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The effects of air pollution on metabolism have become a popular research topic, and a large number of studies had confirmed that air pollution exposure could induce insulin resistance (IR) to varying degrees, but the results were inconsistent, especially for the long-term exposures. The aim of the current study was to further investigate the potential effects of air pollution on IR. A systematic review and meta-analysis of four electronic databases, including PubMed, Embase, Web of Science and Cochrane were conducted, searching for relevant studies published before June 10, 2023, in order to explore the potential relationships between long-term exposure to air pollution and IR. A total of 10 studies were included for data analysis, including seven cohort studies and three cross-sectional studies. Four major components of air pollution, including PM 2.5 (particulate matter with an aerodynamic diameter of 2.5 µm or less), PM 10 (particulate matter with an aerodynamic diameter of 10 µm or less), NO 2 , and SO 2 were selected, and each analyzed for the potential impacts on insulin resistance, in the form of adjusted percentage changes in the homeostasis assessment model of insulin resistance (HOMA-IR). This systematic review and meta-analysis showed that for every 1 μg/m³ increase in the concentration of selected air pollutants, PM 2.5 induced a 0.40% change in HOMA-IR (95%CI: −0.03, 0.84; I2 =67.4%, p = 0.009), while PM 10 induced a 1.61% change (95%CI: 0.243, 2.968; I2 =49.1%, p = 0.001). Meanwhile, the change in HOMA-IR due to increased NO 2 or SO 2 exposure concentration was only 0.09% (95%CI: −0.01, 0.19; I2 =83.2%, p = 0.002) or 0.01% (95%CI: −0.04, 0.06; I2 =0.0%, p = 0.638), respectively. Long-term exposures to PM 2.5 , PM 10 , NO 2 or SO 2 are indeed associated with the odds of IR. Among the analyzed pollutants, inhalable particulate matters appear to exert greater impacts on IR. • Long-term exposure to air pollution is associated with the odds of insulin resistance. • Inhalable particulate matters have greater impacts on IR than other air pollutants. • Publication bias was considered in this meta-analysis and results seemed to be robust. [ABSTRACT FROM AUTHOR]

Nature gas plays an important part in daily life and petrochemical industry, but it always coexists with impurities of considerable amount, which hinders full utilization of methane and thus makes its purification an urgent issue to be addressed. Herein, via solvothermal reaction of N,N′-bis(3-methylbenzoic acid-4-yl)-1,4,5,8-naphthalenetetracarboxydiimide (H 2 L) and cadmium cation, we obtained a layer structure of [Cd 2 (L) 2 (H 2 O) 2 ]·4H 2 O (UPC-71) with sql/Shubnikov tetragonal plane net topology, where tiny pores are formed due to direct dense packing of layer by layer. After adding 1, 2-bis(4-pyridyl) ethane (BPEA) as ancillary ligand, a rare 8-fold interpenetrated framework, [Cd(L)(BPEA)]·4H 2 O (UPC-72), was obtained. Limited by their tiny pore volume, UPC-71 and UPC-72 both display somewhat small gas sorption capacities, but an obvious increase in the adsorption/separation performance can be observed in UPC-72 due to the effect of pore confinement strategy. In particular, the quantities of C 2 H 2 and CO 2 adsorbed are 1.54 and 0.83 ​mmol/g at ambient condition, and the IAST selectivities of C 2 H 2 /CH 4 and CO 2 /CH 4 are up to 20.1 and 4.7 for UPC-72. With the aid of GCMC simulation, we prove that there exist stronger binding interactions between C 2 H 2 and CO 2 with the active sites in UPC-72 , and thus enhances the separation selectivity. [Display omitted] • Two Cd-MOF (UPC-71 and UPC-72) were designed and synthesized. • Rare 8-fold interpenetrated structure is obtained via pore confinement strategy. • A new strategy is explored to improve adsorption/separation performance. • The IAST selectivities of UPC-72 exhibit a great improvement compared with UPC-71. • Interspersed behavior improved the sorption capacity effectively. [ABSTRACT FROM AUTHOR]

[Display omitted] Exposure to ammonia (NH 3) is known harmful to health, environment and industrial facilities, hence it is important for the trace detection of NH 3. Herein, for the first time, ultrasensitive room temperature NH 3 sensors are realized by assembling carbon quantum dots (CQDs) on free-standing ultrathin coordination polymers (CPs) nanosheets (Co[Ni(CN) 4 ]) with an average thickness of ∼2.5 nm, which demonstrate excellent sensitivity (R a /R g = 87.7 to 30 ppm), fast gas response speed (∼10 s to 30 ppm), remarkable repeatability, high selectivity, good long-term stability and low limit of theoretical detection (∼8 ppb) toward NH 3 gas. The NH 3 gas sensor enhancement through incorporation of CQDs provides a simple and environment-friendly strategy for further improving sensor property of CPs nanosheets. This work provides an effective way to construct new electrode materials for high-performance gas sensor devices via the rational design. [ABSTRACT FROM AUTHOR]

Edge computing has been considered as a leading paradigm to satisfy the low latency demand for some computation-intensive or data-intensive applications, especially for IIoT applications such as automatic line scheduling of the Internet of Vehicles, time-sensitive supply-chain supervision, and smart control of complex industrial processes. In the edge computing environment, app vendors prefer to cache their app data on edge servers to ensure low latency service. However, it is frequently a challenge in practice, because cache spaces on edge servers are limited and expensive. In view of this challenge, a d eep l earning-based e dge c aching o ptimization method, named DLECO, is proposed to reduce the cost during the cache planning process. In this paper, the edge app data caching problem is formulated as a constrained optimization problem. Then, the specific design of DLECO with a deep learning model is shown, which aims to minimize the overall system cost with lower service latency. The performance of DLECO is analyzed theoretically and experimentally with a collection of data from the real world. The experimental results show its superior performance through comparison with three representative methods. • The edge app data caching (EADC) problem is modeled formally, and the problem is proved to be NP-hard. • The deep learning-based edge caching optimization method, named DLECO, is proposed to solve the EADC problem. • DLECO is analyzed theoretically and evaluated against three representative methods through experiments to show its superior performance. [ABSTRACT FROM AUTHOR]

Previously, Escherichia coli was engineered to produce isobutyl acetate (IBA). Titers greater than the toxicity threshold (3 g/L) were achieved by using layer-assisted production. To avoid this costly and complex method, adaptive laboratory evolution (ALE) was applied to E. coli for improved IBA tolerance. Over 37 rounds of selective pressure, 22 IBA-tolerant mutants were isolated. Remarkably, these mutants not only tolerate high IBA concentrations, they also produce higher IBA titers. Using whole-genome sequencing followed by CRISPR/Cas9 mediated genome editing, the mutations (SNPs in metH , rho and deletion of arcA) that confer improved tolerance and higher titers were elucidated. The improved IBA titers in the evolved mutants were a result of an increased supply of acetyl-CoA and altered transcriptional machinery. Without the use of phase separation, a strain capable of 3.2-fold greater IBA production than the parent strain was constructed by combing select beneficial mutations. These results highlight the impact improved tolerance has on the production capability of a biosynthetic system. • E. coli was evolved for improved IBA tolerance, but also demonstrated higher titers. • Three mutations (metH , rho , arcA) were responsible for improved IBA tolerance. • Tolerance towards other acetate esters and acids was also demonstrated. • The metH , rho mutant had 3.2-fold greater production than the parent strain. [ABSTRACT FROM AUTHOR]

The unpredictable pharmacokinetics of non-renal cleared drugs in chronic kidney disease (CKD) patients is associated with the activity of drug transporters. However, the mechanisms underlying regulation of drug transporters are yet to be established. In this study, we demonstrated the involvement of a HDAC2-Foxo3α pathway in advanced oxidation protein products (AOPPs)-induced ATP-binding cassette subfamily B member 1 (ABCB1) expression and activity. The correlation of AOPPs accumulation with concentration of cyclosporine in plasma was evaluated in 194 patients with transplantation. Molecular changes in acetylation of various histones and related regulatory molecules were examined in HepG2 cell cultures treated with AOPPs. Accumulation of AOPPs in serum in relation to molecular changes in HDAC2-Foxo3α in vivo were evaluated in 5/6 nephrectomy (5/6 nx) and oral adenine (Adenine) CKD rat models. Interestingly, the cyclosporine level was negatively correlated with AOPPs in plasma. In addition, AOPPs markedly suppressed the expression of histone deacetylase 2 (HDAC2), inducing ABCB1 expression and activity in vitro and in vivo. Importantly, AOPPs modulated phosphorylation of Foxo3α and the upstream Akt protein. Our findings indicate that AOPPs regulate the expression and activity of ABCB1 via reducing HDAC2 expression and activating Foxo3α-dependent signaling. The collective results support the utility of AOPPs as a potential target for drug and/or dosage adjustment in CKD patients. Targeting of AOPPs presents a novel approach to regulate non-renal clearance. • Concentration of cyclosporine is correlated with AOPPs accumulation in patients. • AOPPs regulate HDAC2 and ABCB1 expression in HepG2 cells. • Accumulation of AOPPs regulate HDAC2 and ABCB1 expression in liver of CKD rats. • HDAC2-Foxo3α mediates AOPPs-induced ABCB1 expression. • HDAC2 and Foxo3α mediate AOPPs-stimulated activity of ABCB1 in HepG2 cells. [ABSTRACT FROM AUTHOR]