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Abstract Background M2-like tumor-associated macrophages (M2-like TAMs) play key roles in tumor progression and the immune response. However, the clinical significance and prognostic value of M2-like TAMs-associated regulatory genes in gastric cancer (GC) have not been clarified. Methods Herein, we identified M2-like TAM-related genes by weighted gene coexpression network analysis of TCGA-STAD and GSE84437 cohort. Lasso-Cox regression analyses were then performed to screen for signature genes, and a novel signature was constructed to quantify the risk score for each patient. Tumor mutation burden (TMB), survival outcomes, immune cells, and immune function were analyzed in the risk groups to further reveal the immune status of GC patients. A gene-drug correlation analysis and sensitivity analysis of anticancer drugs were used to identify potential therapeutic agents. Finally, we verified the mRNA expression of signature genes in patient tissues by qRT-PCR, and analyzed the expression distribution of these genes by IHC. Results A 4-gene (SERPINE1, MATN3, CD36, and CNTN1) signature was developed and validated, and the risk score was shown to be an independent prognostic factor for GC patients. Further analyses revealed that GC patients in the high-risk group had a worse prognosis than those in the low-risk group, with significant differences in TMB, clinical features, enriched pathways, TIDE score, and tumor microenvironment features. Finally, we used qRT-PCR and IHC analysis to verify mRNA and protein level expression of signature genes. Conclusion These findings highlight the importance of M2-like TAMs, provide a new perspective on individualized immunotherapy for GC patients.

Objective The aim of this study was to analyze the clinical significance and prognostic value of CD8 + T cell-related regulatory genes in hepatocellular carcinoma (HCC). Methods This was a retrospective study. We combined TCGA-LIHC and single-cell RNA sequencing data for Lasso-Cox regression analysis to screen for CD8 + T cell-associated genes to construct a novel signature. The expression of the signature genes was detected at cellular and tissue levels using qRT-PCR, immunohistochemistry, and tissue microarrays. The CIBERSORT algorithm was then used to assess the immune microenvironmental differences between the different risk groups and a drug sensitivity analysis was performed to screen for potential HCC therapeutic agents. Results An 8-gene CD8 + T cell-associated signature (FABP5, GZMH, ANXA2, KLRB1, CD7, IL7R, BATF, and RGS2) was constructed. Survival analysis showed that high-risk patients had a poorer prognosis in all cohorts. Tumor immune microenvironment analysis revealed 22 immune cell types that differed significantly between patients in different risk groups, with patients in the low-risk group having an immune system that was more active in terms of immune function. Patients in the high-risk group were more prone to immune escape and had a poorer response to immunotherapy, and AZD7762 was screened as the most sensitive drug in the high-risk group. Finally, preliminary experiments have shown that BATF has a promoting effect on the proliferation, migration and invasion of HuH-7 cells. Conclusions The CD8 + T-cell-associated signature is expected to be a tool for optimizing individual patient decision-making and monitoring protocols, and to provide new ideas for treatment and prognostic assessment of HCC.

Salinity is a major abiotic stress that seriously affects crop growth worldwide. In this work, we aimed to isolate potential halotolerant plant growth-promoting rhizobacteria (PGPR) to mitigate the adverse impacts of salt stress in rice. An isolate, D2, with multiple plant growth-promoting (PGP) characteristics was identified as Enterobacter asburiae D2. Strain D2 could produce indole-3-acetic acid and siderophore. It also exhibited phosphate solubilization and 1-aminocyclopropane-1-carboxylic deaminase activity. Genome analysis further provided insights into the molecular mechanism of its PGP abilities. Strain D2 inoculation efficiently stimulated rice growth under both normal and saline conditions. Compared with the non-inoculated plants, a significant increase in plant height (18.1–34.7%), root length (25.9–57.1%), root dry weight (57.1–150%), and shoot dry weight (17.3–50.4%) was recorded in inoculated rice seedlings. Meanwhile, rice seedlings inoculated with strain D2 showed improvement in chlorophyll and proline content, while the oxidant damage was reduced in these plants in comparison with the control group. Moreover, the K+/Na+ ratio of the inoculated rice seedlings exposed to NaCl and Na2CO3 was higher than that of the uninoculated groups. These results imply that Enterobacter asburiae D2 is a potential PGPR that can be used for alleviation of salt stress in rice.

Abstract Unspecific peroxygenases (UPOs) are glycosylated enzymes that provide an efficient method for oxyfunctionalizing a variety of substrates using only hydrogen peroxide (H2O2) as the oxygen donor. However, their poor heterologous expression has hindered their practical application. Here, a novel UPO from Marasmius fiardii PR910 (MfiUPO) was identified and heterologously expressed in Pichia pastoris. By employing a two-copy expression cassette, the protein titer reached 1.18 g L−1 in a 5 L bioreactor, marking the highest record. The glycoprotein rMfiUPO exhibited a smeared band in the 40 to 55 kDa range and demonstrated hydroxylation, epoxidation and alcohol oxidation. Moreover, the peroxidative activity was enhanced by 150% after exposure to 50% (v/v) acetone for 40 h. A semi-preparative production of 4-OH-β-ionone on a 100 mL scale resulted in a 54.2% isolated yield with 95% purity. With its high expression level, rMfiUPO is a promising candidate as an excellent parental template for enhancing desirable traits such as increased stability and selectivity through directed evolution, thereby meeting the necessary criteria for practical application. Graphical Abstract

With the deepening of transit-oriented development (TOD), the construction of high-density, multi-functional urban spatial structures around public transportation stations has become a significant focus in urban development planning. This study is aimed to explore the spatial and temporal cluster patterns and the relationship between taxi passenger flow and land use types around urban rail transit stations. Taking Beijing as an example, this study extracts the time series of pick-up and drop-off points from the taxi GPS track dataset and employs the affinity propagation (AP) method to conduct the spatial and temporal cluster analysis on these taxi pick-up and drop-off points. Then, based on the urban POI dataset, this study classifies these stations into four functional types by adopting the K-means method. Finally, the partial least squares (PLS) method has been used to explore the relationship between the taxi passenger flow and the land use types under different time intervals. The result indicates that: first, there is a regional aggregation effect for the taxi passenger source in the rail transit station area, and the cluster areas are mainly located in Chaoyang and Haidian districts, as well as along the circular metro line. Besides, there is a significant rush hour in the morning and evening for this passenger flow. Second, the commercial, residential, and comprehensive transit stations are mainly located in the central urban districts of Beijing with balanced spatial distribution, while the industrial transit stations are dispersed to the outer suburbs of the city, which conform to Alonso's spatial distribution of land. Third, there is a significant positive correlation between taxi passenger sources in the rail transit station area and land use types containing transportation service, public facility and daily life service. This study analyses the population mobility and land type cluster form around the urban rail transit from the micro-perspective, which verifies and supplements Alonso's transportation location theory. Therefore, this study contributes to the rational planning of urban spatial resource allocation and the construction of the urban rail transit network.

The emergence of taxi sharing enhances urban transport efficiency and reduces carbon emissions. Using GPS tracking data from taxis in Chengdu, China, this study first outlines conditions for identifying shareable taxi orders based on their origins and destinations. We then develop a three-phase computational model to optimize matches among all potential shareable orders, calculating the shareable mileage and the proportion of original mileage that could be shared. Our comprehensive temporal and spatial analysis reveal a significant market for taxi sharing in Chengdu, with higher potential on workdays than non-workdays and four distinct demand peaks throughout the day. The morning peak on workdays and the night peak on non-workdays are particularly pronounced. Most shareable orders originate within major city districts. We find a positive correlation between the potential of taxi sharing and average traffic speed, and negative correlations with order volume, regional economic development, and population density. Functional zones related to Enterprises, Motorcycle Services, and Transportation Services exhibit significantly higher sharing potential. Compared to traditional taxi operations, taxi sharing significantly reduces total travel mileage. This quantitative analysis offers insights into the potential demand for taxi sharing among urban residents and may help government authorities optimize taxi resources for the sustainable development of urban transport.

Abstract Glaucoma, the leading cause of irreversible blindness worldwide, is closely linked to aqueous overaccumulation and elevated intraocular pressure (IOP). For refractory glaucoma, aqueous shunts with valves are commonly implanted for effective aqueous drainage control and IOP stabilization. However, existing valved glaucoma implants have the disadvantages of inconsistent valve opening/closing pressures, poor long‐term repeatability due to their reliance on moving parts, and complex architectures and fabrication processes. Here, we propose a novel valving concept, the droplet Laplace valve (DLV), a three‐dimensional printable moving‐parts‐free microvalve with customizable and consistent threshold valving pressures. The DLV uses a flow discretization unit governed by capillarity, comprising a droplet‐forming nozzle, and a separated reservoir to digitize continuous flow into quantifiable droplets. Unlike the classic one‐time‐use Laplace valves, the DLV's unique design allows for its reusability. The opening pressure is adjustable by varying the nozzle size, like the classic Laplace valves (following the Young–Laplace equation), while the closing pressure can be modified by tuning the separation distance and the reservoir size. Various DLVs with customizable opening pressures from 5 to 11 mmHg have been demonstrated, with opening/closing pressure differences suppressed down to 0.99). Preliminary ex vivo validation in an enucleated porcine eye confirms the DLV's efficiency in aqueous shunting and prompt IOP stabilization. The DLV technology holds great promise in glaucoma implants for IOP management and various microsystems for flow control.

Plants possess intricate defense mechanisms to resist cadmium (Cd) stress, including strategies like metal exclusion, chelation, osmoprotection, and the regulation of photosynthesis, with antioxidants playing a pivotal role. The application of nitrogen (N) and phosphorus (P) fertilizers are reported to bolster these defenses against Cd stress. Several studies investigated the effects of N or P on Cd stress in non-woody plants and crops. However, the relationship between N, P application, and Cd stress resistance in valuable timber trees remains largely unexplored. This study delves into the Cd tolerance mechanisms of Phoebe zhennan, a forest tree species, under various treatments: Cd exposure alone, combined Cd stress with either N or P and Cd stress with both N and P application. Our results revealed that the P application enhanced root biomass and facilitated the translocation of essential nutrients like K, Mn, and Zn. Conversely, N application, especially under Cd stress, significantly inhibited plant growth, with marked reductions in leaf and stem biomass. Additionally, while the application of P resulted in reduced antioxidant enzyme levels, the combined application of N and P markedly amplified the activities of peroxidase by 266.36%, superoxide dismutase by 168.44%, and ascorbate peroxidase by 26.58% under Cd stress. This indicates an amplified capacity of the plant to neutralize reactive oxygen species. The combined treatment also led to effective regulation of nutrient and Cd distribution in roots, shoots, and leaves, illustrating a synergistic effect in mitigating toxic impact of N. The study also highlights a significant alteration in photosynthetic activities under different treatments. The N addition generally reduced chlorophyll content by over 50%, while P and NP treatments enhanced transpiration rates by up to 58.02%. Our findings suggest P and NP fertilization can manage Cd toxicity by facilitating antioxidant production, osmoprotectant, and root development, thus enhancing Cd tolerance processes, and providing novel strategies for managing Cd contamination in the environment.

With the advancement of computer technology, machine learning-based artificial intelligence technology has been increasingly integrated and applied in the fields of medicine, biology, and pharmacy, thereby facilitating their development. Transporters have important roles in influencing drug resistance, drug–drug interactions, and tissue-specific drug targeting. The investigation of drug transporter substrates and inhibitors is a crucial aspect of pharmaceutical development. However, long duration and high expenses pose significant challenges in the investigation of drug transporters. In this review, we discuss the present situation and challenges encountered in applying machine learning techniques to investigate drug transporters. The transporters involved include ABC transporters (P-gp, BCRP, MRPs, and BSEP) and SLC transporters (OAT, OATP, OCT, MATE1,2-K, and NET). The aim is to offer a point of reference for and assistance with the progression of drug transporter research, as well as the advancement of more efficient computer technology. Machine learning methods are valuable and attractive for helping with the study of drug transporter substrates and inhibitors, but continuous efforts are still needed to develop more accurate and reliable predictive models and to apply them in the screening process of drug development to improve efficiency and success rates.

The kidney is critical in the human body’s excretion of drugs and their metabolites. Renal transporters participate in actively secreting substances from the proximal tubular cells and reabsorbing them in the distal renal tubules. They can affect the clearance rates (CLr) of drugs and their metabolites, eventually influence the clinical efficiency and side effects of drugs, and may produce drug–drug interactions (DDIs) of clinical significance. Renal transporters and renal transporter-mediated DDIs have also been studied by many researchers. In this article, the main types of in vitro research models used for the study of renal transporter-mediated DDIs are membrane-based assays, cell-based assays, and the renal slice uptake model. In vivo research models include animal experiments, gene knockout animal models, positron emission tomography (PET) technology, and studies on human beings. In addition, in vitro–in vivo extrapolation (IVIVE), ex vivo kidney perfusion (EVKP) models, and, more recently, biomarker methods and in silico models are included. This article reviews the traditional research methods of renal transporter-mediated DDIs, updates the recent progress in the development of the methods, and then classifies and summarizes the advantages and disadvantages of each method. Through the sorting work conducted in this paper, it will be convenient for researchers at different learning stages to choose the best method for their own research based on their own subject’s situation when they are going to study DDIs mediated by renal transporters.

BackgroundM2-like tumor-associated macrophages (M2-like TAMs) have important roles in the progression and therapeutics of cancers. We aimed to detect novel M2-like TAM-related biomarkers in hepatocellular carcinoma (HCC) via integrative analysis of single-cell RNA-seq (scRNA-seq) and bulk RNA-seq data to construct a novel prognostic signature, reveal the “immune landscape”, and screen drugs in HCC.MethodsM2-like TAM-related genes were obtained by overlapping the marker genes of TAM identified from scRNA-seq data and M2 macrophage modular genes identified by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were carried out to screen prognostic genes from M2-like TAM-related genes, followed by a construction of a prognostic signature, delineation of risk groups, and external validation of the prognostic signature. Analyses of immune cells, immune function, immune evasion scores, and immune-checkpoint genes between high- and low-risk groups were done to further reveal the immune landscape of HCC patients. To screen potential HCC therapeutic agents, analyses of gene–drug correlation and sensitivity to anti-cancer drugs were conducted.ResultsA total of 127 M2-like TAM-related genes were identified by integrative analysis of scRNA-seq and bulk-seq data. PDLIM3, PAM, PDLIM7, FSCN1, DPYSL2, ARID5B, LGALS3, and KLF2 were screened as prognostic genes in HCC by univariate Cox regression and LASSO regression analyses. Then, a prognostic signature was constructed and validated based on those genes for predicting the survival of HCC patients. In terms of drug screening, expression of PAM and LGALS3 was correlated positively with sensitivity to simvastatin and ARRY-162, respectively. Based on risk grouping, we predicted 10 anticancer drugs with high sensitivity in the high-risk group, with epothilone B having the lowest half-maximal inhibitory concentration among all drugs tested.ConclusionsOur findings enhance understanding of the M2-like TAM-related molecular mechanisms involved in HCC, reveal the immune landscape of HCC, and provide potential targets for HCC treatment.

Two-dimensional (2D) crystalline materials have been regarded as promising sensor materials due to their large specific surface area, high sensitivity, and low cost. In the present work, based on the density functional theory (DFT) method, the sensor performance of novel silicon (Si)-doped nitrogenated holey graphene (SiC2N) toward five typical VOCs (HCHO, CH3OH, C3H6O, C6H6, and C2HCl3) and ammonia were systematically investigated. The results demonstrated that Si doping could effectively decrease the band gap of C2N and simultaneously provide active sites for gas adsorption. Through comprehensive analyses of adsorption energies and electronic properties, the SiC2N was found to exhibit high selectivity for O-containing VOCs (HCHO, CH3OH, and C3H6O) and NH3 via a covalent bond. Moreover, after the HCHO, CH3OH, C3H6O, and NH3 adsorption, the band gap of SiC2N greatly decreases from 1.07 eV to 0.29, 0.13, 0.25, and 0.12 eV, respectively, which indicated the enhancement the conductivity and enabled the SiC2N to be a highly sensitive resistive-type sensor. In addition, the SiC2N possesses a short recovery time. For instance, the recovery time of HCHO desorbed from SiC2N is 29.2 s at room temperature. Our work anticipates a wide range of potential applications of Si-doped C2N for the detection of toxic VOCs and ammonia, and supplies a valuable reference for the development of C2N-based gas sensors.

Several lines of evidence suggest that the intestinal microbiota plays crucial roles in infant development, and that it is highly influenced by extrinsic and intrinsic factors. Prebiotic-containing infant formula may increase gastrointestinal tolerance and improve commensal microbiota composition. However, it remains unknown whether supplementation of milk-formulas with prebiotics and 1,3-olein-2-palmitin (OPO) can achieve feeding outcomes similar to those of breastfeeding. In the present study, we investigated the effects of two kinds of infant formula with different additives on the overall diversity and composition of the fecal microbiota, to determine which was closer to breastfeeding. A total of 108 infants were enrolled, including breastfeeding (n=59) and formula feeding group (n=49). The formula feeding infants were prospectively randomly divided into a standard formula group (n=18), and a supplemented formula group(n=31). The fecal samples were collected at 4 months after intervention. Fecal microbiota analysis targeting the V4 region of the 16S rRNA gene was performed using MiSeq sequencing. The overall bacterial diversity and composition, key functional bacteria, and predictive functional profiles in the two different formula groups were compared with breastfeeding group. We found that the alpha diversity of the gut microbiota was not significantly different between the OPO and breastfeeding groups with Chaos 1 index (p=0.346). The relative abundances of Enhydrobacter and Akkermansia in the OPO group were more similar to those of the breastfeeding group than to those of the standard formula group. The gut microbiota metabolism function prediction analysis showed that the supplemented formula group was similar to the breastfeeding group in terms of ureolysis (p=0.297). These findings suggest that, when formula supplemented with prebiotics and OPO was given, the overall bacterial diversity and parts of the composition of the fecal microbiota would be similar to that of breastfeeding infants.

Cantharidin (CTD) is a widely used anticancer compound, but its clinical use is mainly limited due to hepatotoxicity. Ginsenoside Rb1 (GRb1) shows potential hepatoprotective effects. Nonetheless, the protective effect and underlying mechanism of GRb1 against CTD-induced hepatotoxicity in mice have not been investigated. This study aims to elucidate the effect and mechanism of GRb1 on CTD-induced hepatotoxicity using network pharmacology and in vivo experiments. Network pharmacology studies have shown that 263 targets were the main mechanisms by which GRb1 alleviates CTD-induced hepatotoxicity. KEGG enrichment analysis revealed that 75 hub genes were mainly enriched in TNF, IL-17 and apoptosis signalling pathways. Molecular docking analysis showed that GRb1 exhibited high affinity with Akt1, Tnf, Il6, Bcl2 and Caspase3. In addition, results from animal studies demonstrated that GRb1 could ameliorate CTD-induced hepatotoxicity by inhibiting protein expression of Caspase-3, Caspase-8, Bcl-2/Bax, GRP78, ATF6, ATF4, CHOP, IRE1a and PERK. This research revealed the mechanism of GRb1 against CTD-induced hepatotoxicity by inhibiting apoptosis and endoplasmic reticulum stress (ERS) and it may provide a scientific rationale for the potential use of GRb1 in the treatment of hepatotoxicity induced by CTD. [ABSTRACT FROM AUTHOR]

Abstract Background With the rapid aging trend of China's population, the issue of drug rational use in older adults has become more and more prominent. Parkinson’s disease (PD) is the one of the most common age-related neurodegenerative disorders. Pharmaceutical treatment plays a cardinal role in alleviating motor and non-motor symptoms to improve the quality of life of patients with PD. Patients with PD have complex medical needs yet little is known about the use of potentially inappropriate medications (PIM) among them in China. We quantify the prevalence of PIM use and identify its predictors among older persons with PD in China. Methods We conducted a cross-sectional analysis using a national representative database of all medical insurance beneficiaries across China, extracting records of ambulatory visits of older adults with PD between 2015 and 2017. Beneficiaries aged 65 and above were eligible for inclusion. The prevalence of patients exposed to overall PIMs and PIMs related to motor and cognitive impairment was calculated based on Beers Criteria 2015 version. Potential predictors of PIM concerning patients’ characteristics were estimated using multivariate logistic regression. Results A total of 14,452 older adults with PD were included. In total, 8,356 (57.8%) patients received at least one PIM; 2,464 (17.1%) patients received at least one motor-impairing PIM and 6,201 (42.9%) patients received at least one cognition-impairing PIM. The prevalence of overall PIM use was higher in patients of older age group (54.7% [65–74] vs. 59.5% [75–84; OR, 1.22; 95% CI, 1.14–1.31] vs.65.5% [≥ 85; OR, 1.58; 95% CI, 1.38–1.80) and females (61.4% [female] vs. 55.0% [males; OR, 0.77; 95% CI, 0.72–0.82). Conclusions Prescribing PIMs for older adults with PD was common in China, especially for females and older age groups, yet younger patients were more inclined to be prescribed with motor or cognition-impaired PIMs. Our findings represent a clear target awaiting multidimensional efforts to promote the rational prescribing of medications for this vulnerable population.

Summary: Background: The appropriateness of antibiotic use for acute respiratory infections (ARIs) in Chinese primary healthcare facilities (PHFs) remained uncertain. We aimed to evaluate to what degree antibiotic prescribing for ARIs were aligned with guideline recommendations in primary settings across China. Methods: We collected outpatient prescriptions from 262 Chinese PHFs in 27 cities of six provinces between 2017 and 2019. The appropriate antibiotic prescribing was defined as prescribing antibiotic classes that were recommended by Chinese clinical guidelines, if patients were prescribed antibiotics. We evaluated the magnitude of antibiotics prescribed for acute upper respiratory infections (AURIs), acute bronchitis, and community-acquired pneumonia (CAP) and their appropriateness. Findings: Overall, 55.1% (87,684/159,150), 66.8% (30,836/46,153), and 68.5% (4615/6733) of outpatients with AURIs, acute bronchitis, and CAP treated at PHFs in China were prescribed with antibiotics. Of all antibiotic prescriptions, only 20.0% (17,542/87,684), 18.6% (5724/30,836) and 69.6% (3211/4615) used antibiotic classes that were recommended by the guidelines for AURIs, acute bronchitis, and CAP, respectively. Patients residing in the Chinese central region (17.0%, 15.4%, 69.3% for AURIs, acute bronchitis, and CAP, respectively) were less likely to be prescribed with antibiotics that were appropriately selected. Interpretation: Unnecessary antibiotics were widely prescribed for patients with AURIs or acute bronchitis and most patients with ARIs did not receive guideline-recommended antibiotic classes in Chinese PHFs. Interventions to promote evidence-based treatment and the appropriate use of antibiotics are urgently needed at the primary level across China. Funding: This work was supported by the National Natural Science Foundation of China [grant number 72074007, 81973294].

ObjectiveThis study aimed to assess whether different clinical trial endpoints in pivotal trials of cancer drugs were associated with reimbursement decisions in China.Materials and methodsCancer drugs marketed before June 30th, 2021 with publicly available technical review reports for application of drug registration on Center for Drug Evaluation (CDE) website were reviewed. The trial design characteristics and relevant clinical outcomes [e.g., overall survival (OS), progression-free survival (PFS) and objective response rate (ORR)] were extracted from the technical review reports, while the reimbursement decisions were reviewed from National Healthcare Security Administration (NHSA) website. The differences in trial characteristics and clinical outcomes between drugs with positive reimbursement decisions and negative ones were compared by hypothesis test (Pearson's chi-squared test, Fisher's exact test, independent samples t-test and Mann-Whitney U test). The correlation between different clinical trial endpoints and reimbursement decisions was analyzed by multivariate logistic regression.ResultsThere were 112 cancer drug indications included in this study. Among these indications, 76 received a positive reimbursement decision, and the most common primary endpoints of them were PFS (42.1%) and ORR (30.3%). Taking PFS (OR = 7.333) and ORR (OR = 5.271) as the primary endpoints were more likely to receive a positive reimbursement decision compared with OS (P = 0.003). The proportion of drugs marketed with phase I (75.0%) and phase II (85.7%) clinical trials receiving positive reimbursement decisions are significantly higher than those marketed with phase III clinical trials (61.3%, P = 0.043). The magnitude of clinical benefit only had subtle influences (Prisk benefit − OS = 0.627, Prisk benefit − PFS = 0.087, Psurvival benefit − OS = 0.545, Psurvival benefit − PFS = 0.189) on the drug reimbursement decisions, however, the drug prices and clinical needs also made a difference on that.ConclusionThis study found that, in Chinese drug price negotiations from 2017 to 2021, policymakers have focused more on meeting clinical needs and filling therapeutical gaps in National Reimbursement Drug List (NRDL), while requirements for the selection of primary endpoints, clinical trial phases, and clinical benefits have been reduced. In the future, emphasis should be put on the use of surrogate endpoints and clinical benefits.

Directly coordinating transition metal catalysts to the linkers of stable metal organic frameworks (MOFs) is a sleek solution to increasing the longevity of the catalyst. Photoluminescence metal complexes incorporated in MOFs have risen in interest lately. Particularly, Re(bpydc)(CO)3Cl (bpydc = 2,2’-bipyridine-5,5’-dicarboxylic acid) doped zirconium-based MOFs (Re-UiO-67) and their use in the photocatalytic reduction of CO2 have attracted considerable attention. Nonetheless, the photophysical characteristics of Re-UiO-67 as a function of loading have not been well explored. Here we analyzed the structural and compositional properties of Re-UiO-67 and showed that the photoluminescence properties of rhenium doped MOFs, including emission intensity, maximum, and lifetime, can be tuned by changing the rhenium loading. The photoluminescence of the film made of Re-UiO-67 exposed to different vapors also exhibited vapoluminescence, luminescence vapochromism, and vapotemporism. Understanding of photophysical properties of the Re-doped MOFs material could provide guidance for further photocatalytic, solar energy conversion and sensing applications.