Highly sensitive SERS platform for pathogen analysis by cyclic DNA nanostructure@AuNP tags and cascade primer exchange reaction.

The capacity to identify small amounts of pathogens in real samples is extremely useful. Herein, we proposed a sensitive platform for detecting pathogens using cyclic DNA nanostructure@AuNP tags (CDNA) and a cascade primer exchange reaction (cPER). This platform employs wheat germ agglutinin-modified Fe3O4@Au magnetic nanoparticles (WMRs) to bind the E. coli O157:H7, and then triggers the cPER to generate branched DNA products for CDNA tag hybridization with high stability and amplified SERS signals. It can identify target pathogens as low as 1.91 CFU/mL and discriminate E. coli O157:H7 in complex samples such as water, milk, and serum, demonstrating comparable or greater sensitivity and accuracy than traditional qPCR. Moreover, the developed platform can detect low levels of E. coli O157:H7 in mouse serum, allowing the discrimination of mice with early-stage infection. Thus, this platform holds promise for food analysis and early infection diagnosis.

Transport of per-/polyfluoroalkyl substances from leachate to groundwater as affected by dissolved organic matter in landfills.

The transport of per- and polyfluoroalkyl substances (PFAS) from landfill leachate to surrounding soil and groundwater poses a threat to human health via the food chain or drinking water. Studies have shown that the transport process of PFAS from the solid to liquid phase in the environment is significantly affected by dissolved organic matter (DOM) adsorption. However, the mechanism of PFAS release from landfill solids into leachate and its transport to the surrounding groundwater remains unclear. In this study, we identified the composition of PFAS and DOM components and analyzed the association between DOM components, physicochemical factors, and PFAS concentrations in landfill leachate and groundwater. This study demonstrated that the frequency of PFAS detection in the samples was 100%, and the PFAS concentrations in leachate were greater than in the groundwater samples. Physicochemical factors, such as ammonium-nitrogen (NH4+-N), sodium (Na), calcium (Ca), DOM components C4 (macromolecular humic acid), SUVA254 (aromatic component content), and A240-400 (humification degree and molecular weight), were strongly correlated with PFAS concentrations. In conclusion, PFAS environmental risk management should be enhanced in landfills, especially in closed landfills, or landfills that are scheduled to close in the near future.

Utility of metagenomic Next-Generation Sequencing for simultaneously detecting pathogens and neoplasms.

Objectives: Clinicians often face the challenge of differentially diagnosing febrile patients who are suspected of infectious diseases, since the clinical manifestations of infection and cancer may overlap. A single test that can detect both pathogens and tumor could provide timely and accurate diagnostic clues to aid the treatment and management of these patients. Methods: We enrolled eight patients to evaluate the utility of metagenomic Next-Generation Sequencing for simultaneously detecting pathogens and neoplasms using body fluids and tissue samples. Patients were selected by the following criteria: 1) Tumor was not considered upon hospitalization, but mNGS testing indicated neoplasm; 2) Tumor was not excluded, but microbial infection was primarily suspected according to initial clinical assessment. Results: We detected potential pathogens in five patients, three of whom had progressed into critical infections. Moreover, abnormal chromosomal copy numbers were identified in all patients that indicated presence of neoplasms, which were pathologically confirmed. Conclusions: Although copy number variations do not render a definitive cancer diagnosis, it can prompt clinicians to conduct more focused diagnostic testing for cancer, potentially saving time and cost. As a result, integrating copy number analysis with pathogen detection in mNGS may help establish rapid and accurate diagnosis for febrile patients.

RVFScan predicts virulence factor genes and hypervirulence of the clinical metagenome.

Bacterial infections often involve virulence factors that play a crucial role in the pathogenicity of bacteria. Accurate detection of virulence factor genes (VFGs) is essential for precise treatment and prognostic management of hypervirulent bacterial infections. However, there is a lack of rapid and accurate methods for VFG identification from the metagenomic data of clinical samples. Here, we developed a Reads-based Virulence Factors Scanner (RVFScan), an innovative user-friendly online tool that integrates a comprehensive VFG database with similarity matrix-based criteria for VFG prediction and annotation using metagenomic data without the need for assembly. RVFScan demonstrated superior performance compared to previous assembly-based and read-based VFG predictors, achieving a sensitivity of 97%, specificity of 98% and accuracy of 98%. We also conducted a large-scale analysis of 2425 clinical metagenomic datasets to investigate the utility of RVFScan, the species-specific VFG profiles and associations between VFGs and virulence phenotypes for 24 important pathogens were analyzed. By combining genomic comparisons and network analysis, we identified 53 VFGs with significantly higher abundances in hypervirulent Klebsiella pneumoniae (hvKp) than in classical K. pneumoniae. Furthermore, a cohort of 1256 samples suspected of K. pneumoniae infection demonstrated that RVFScan could identify hvKp with a sensitivity of 90%, specificity of 100% and accuracy of 98.73%, with 90% of hvKp samples consistent with clinical diagnosis (Cohen's kappa, 0.94). RVFScan has the potential to detect VFGs in low-biomass and high-complexity clinical samples using metagenomic reads without assembly. This capability facilitates the rapid identification and targeted treatment of hvKp infections and holds promise for application to other hypervirulent pathogens.

Novel Clinical mNGS-Based Machine Learning Model for Rapid Antimicrobial Susceptibility Testing of Acinetobacter baumannii.

Multidrug-resistant (MDR) bacteria are important public health problems. Antibiotic susceptibility testing (AST) currently uses time-consuming culture-based procedures, which cause treatment delays and increased mortality. We developed a machine learning model using Acinetobacter baumannii as an example to explore a fast AST approach using metagenomic next-generation sequencing (mNGS) data. The key genetic characteristics associated with antimicrobial resistance (AMR) were selected through a least absolute shrinkage and selection operator (LASSO) regression model based on 1,942 A. baumannii genomes. The mNGS-AST prediction model was accordingly established, validated, and optimized using read simulation sequences of clinical isolates. Clinical specimens were collected to evaluate the performance of the model retrospectively and prospectively. We identified 20, 31, 24, and 3 AMR signatures of A. baumannii for imipenem, ceftazidime, cefepime, and ciprofloxacin, respectively. Four mNGS-AST models had a positive predictive value (PPV) greater than 0.97 for 230 retrospective samples, with negative predictive values (NPVs) of 100% (imipenem), 86.67% (ceftazidime), 86.67% (cefepime), and 90.91% (ciprofloxacin). Our method classified antibacterial phenotypes with an accuracy of 97.65% for imipenem, 96.57% for ceftazidime, 97.64% for cefepime, and 98.36% for ciprofloxacin. The average reporting time of mNGS-based AST was 19.1 h, in contrast to the 63.3 h for culture-based AST, thus yielding a significant reduction of 44.3 h. mNGS-AST prediction results coincided 100% with the phenotypic AST results when testing 50 prospective samples. The mNGS-based model could be used as a rapid genotypic AST approach to identify A. baumannii and predict resistance and susceptibility to antibacterials and could be applicable to other pathogens and facilitate rational antimicrobial usage.

Spatial effects of environmental regulation on high-quality economic development: From the perspective of industrial upgrading.

Studying the spatiotemporal heterogeneity of environmental regulations on high-quality regional economic development is of enormous practical value in the context of sustainable economic, social, and environmental development. Only a few studies, however, examined the regional heterogeneity of environmental regulation affecting economic development from the standpoint of upgrading the industrial structure. This research investigated the spatial distribution traits of high-quality regional development based on the construction of a comprehensive assessment index system for high-quality economic development. The economic geography-nested spatial Durbin model is then used to perform an empirical test. The findings demonstrate that (1) high-quality economic development has visible spatial heterogeneity, with strong local spatial agglomeration between regions; (2) environmental regulation and the modernization of the industrial structure are significant variables influencing high-quality economic development, but their development is not balanced; and (3) environmental policies promote high-quality regional development through a distinct channel. Formal environmental regulation promotes economic development through rationalizing industrial structure, while informal environmental regulation does so through upgrading the industrial structure. Further, both kinds of environmental regulation have positive spatial spillover effects on adjacent areas. Therefore, the regional heterogeneity of environmental regulation and industrial structure is of great significance in promoting the high-quality and sustainable development of regional economies.

Human umbilical cord mesenchymal stem cell-derived TGFBI attenuates streptozotocin-induced type 1 diabetes mellitus by inhibiting T-cell proliferation.

MSCs have been demonstrated to have a great benefit for type 1 diabetes mellitus (T1DM) due to their strong immunosuppressive and regenerative capacity. However, the comprehensive mechanism is still unclear. Our previous study indicated that transforming growth factor beta induced (TGFBI) is highly expressed in human umbilical cord-derived mesenchymal stem or stromal cells (hUC-MSCs), which are also implicated in T1DM. In this study, we found that infusion of TGFBI knockdown hUC-MSCs displayed impaired therapeutic effects in T1DM mice and decreased immunosuppressive capability. TGFBI knockdown hUC-MSCs could increase the proportion of T-cell infiltration while increasing the expression of IFN-gamma and interleukin-17A in the spleen. In addition, we also revealed that hUC-MSC-derived TGFBI could repress activated T-cell proliferation by interfering with G1/S checkpoint CyclinD2 expression. Our results demonstrate that TGFBI plays a critical role in MSC immunologic regulation. TGFBI could be a new immunoregulatory molecule controlling MSC function for new treatments of T1DM. Schematic Representation of the Immunosuppression capacity of hUC-MSC by TGFBI.

Water quality degradation drives the release and fractionation transformation of trace metals in sediment.

The behavior and stability of trace metals in sediment are important to the ecology of rivers. Deteriorated water quality from domestic wastewater discharge has been studied extensively, but the effect of domestic wastewater on trace metals in sediment is poorly understood. To investigate this, we simulated the water quality degradation process through leaching experiments using domestic wastewater as the leaching solution. The results indicated that domestic wastewater does not negatively influence the stability and fractionation of trace metals in this experimental model, the existence of phosphate was the pacing factor for this phenomenon. Single-factor control treatment groups showed that a leaching solution with pH < 6, NaCl, NH4Cl, NaNO3, and humic acid promoted the dissolution of trace metals from sediment, whereas NaH2PO4 inhibited this process and increased their stability in sediment. The response of trace metals behavior to NaCl, NH4Cl, and extreme pH levels was more sensitive than NaNO3 and HA. Chloride ions can form relatively stable compounds with trace metals, reducing the activity of trace metals in the solution and promoting the release of trace metals from sediment, but it has positive effect on Pb and Zn stability and negative effect on Cu. Extreme pH conditions (pH > 10) and higher concentrations of leaching solutions (NaCl, NH4Cl, NaNO3, and HA) led to an increase in the Cu leaching concentration from sediment and the transformation to unstable fractions, while the impact on the stability of Zn and Pb was beneficial or had little effect. These experiment groups indicated that phosphate is beneficial to the stability of trace metals even at the condition of water degradation and can decrease the ecological risk caused by trace metals.

A critical review of the occurrence, fate and treatment of per- and polyfluoroalkyl substances (PFASs) in landfills.

The aim of this critical review is i) to summarize the occurrence of Per- and polyfluoroalkyl substances (PFASs) in landfills; ii) to outline the environmental fate and transport of PFASs in landfills; iii) to compare the treatment technologies of PFASs in landfill leachate and remediation methods of PFASs in surrounding groundwater; iv) to identify the research gaps and suggest future research directions. In recent years, PFASs have been detected in landfills around the world, among which Perfluoroalkyl acids (PFAAs) especially Perfluorooctanoic acid (PFOA) and Perfluorooctane sulfonic acid (PFOS) are mostly studied due to their long-term stability. Short-chain PFASs (<8 carbons) are more common than long-chain PFASs (≧8 carbons) in landfill leachate. PFASs in landfill leachate are eventually transported to the surrounding groundwater, surface water and soil. Some PFASs evaporate from landfills to the ambient air. To avoid the environmental and health risks of PFASs in landfills, new technologies and combined use of existing technologies have been implemented to treat PFASs in landfill leachate. Integrated remediation methods are applied to control the diffusion of PFASs in groundwater surrounding landfills. In future, the mechanisms of PFAAs precursors degradation, the correlation among PFASs in different environmental media around landfills, as well as the environmental behavior and toxic effect of combined pollutants together with PFASs in landfill leachate and surrounding groundwater should be studied.

Wavelet Packet Decomposition-Based Multiscale CNN for Fault Diagnosis of Wind Turbine Gearbox.

This article presents an intelligent fault diagnosis method for wind turbine (WT) gearbox by using wavelet packet decomposition (WPD) and deep learning. Specifically, the vibration signals from the gearbox are decomposed using WPD and the decomposed signal components are fed into a hierarchical convolutional neural network (CNN) to extract multiscale features adaptively and classify faults effectively. The presented method combines the multiscale characteristic of WPD with the strong classification capacity of CNNs, and it does not need complex manual feature extraction steps as usually adopted in existing results. The presented CNN with multiple characteristic scales based on WPD (WPD-MSCNN) has three advantages: 1) the added WPD layer can legitimately process the nonstationary vibration data to obtain components at multiple characteristic scales adaptively, it takes full advantage of WPD and, thus, enables the CNN to extract multiscale features; 2) the WPD layer directly sends multiscale components to the hierarchical CNN to extract rich fault information effectively, and it avoids the loss of useful information due to hand-crafted feature extraction; and 3) even if the scale changes, the lengths of components remain the same, which shows that the proposed method is robust to scale uncertainties in the vibration signals. Experiments with vibration data from a production wind farm provided by a company using condition monitoring system (CMS) show that the presented WPD-MSCNN method is superior to traditional CNN and multiscale CNN (MSCNN) for fault diagnosis.

Neoantigen cancer vaccines: a new star on the horizon.

Immunotherapy represents a promising strategy for cancer treatment that utilizes immune cells or drugs to activate the patient's own immune system and eliminate cancer cells. One of the most exciting advances within this field is the targeting of neoantigens, which are peptides derived from non-synonymous somatic mutations that are found exclusively within cancer cells and absent in normal cells. Although neoantigen-based therapeutic vaccines have not received approval for standard cancer treatment, early clinical trials have yielded encouraging outcomes as standalone monotherapy or when combined with checkpoint inhibitors. Progress made in high-throughput sequencing and bioinformatics have greatly facilitated the precise and efficient identification of neoantigens. Consequently, personalized neoantigen-based vaccines tailored to each patient have been developed that are capable of eliciting a robust and long-lasting immune response which effectively eliminates tumors and prevents recurrences. This review provides a concise overview consolidating the latest clinical advances in neoantigen-based therapeutic vaccines, and also discusses challenges and future perspectives for this innovative approach, particularly emphasizing the potential of neoantigen-based therapeutic vaccines to enhance clinical efficacy against advanced solid tumors.

Coxiella burnetii and Bartonella Endocarditis Diagnosed by Metagenomic Next-Generation Sequencing.

(1) Background: Culture-negative endocarditis is challenging to diagnose. Here, we retrospectively identified 23 cases of Coxiella burnetii and Bartonella endocarditis by metagenomic next-generation sequencing. (2) Methods: Twenty-three patients with culture-negative endocarditis were retrospectively enrolled from Guangdong Provincial People's Hospital (n = 23) between April 2019 and December 2021. Metagenomic next-generation sequencing was performed on blood (n = 22) and excised cardiac valvular tissue samples (n = 22) for etiological identification, and Sanger sequencing was performed for pathogenic diagnostic verification. The demographic and clinical data of the 23 patients were obtained from hospital electronic health records. (3) Results: A total of 23 male patients (median age, 56 years (interquartile range, 16)) with culture-negative endocarditis were diagnosed with Coxiella burnetii (n = 21) or Bartonella (n = 2) species infection by metagenomic next-generation sequencing. All patients underwent cardiac surgery. The resected tissue exhibited both a significantly higher number of unique suspected pathogen read-pairs and more unique pathogen read-pairs than the blood specimens. The results of Sanger sequencing tests on all remaining tissue and blood specimens were positive. Oral doxycycline was added to the antibiotic regimen for at least 1.5 years according to etiology. A total of 21 patients (91%) were discharged, and 20 patients were healthy at the 21-month (interquartile range, 15) follow-up visit. One patient exhibited endocarditis relapse with the same pathogen from inadequate antibiotic administration. The last 2 patients (9%) developed septic shock and multiple organ dysfunction syndrome postoperatively and died shortly after discharge. (4) Conclusions: CNE caused by C. burnetii and Bartonella species is challenging to diagnose and exhibits poor outcome due to delayed treatment. In response, mNGS, characterized by high sensitivity and rapid results, is an effective alternative for the etiological identification of C. burnetii and Bartonella endocarditis.

Maternal inappropriate calcium intake aggravates dietary-induced obesity in male offspring by affecting the differentiation potential of mesenchymal stem cells.

BACKGROUND: The effects of inappropriate dietary calcium intake in early life on later obesity have not been fully elucidated. AIM: To raise the mechanism of maternal calcium intake on the multi-differentiation potential of mesenchymal stem cells among their male offspring. METHODS: Four-week-old female C57BL/6N mice were fed by deficient, low, normal and excessive calcium reproductive diets throughout pregnancy and lactation. Bone MSCs (BMSCs) were obtained from 7-day-old male offspring to measure the adipogenic differentiation potential by the Wnt/ß-catenin signaling pathway. The other weaning male pups were fed a high-fat diet for 16 wk, along with normal-fat diet as the control. Then the serum was collected for the measurement of biochemical indicators. Meanwhile, the adipose tissues were excised to analyze the adipocyte sizes and inflammatory infiltration. And the target gene expressions on the adipogenic differentiation and Wnt/ß-catenin signaling pathway in the adipose tissues and BMSCs were determined by real-time reverse transcription polymerase chain reaction. RESULTS: Compared with the control group, maternal deficient, low and excessive calcium intake during pregnancy and lactation aggravated dietary-induced obesity, with larger adipocytes, more serious inflammatory infiltration and higher serum metabolism indicators by interfering with higher expressions of adipogenic differentiation (PPARγ, C/EBPα, Fabp4, LPL, Adiponectin, Resistin and/or Leptin) among their male offspring (P < 0.05). And there were significantly different expression of similar specific genes in the BMSCs to successfully polarize adipogenic differentiation and suppress osteogenic differentiation in vivo and in vitro, respectively (P < 0.05). Meanwhile, it was accompanied by more significant disorders on the expressions of Wnt/ß-catenin signaling pathway both in BMSCs and adulthood adipose tissues among the offspring from maternal inappropriate dietary calcium intake groups. CONCLUSION: Early-life abnormal dietary calcium intake might program the adipogenic differentiation potential of BMSCs from male offspring, with significant expressions on the Wnt/ß-catenin signaling pathway to aggravate high-fat-diet-induced obesity in adulthood.

hUC-MSCs Attenuate Acute Graft-Versus-Host Disease through Chi3l1 Repression of Th17 Differentiation.

Mesenchymal stem cells (MSCs) have already demonstrated definitive evidence of their clinical benefits in acute graft-versus-host disease (aGvHD) and other inflammatory diseases. However, the comprehensive mechanism of MSCs' immunomodulation properties has not been elucidated. To reveal their potential immunosuppressive molecules, we used RNA sequencing to analyze gene expression in different tissue-derived MSCs, including human bone marrow, umbilical cord, amniotic membrane, and placenta, and found that chitinase-3-like protein 1 (Chi3l1) was highly expressed in human umbilical cord mesenchymal stem cells (hUC-MSCs). We found that hUC-MSCs treated with interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α) exhibited increased expression of Chi3l1 and concurrently repressed T-helper 17 cell (Th17) differentiation through inhibition of signal transducer and activator of transcription 3 (STAT3) activation. Furthermore, Chi3l1 knockdown hUC-MSCs exhibited impaired therapeutic efficacy in aGvHD mice with an increased inflammatory response by promoting Th17 cell differentiation, including an increase in IL-17A in the spleen, intestine, and serum. Collectively, these results reveal a new immunosuppressive molecule, Chi3l1, in hUC-MSCs in the treatment of aGvHD that regulates Th17 differentiation and inhibits STAT3 activation. These novel insights into the mechanisms of hUC-MSC immunoregulation may lead to the consistent production of hUC-MSCs with strong immunosuppressive functions and thus improved clinical utility.

Exploring the Impact and Path of Environmental Protection Tax on Different Air Pollutant Emissions.

Existing studies have examined the double dividend effect of environmental protection tax. However, less attention has been paid to the influencing factors and transmission paths of the pollution abatement effect of the environmental protection tax. Based on the panel data for 30 of China's provinces from 2007 to 2019, this study discusses the environmental protection tax's influencing factors and transmission paths on the emission scale and intensity of different air pollutants through the panel threshold regression model and mediating effect model. The results show that: (1) the environmental protection tax has a positive emission reduction effect on the emission scale or emission intensity of sulfur dioxide (SO2) and nitrogen oxides (NO2); (2) the abatement effect is stronger when per capita gross regional product is above the threshold value; (3) technological progress, economic growth, and industrial structure all have positive mediating effects. Therefore, the local environmental protection tax rate should be set with comprehensive consideration of regional economic development, industrial structure, and technological progress.

Does a Recycling Carbon Tax with Technological Progress in Clean Electricity Drive the Green Economy?

The environmental issue is a significant challenge that China faces in leading the development of the green economy. In this context, reducing CO2 emissions is the key to combatting this problem. Taking the 2017 social accounting matrix (SAM) as the database and combing macroeconomic parameters from previous studies, this article constructed the environmentally computable general equilibrium (CGE) model as an analytical model to analyze the economic-environmental-energy impacts of recycling carbon tax with technological progress in clean electricity. We found that when the rate of clean electricity technological progress reaches 10%, the carbon recycling tax that reduces corporate income taxes will achieve a triple dividend of the carbon tax, namely, promoting economic development, reducing carbon emissions, and improving social welfare. In the meantime, on the basis of carbon tax policies that raise the price of fossil energy, clean electricity technological progress will help accelerate the transformation of electricity structure, reduce the proportion of thermal power generation, and better promote emission reduction. In addition, due to the high carbon emission coefficient, coal contributes significantly to carbon emission reduction. Therefore, China should implement a carbon tax recycling policy supplemented by the progress of clean power technology as soon as possible to better promote green economy development.

Spatial Correlation of Air Pollution and Its Causes in Northeast China.

To understand the status of air pollution in northeastern China, we explore the structure of air pollution transmission networks and propose targeted policy recommendations. Using air pollution data from 35 cities in northeastern China for a total of 879 periods from 6 January 2015 to 3 June 2017, this paper used social network analysis (SNA) to construct a spatial association network of air pollution in the region, and analyzed the spatial association of air pollution among cities and its causes in an attempt to reveal the transmission path of air pollution in the region. The results show that inter-city air pollution in northeast China forms a complex and stable correlation network with obvious seasonal differences of "high in winter and low in summer". Different cities in the region play the roles of "spillover", "intermediary" and "receiver" of air pollution in the network. Small respirable particulate (PM2.5) pollution constitutes a significant component of air pollution in northeast China, which spreads from Liaoning province to Heilongjiang province via Jilin province. Therefore, regional joint pollution prevention and control measures should be adopted to combat the air pollution problem, and different treatment measures should be developed for different city "roles" in the pollution network, in order to fundamentally solve the air pollution problem in the region.

How to Promote Low-Carbon Economic Development? A Comprehensive Assessment of Carbon Tax Policy in China.

Facing the increasingly severe environmental problems, the development of a green and sustainable low-carbon economy has become an international trend. In China, the core issue of low-carbon economic development is effectively resolving the contradiction between the exploitation and utilization of fossil energy and greenhouse gas emissions (mainly carbon emissions). Based on the SAM matrix, we established a static Computable General Equilibrium (CGE) model to simulate the impact of carbon tax policies on energy consumption, carbon emissions, and macroeconomics variables under 10, 20, and 30% emission reductions. Meanwhile, we analyze the impact of different carbon tax recycling mechanisms under the principle of tax neutrality. We find that the carbon tax effectively reduces carbon emissions, but it will negatively impact economic development and social welfare. A reasonable carbon tax recycling system based on the principle of tax neutrality can reduce the negative impact of carbon tax implementation. Among the four simulated scenarios of carbon tax cycle, the scenario of reducing residents' personal income tax is most conducive to realizing the "double dividend" of carbon tax.

Wip1 regulates the immunomodulatory effects of murine mesenchymal stem cells in type 1 diabetes mellitus via targeting IFN-α/BST2.

Mesenchymal stem cells (MSCs) show significant therapeutic effects in type 1 diabetes mellitus (T1DM) as regulating the inflammatory processes. However, little is known about the detailed process of MSCs immunosuppression in T1DM. In this study, we investigated the effects of wild-type p53-induce phosphatase 1 (Wip1) on regulating MSCs immunosuppressive capacities in T1DM mice. We found that Wip1 knockout (Wip1-/-) MSCs had lower therapeutic effects in T1DM mice, and displayed weaker immunosuppressive capability. In vivo distribution analysis results indicated thatWip1-/-MSCs could home to the damaged pancreas and increase the expression of tumor necrosis factor-α (TNF-α), interleukin-17a (IL-17a), interferon-α(IFN-α), IFN-ß, and IFN-γ, while decrease the expression of IL-4 and IL-10. Moreover, we confirmedWip1-/-MSCs exhibited weaker immunosuppressive capacity, as evidenced by enhanced expression of bone marrow stromal cell antigen 2(BST2) and IFN-α. In conclusion, these results revealed Wip1 affects MSCs immunomodulation by regulating the expression of IFN-α/BST2. Our study uncovered that Wip1 is required to regulate the therapeutic effects of MSCs on T1DM treatment, indicating a novel role of Wip1 in MSCs immunoregulation properties.

Is Technological Progress Selective for Multiple Pollutant Emissions?

Current research on technological progress does not focus on whether there is a biased selection of technological progress based on the resulting pollutant emissions and the emission reduction effect. This paper measures green total factor productivity for 30 provinces in China from 2004-2018 and tests whether technological progress is selectively biased towards the pollutants emitted. The results find a selective bias of technological progress on pollutant emissions, and there is also heterogeneity in the selective bias across regions. The current level of technological progress is on the right side of the inverted U-shaped inflection point for SO2 and PM2.5 and the left side of the inverted U-shaped inflection point for CO2. The improvement of technological progress can reduce the emissions of SO2 and PM2.5. Still, the results indicate that the reduction effect of these two pollutants originates from the treatment process rather than reducing the source of the production side. The inability of technological advancement to reduce CO2 emissions suggests some carbon lock-in in China's technological advancement. The Chinese government should increase the proportion of new energy applications and reduce the production methods of polluting industries to reduce pollutants effectively.