertriglyceridemia-induced pancreatitis (HTGP) and computed tomography (CT)-based body composition parameters and laboratory markers. METHODS: Laboratory and clinical parameters were collected from 242 patients with HTGP between 2017 and 2020. Severity of HTGP was evaluated by original or modified CT severity index. Body composition parameters such as area and radiodensity of muscle, subcutaneous adipose tissue and visceral adipose tissue were calculated by CT at the level of third lumbar vertebra. Parameters were compared between mild and moderately severe to severe HTGP. Uni-variate and multi-variate Logistic regression analyses were employed to assess the risk factors of the severity of HTGP. RESULTS: Seventy patients (28.9%) presented with mild HTGP. Body mass index, waist circumference and all CT-based body composition parameters differed between male and female patients. None was associated with the severity of HTGP, neither in males nor in females. Receiver operating characteristic curves showed that areas under the curves of apolipoprotein A-I and albumin to predict the severity of HTGP were 0.786 and 0.759, respectively (all P < 0.001). Uni-variate and further multi-variate Logistic regression analysis confirmed that low serum albumin (< 35 g/L, P = 0.004, OR = 3.362, 95%CI = 1.492-8.823) and apolipoprotein A-I (< 1.1 g/L, P < 0.001, OR = 5.126, 95%CI = 2.348-11.195), as well as high C-reactive protein (> 90 mg/L, P = 0.005, OR = 3.061, 95%CI = 1.407-6.659) and lipase (P = 0.033, OR = 2.283, 95%CI = 1.070-4.873) were risk factors of moderately severe to severe HTGP. Levels of albumin, apolipoprotein A-I, C-reactive protein and lipase were also associated with the length of hospital stay (all P < 0.05). Besides, low serum albumin, low-density lipoprotein cholesterol and high radiodensity of subcutaneous adipose tissue were significant risk factors of pancreatic necrosis in patients with HTGP (all P < 0.05). CONCLUSIONS: Low serum albumin and apolipoprotein A-I, and high C-reactive protein and lipase upon admission were associated with a more severe type of HTGP and longer hospital stay for these patients. Albumin and apolipoprotein A-I may serve as novel biomarkers for the severity of HTGP. However, none of the body composition parameters was associated with the severity of HTGP.

Sustainability evaluation based on the Three-dimensional Ecological Footprint and Human Development Index: A case study on the four island regions in China.

Sustainable development emphasizes the sustainability of natural resources and the environment as well as the development of social welfare. Under the background of resource scarcity and environmental constraints, maximizing social welfare is an inevitable choice to achieve sustainable development. Ecological Wellbeing Performance (EWP) can comprehensively reflect the efficiency of natural capital conversion into social welfare, and improving EWP is a feasible measure to achieve sustainable development. Moreover, island areas are the extremely complicated ecological-social-economic systems due to the traits that are geographical isolation, scarce resources, and frequent natural disasters, so that emphasizing the sustainability of island systems is a key step for achieving sustainable development goals. This study developed the EWP model based on the improved Three-dimensional Ecological Footprint (EF) and urban-scale Human Development Index (HDI), to synthetically evaluate and analyze the sustainable development of four major island regions in China with the data in 2017. Results found that: (1) The four regions are all in ecological deficits, being in exchange for overdraft natural capital for economic development. The EFdepth is greater than the original length 1 indicating the excessive consumption of the natural capital stock. The EFsize reflects the abundance and liquidity of regional natural capital, all the four regions are with the generally low level of flow capital utilization. Hainan with highest EFsize 0.428 is due to its comparatively sparse population density, abundant resources, and strong ecological capacity, while the relatively large population density and more restricted natural capital flows make Taiwan in the lowest value. (2) Judging from the evaluation results of the HDI, Chongming (0.796) and Hainan (0.773) high development level are relatively behind Taiwan (0.912) and Zhoushan (0.827) very high development level, for the impact of income is greater, that is, economic development in Hainan and Chongming is slightly weak. (3) Taiwan, with the highest EWP 3.646, shows the excellent natural resource utilization efficiency and sustainability, followed by Zhoushan, Chongming, and Hainan. In general, increasing HDI while reducing EF can be an ideal way to improve the efficiency of ecological resources and achieve sustainable urban development.

Synthesis, characterization, and photodynamic therapy activity of 5,10,15,20-Tetrakis(carboxyl)porphyrin.

Water-soluble porphyrins are considered promising drug candidates for photodynamic therapy (PDT). This study investigated the PDT activity of a new water-soluble, anionic porphyrin (1-Zn), which possesses four negative charges. The photodynamic anticancer activity of 1-Zn was investigated by the MTT assay, with mTHPC as a positive control. The cellular distribution was determined by fluorescence microscopy. Holographic and phase contrast images were recorded after 1-Zn treatment with a HoloMonitor™ M3 instrument. The inhibition of A549 cell growth achieved by inducing apoptosis was investigated by flow cytometry and fluorescence microscopy. DNA damage was investigated by the comet assay. The expression of apoptosis-related proteins was also measured by western blot assays. 1-Zn had better phototoxicity against A549 cells than HeLa and HepG2 cancer cells. Interestingly, 1-Zn was clearly located almost entirely in the cell cytoplasmic region/organelles. The late apoptotic population was less than 1.0% at baseline in the untreated and only light-treated cells and increased to 40.5% after 1-Zn treatment and irradiation (P < 0.05). 1-Zn triggered significant ROS generation after irradiation, causing ΔΨm disruption (P < 0.01) and DNA damage. 1-Zn induced A549 cell apoptosis via the mitochondrial apoptosis pathway. In addition, 1-Zn bound in the groove of DNA via an outside binding mode by pi-pi stacking and hydrogen bonding. 1-Zn exhibits good photonuclease activity and might serve as a potential photosensitizer (PS) for lung cancer cells.

miR-190 promotes HCC proliferation and metastasis by targeting PHLPP1.

miRNAs regulate gene expression and enable clinicians to distinguish between benign and malignant tissues in cancers. PH domain leucine-rich repeat-containing protein phosphatase 1 (PHLPP1) is known to be a tumour suppressor. A lentiviral overexpression system was used to stably express miR-190, leading to the enhancement of hepatocellular carcinoma (HCC) proliferation and metastasis as a result of inhibited PHLPP1 expression. The results showed that stable miR-190 expression increased the expression of EMT-related proteins (Snail and TCF8/ZEB1) as well as the phosphorylation of Akt at Ser473 and the expression of a disintegrin and metalloproteinase with thrombospondin motifs 1 (ADAMTS1). However, restoring PHLPP1 expression counteracted the effects of miR-190 on HCC proliferation, migration and invasion. The results of the animal experiments showed that miR-190 improved the HepG2 cell tumour formation and lung metastasis ability. Stable miR-190 overexpression leads to the downregulation of PHLPP1 protein expression. miR-190 has potential as a target in the treatment and diagnosis of HCC.

The photocytotoxicity effect of cationic sulfonated corrole towards lung cancer cells: in vitro and in vivo study.

Corrole is a kind of new and promising photosensitizer (PS) in cancer photodynamic therapy (PDT). However, the protein molecular mechanism of PDT activity for corrole under light irradiation is still not clear. In this paper, water-soluble cationic sulfonated corrole (1) and its metal complexes (1-Fe, 1-Mn, and 1-Cu) were prepared, and the photodynamic anti-cancer activity against various tumor cells was investigated by MTT assay. The potential molecular mechanism of PDT activity was elucidated by fluorescence microscope, flow cytometry, molecular docking, and western blotting analysis. Besides, the potential PDT anti-tumor effect of 1 in vivo was assessed in human tumor xenografts in mice. Quantitative analysis revealed that 1's phototoxicity triggered a significant generation of reactive oxygen species, causing disruption of mitochondrial membrane potential. The results of western blotting (WB) assay shown in 1's phototoxicity could induce cell apoptosis via ROS-mediated mitochondrial caspase apoptosis pathway, in which SIRT1 protein degradation played a key role. PTD activity in vivo shown in 1 could significantly reduce the growth of A549 xenografted tumor, without obvious loss of mice body weight. We clearly found that cationic sulfonated corrole is a potential candidate of PS in vitro and in vivo. The phototoxicity of 1 could induce A549 cell apoptosis by inducing ROS production increase, further to activate the mitochondrial apoptosis pathway. We concluded that SIRT1 protein is a more appropriate target in this progress.

Dermokine contributes to epithelial-mesenchymal transition through increased activation of signal transducer and activator of transcription 3 in pancreatic cancer.

Dermokine (DMKN) was first identified in relation to skin lesion healing and skin carcinoma. Recently, its expression was associated with pancreatic cancer tumorigenesis, although its involvement remains poorly understood. Herein, we showed that DMKN loss of function in Patu-8988 and PANC-1 pancreatic cancer cell lines resulted in reduced phosphorylation of signal transducer and activator of transcription 3, and increased activation of ERK1/2 and AKT serine/threonine kinase. This decreased the proliferation ability of pancreatic ductal adenocarcinoma (PDAC) cells. In addition, DMKN knockdown decreased the invasion and migration of PDAC cells, partially reversed the epithelial-mesenchymal transition, retarded tumor growth in a xenograft animal model by decreasing the density of microvessels, and attenuated the distant metastasis of human PDAC in a mouse model. Taken together, these data suggested that DMKN could be a potential prognostic biomarker and therapeutic target in pancreatic cancer.

Increased Active Tumor Targeting by An αvß3-Targeting and Cell-Penetrating Bifunctional Peptide-Mediated Dendrimer-Based Conjugate.

PURPOSE: A bifunctional RGDTAT peptide-modified PEG-PAMAM dendrimer conjugate RGDTAT-PEG-PAMAM (RTPP) was established for the targeted treatment of αvß3-overexpressing tumor cells. METHODS: The RGDTAT peptide was synthesized and attached to PAMAM using PEG to construct the RTPP conjugate. The methotrexate (MTX) encapsulated RTPPM complex was prepared and characterized by dynamic light scattering (DLS), transmission electron microscopy (TEM) and in vitro release. The targeting ability was then studied in cells and tumor-bearing nude mice using fluorescence microscopy, confocal fluorescence microscopy, flow cytometry, and in vivo imaging. The cytotoxicity and pharmacokinetics of the RTPPM complex was also evaluated in cells and rats. RESULTS: The successful synthesis of the RTPP conjugate was confirmed by 1H-NMR. DLS and TEM measurements revealed that the size was 37 nm and the complex had a spherical shape. RTPP and RTPPM were taken up by αvß3-overexpressing cells more efficiently than by αvß3-lowexpressing cells. The RTPP conjugate localized to the cell nucleus and accumulated in the tumor more efficiently than did the conjugates without RGDTAT. The pharmacokinetic study of the RTPPM complex showed sustained drug release. CONCLUSIONS: The bifunctional peptide-mediated dendrimer-based RTPP conjugate can serve as a promising nanocarrier for targeted drug delivery to improve anti-tumor activity.

Application of Recombinant Collagen Type â Combined with Polyaspartic Acid in Biomimetic Biomineralization.

Objective To prepare biomimetic bone material by reconstructing type Ⅰ collagen combined with polyaspartic acid. Methods By acid hydrolysis,rat tail type Ⅰ collagen was decomposed into collagen fibers,which were then placed in the calcium phosphate mineralization solution. Under the cross-linking of glutaraldehyde,the collagen fibers were reconstructed and assembled into collagen fibers,and the calcium phosphate crystals were wrapped in the inner side of the collagen fibers for biomineralizationin. After poly aspartate acid was added,calcium hydroxyapatite calcium precursor was added into the collagen fibers to simulate thebiomimetic biomineralizationin the human body. After mineralization for 3-9 days,the bone mineralization process was observed by transmission electron microscopy and electron diffraction. Results Transmission electron microscopy and electron diffraction displayed that,after 3 days of mineralization,calcium hydroxyapatite precursor was wrapped in the collagen fiber gap,and the collagen fiber was partially mineralized. After 9 days of mineralization,calcium hydroxyapatite precursor completely infiltrated into the collagen fiber,and the amorphous calcium phosphate was transformed into hydroxyapatite calcium crystal. Thus,the simulation of bone mineralization was completed,and collagen type Ⅰ collagen/hydroxyapatite calcium biomimetic bone material was formed. Conclusion Reconstruction of type Ⅰ collagen combined with polyaspartic acid can prepare biomimetic bone material that has close chemical composition and molecular structure to the human bone tissue.

Computed tomography-based body composition indicative of diabetes after hypertriglyceridemic acute pancreatitis.

BACKGROUND: Post­acute pancreatitis prediabetes/diabetes mellitus (PPDM­A) is one of the common sequelae of acute pancreatitis (AP). The aim of our study was to build a machine learning (ML)-based prediction model for PPDM-A in hypertriglyceridemic acute pancreatitis (HTGP). METHODS: We retrospectively enrolled 165 patients for our study. Demographic and laboratory data and body composition were collected. Multivariate logistic regression was applied to select features for ML. Support vector machine (SVM), linear discriminant analysis (LDA), and logistic regression (LR) were used to develop prediction models for PPDM-A. RESULTS: 65 patients were diagnosed with PPDM-A, and 100 patients were diagnosed with non-PPDM-A. Of the 84 body composition-related parameters, 15 were significant in discriminating between the PPDM-A and non-PPDM-A groups. Using clinical indicators and body composition parameters to develop ML models, we found that the SVM model presented the best predictive ability, obtaining the best AUC=0.796 in the training cohort, and the LDA and LR model showing an AUC of 0.783 and 0.745, respectively. CONCLUSIONS: The association between body composition and PPDM-A provides insight into the potential pathogenesis of PPDM-A. Our model is feasible for reliably predicting PPDM-A in the early stages of AP and enables early intervention in patients with potential PPDM-A.

Lactate enhances NMNAT1 lactylation to sustain nuclear NAD+ salvage pathway and promote survival of pancreatic adenocarcinoma cells under glucose-deprived conditions.

The aim of this study was to investigate the underlying molecular mechanism behind the promotion of cell survival under conditions of glucose deprivation by l-lactate. To accomplish this, we performed tissue microarray and immunohistochemistry staining to analyze the correlation between the abundance of pan-Lysine lactylation and prognosis. In vivo evaluations of tumor growth were conducted using the KPC and nude mice xenograft tumor model. For mechanistic studies, multi-omics analysis, RNA interference, and site-directed mutagenesis techniques were utilized. Our findings robustly confirmed that l-lactate promotes cell survival under glucose deprivation conditions, primarily by relying on GLS1-mediated glutaminolysis to support mitochondrial respiration. Mechanistically, we discovered that l-lactate enhances the NMNAT1-mediated NAD+ salvage pathway while concurrently inactivating p-38 MAPK signaling and suppressing DDIT3 transcription. Notably, Pan-Kla abundance was significantly upregulated in patients with Pancreatic adenocarcinoma (PAAD) and associated with poor prognosis. We identified the 128th Lysine residue of NMNAT1 as a critical site for lactylation and revealed EP300 as a key lactyltransferase responsible for catalyzing lactylation. Importantly, we elucidated that lactylation of NMNAT1 enhances its nuclear localization and maintains enzymatic activity, thereby supporting the nuclear NAD+ salvage pathway and facilitating cancer growth. Finally, we demonstrated that the NMNAT1-dependent NAD+ salvage pathway promotes cell survival under glucose deprivation conditions and is reliant on the activity of Sirt1. Collectively, our study has unraveled a novel molecular mechanism by which l-lactate promotes cell survival under glucose deprivation conditions, presenting a promising strategy for targeting lactate and NAD+ metabolism in the treatment of PAAD.

Assessing life-cycle GHG emissions of recycled paper products under imported solid waste ban in China: A case study.

Changes of raw materials in China's recycled paper industry after the imported solid waste ban affect products' life-cycle greenhouse gas (GHG) emissions as well. This paper presented a case study of newsprint production with prior- and post-ban scenarios with life cycle assessment, including using imported waste paper (P0) and its three substitutions, i.e., virgin pulp (P1), domestic waste paper (P2), and imported recycled pulp (P3). The function unit is 1 ton of newsprint produced in China, and the study is conducted from cradle to grave which consists pulping and papermaking process, from raw material acquisition to manufacturing, with associated energy production and wastewater treatment, transport, and chemicals production. Our results showed that P1 holds the highest life-cycle GHG emission of 2724.91, followed by 2400.88 from P3. P2 has the lowest emission of 1619.27, only slightly lower than 1742.39 before the ban using route P0 (unit: kgCO2e/ton paper). Scenario analysis showed that current average life-cycle GHG emission for one ton of newsprint is 2049.33 kgCO2e, increased by 17.62 % due to the ban, while this number could be reduced to 12.22 % or even -0.79 % if switching from P1 to P3 and P2. Our study highlighted the importance of domestic waste paper as a promising way to reduce GHG emissions, which still has great potential to increase if with an enhanced waste paper recycling system in China.