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Programmed death-ligand 1 (PD-L1) is a promising target for cancer immunotherapy due to its ability to inhibit T cell activation; however, its expression on various noncancer cells may cause on-target off-tumor toxicity when designing PD-L1-targeting Chimeric Antigen Receptor (CAR) T cell therapies. Combining rational design and directed evolution of the human fibronectin-derived monobody scaffold, PDbody was engineered to bind to PD-L1 with a preference for a slightly lower pH, which is typical in the tumor microenvironment. PDbody was further utilized as a CAR to target the PD-L1-expressing triple negative MDA-MB-231 breast cancer cell line. To mitigate on-target off-tumor toxicity associated with targeting PD-L1, a Cluster of Differentiation 19 (CD19)-recognizing SynNotch IF THEN gate was integrated into the system. This CD19-SynNotch PDbody-CAR system was then expressed in primary human T cells to target CD19-expressing MDA-MB-231 cancer cells. These CD19-SynNotch PDbody-CAR T cells demonstrated both specificity and efficacy in vitro, accurately eradicating cancer targets in cytotoxicity assays. Moreover, in an in vivo bilateral murine tumor model, they exhibited the capability to effectively restrain tumor growth. Overall, CD19-SynNotch PDbody-CAR T cells represent a distinct development over previously published designs due to their increased efficacy, proliferative capability, and mitigation of off-tumor toxicity for solid tumor treatment.

Abstract The significance of democratic commitment is highlighted on a global scale by the importance placed on offering a multitude of chances to establish enduring ecosystems and foster economic progress. Social finance, capital formation, and green finance have recently received a lot of attention from this perspective. Past studies mainly examined social finance and green finance in isolation. When investigating the individual impact of these important variables on economic growth in the occurrence of important events like the COVID-19 pandemic and other environmental pollution issues, most studies have mainly focused on developed countries, ultimately ignoring the different dynamics in emerging economies. The purpose of the research is to investigate the joint interaction between social finance (Social Impact Bonds), capital formation, and green finance (green loans, green investments, and green security) on economic development in BRICS economies. This research employed a longitudinal dataset from 2013 to 2023. The generalized method of moments (GMM) and fixed effect model (FEM) were employed in this research as statistical techniques for estimating parameters. The findings of this study revealed a positive joint relationship between green finance, capital formation, and social financing on economic development of BRICS economies. Therefore, measures that jointly promote social and green finance amidst environmental challenges or economic risks could present opportunities to mitigate the vulnerability of a country's economic prosperity. This research will surely guide policymakers in developing economies on how to give considerable attention to sustainable aspects while formulating policies and strategies aimed at economic development.

Abstract Background Dual bronchodilator therapy, consisting of a long-acting beta-agonist (LABA) and a long-acting muscarinic antagonist (LAMA), has proven effective for patients with chronic obstructive pulmonary disease (COPD). However, it remains uncertain whether there are efficacy differences between current and former smokers with COPD. This study aims to explore the effectiveness of LABA/LAMA therapies in both these groups. Methods The TOReTO trial assessed lung function, symptoms, health status, the occurrence of exacerbations, clinically significant exacerbations, and the use of LABA/LAMA therapies. These therapies include Tio/Olo, umeclidinium/vilanterol (Umec/Vi), and umeclidinium/vilanterol (Umec/Vi) are used in patients with COPD. The study examined the differences in outcomes between current and former smokers. To balance the baseline characteristics, propensity score matching (PSM) was employed. Results Data from 967 patients were collected. After PSM, the time to the first acute exacerbation in current smokers was analyzed separately for the three treatment groups and was significantly different between them (p = 0.0457). Among, there are differences in the occurrence of acute exacerbation between treatment and smoking status in Umec/Vi (p = 0.0114). There is no significant difference in the treatment of former smokers among the three different groups of LABA/LAMA fixed-dose combinations (p = 0.3079). COPD-related symptoms remained stable throughout the treatment period. There were no significant differences in symptom scores, including CAT and mMRC, among the three groups at the end of the study. Conclusions The three fixed-dose combinations of LABA/LAMA showed no difference in reducing exacerbations in former smokers but did show differences in current smokers. This trend has clinical significance, and future research will be conducted to control influencing variables to validate this point. However, due to the non-randomized study design, these findings should be interpreted with caution.

Abstract Cellular bioenergetics and mitochondrial dynamics are crucial for the secretion of insulin by pancreatic beta cells in response to elevated levels of blood glucose. To elucidate the interactions between energy production and mitochondrial fission/fusion dynamics, we combine live-cell mitochondria imaging with biophysical-based modeling and graph-based network analysis. The aim is to determine the mechanism that regulates mitochondrial morphology and balances metabolic demands in pancreatic beta cells. A minimalistic differential equation-based model for beta cells is constructed that includes glycolysis, oxidative phosphorylation, calcium dynamics, and fission/fusion dynamics, with ATP synthase flux and proton leak flux as main regulators of mitochondrial dynamics. The model shows that mitochondrial fission occurs in response to hyperglycemia, starvation, ATP synthase inhibition, uncoupling, and diabetic conditions, in which the rate of proton leakage exceeds the rate of mitochondrial ATP synthesis. Under these metabolic challenges, the propensities of tip-to-tip fusion events simulated from the microscopy images of the mitochondrial networks are lower than those in the control group and prevent the formation of mitochondrial networks. The study provides a quantitative framework that couples bioenergetic regulation with mitochondrial dynamics, offering insights into how mitochondria adapt to metabolic challenges.

Abstract Protein complexes are fundamental to all cellular processes, so understanding their evolutionary history and assembly processes is important. Gene duplication followed by divergence is considered a primary mechanism for diversifying protein complexes. Nonetheless, to what extent assembly of present-day paralogous complexes has been constrained by their long evolutionary pathways and how cross-complex interference is avoided remain unanswered questions. Subunits of protein complexes are often stabilized upon complex formation, whereas unincorporated subunits are degraded. How such cooperative stability influences protein complex assembly also remains unclear. Here, we demonstrate that subcomplexes determined by cooperative stabilization interactions serve as building blocks for protein complex assembly. We further develop a protein stability-guided method to compare the assembly processes of paralogous complexes in cellulo. Our findings support that oligomeric state and the structural organization of paralogous complexes can be maintained even if their assembly processes are rearranged. Our results indicate that divergent assembly processes by paralogous complexes not only enable the complexes to evolve new functions, but also reinforce their segregation by establishing incompatibility against deleterious hybrid assemblies.

This study evaluates the utilization of ethyl lactate as an environmentally friendly solvent for extracting phenolic compounds from the Orthosiphon stamineus (O. stamineus) by employing aqueous two-phase system (ATPS). Ethyl lactate (EL) was selected as the primary component for the top phase due to its non-toxic attributes and cost-effectiveness. The impact of type of salt, phase compositions, sample loading, pH, equilibration time, and neutral salt’s composition on the partition coefficient, K; yield, Y; and 2,2-diphenyl-1-pircrylhydrazyl (DPPH) scavenging activity of phenolic compounds was evaluated. The EL-salt ATPS contained 41.9% (w/w) EL and 14.6% (w/w) sulfate at 1.4% (w/w) of sample load, 1.5% (w/w) of potassium chloride, and pH 6.0, had the greatest K of 23.28 ± 0.12, Y of 99.03% ± 1.37%, and DPPH scavenging activity of 98.22% ± 0.40%. Therefore, the study underscores the efficiency of EL-based ATPS for extracting phenolic compounds from plants.

Abstract UVC‐LEDs have drawn attention recently because of their benefits to sterilization, decontamination, etc. Since the internal quantum efficiency and light extraction efficiency (LEE) of UVC‐LEDs are low, their external quantum efficiency remains unsatisfied. To enhance the LEE, this study proposes an integration design with the features of substrate‐thickness optimization, substrate shaping, diffuse‐reflective coating, an index‐matching layer, and taper‐base optimization. In addition to optical modeling via ray tracing, thermal modeling is conducted to evaluate both the optical and thermal performances of each feature. The simulation results show that, by means of the combination of these features, the LEE of the chip can be raised from 18.5% to more than 40%, and the average temperature of the device can be lowered by 2.2°C via the design of the diffuse‐reflective coating.

The hole accelerator is proven to benefit the hole injection for traditional light‐emitting diodes (LEDs) because the induced electric field provides the holes with more kinetic energy to pass through the electron‐blocking layer, enhancing the hole injection efficiency. Herein, the effect of the hole accelerator (HA) layer on the micro‐LEDs by modeling the characteristics of the devices with a current density of lower than 10 A cm−2 is investigated. The simulation results show that the appended HA layer brings a knot of the electric field in the HA layer, leading to higher internal quantum efficiency (IQE) than the device without HA under the low current density. The thickness and composition of HA, the quantum number, and the material of quantum barrier are also simulated and analyzed. The simulated radiative, Shockley–Read–Hall, and Auger recombination rates show that the IQE of the micro‐LED with the HA layer is higher than that without the HA layer under the current density of lower than 10 A cm−2.

Recognising the significant role of artificial intelligence in the labour market is essential for China to develop sustainably. The research utilises the mixed frequency vector auto-regression (MF-VAR) technique, which would innovatively incorporate data at different frequencies into one model to identify the intricate correlation between the monthly artificial intelligence index (AII) and the quarterly unemployment rate (UR) in China. Through comparison, the MF-VAR method has a more substantial explanatory power than the low-frequency VAR (LF-VAR) model, the impulse responses of the former reveal that AII exerts favourable and adverse influences on UR. Among them, the positive effect occurs on the AII in the first and second months. In contrast, the negative one appears on the AII in the third month, highlighting that artificial intelligence has both stimulating and inhibiting effects on the labour market in China. By analysing UR’s predictive error variance decomposition, the total impact of China’s artificial intelligence technology on employment is a substitution; this outcome is accordant with the theoretical dis¬cussion. In the new round of scientific and technological revolution and industrial transformation, meaningful recommendations for China would be put forward to avert the wave of unemployment brought by the development of artificial intelligence technology. First published online 09 September 2024

Online lending is a product of digital transformation, which has had a profound impact on the traditional money market. This paper discusses the impact of peer-to-peer (P2P) online lending on the effectiveness of monetary policy. Through the bootstrap sub-sample rolling-window Granger causality tests show that P2P has both positive and negative impacts on the money supply (M2). The positive impact of P2P on M2 indicates that online loans increase the amount of money supply. The negative impact of P2P on M2 shows that it may cut the money supply, thus weakening the monetary policy effectiveness. The general equilibrium model is inconsistent with these results, which underlines a positive effect from P2P to M2. In turn, the negative impact points out that the adjustment of monetary policy will hinder the development of P2P. The negative impact of M2 on P2P indicates that through the regulation of money supply, the online lending market can be correctly guided to prevent financial market from getting out of control. Through the supervision of online lending industry, we can accurately grasp the development of the internet financial industry and reduce its impact on monetary policy. First published online 3 September 2024

Studying the interplay between energy imports and employment is paramount for attaining sustainable development in Germany. The research employs the time-varying parameters-vector autoregression-stochastic volatility (TVP-VAR-SV) methodology to capture the dynamic correlation between energy import price (EIP) and unemployment rate (UR) under the control of consumer price index (CPI), which is constantly evolving. In quantitative analyses, it is clear that EIP significantly and positively impacts UR, indicating that a surge in imported energy costs has adverse consequences for the German labour market, possibly leading to job cuts and a spike in unemployment. Conversely, UR has a notable negative impact on EIP, particularly in the short period, signifying that an elevated unemployment rate reduces demand for imported energy. Further, the favourable impact of EIP on CPI, coupled with CPI's detrimental effect on UR, underscores the pivotal importance of CPI as a critical control variable. Additionally, we reinforce the robustness of these conclusions through stringent testing that encompassed the introduction of a business cycle-related control variable, variations in the number of iterations and replacement of energy import price. Amidst the severe energy crisis, this study aims to offer crucial recommendations to Germany for securing its energy imports and stabilising the labour market.

Abstract Recurrent DNA break clusters (RDCs) are replication-transcription collision hotspots; many are unique to neural progenitor cells. Through high-resolution replication sequencing and a capture-ligation assay in mouse neural progenitor cells experiencing replication stress, we unravel the replication features dictating RDC location and orientation. Most RDCs occur at the replication forks traversing timing transition regions (TTRs), where sparse replication origins connect unidirectional forks. Leftward-moving forks generate telomere-connected DNA double-strand breaks (DSBs), while rightward-moving forks lead to centromere-connected DSBs. Strand-specific mapping for DNA-bound RNA reveals co-transcriptional dual-strand DNA:RNA hybrids present at a higher density in RDC than in other actively transcribed long genes. In addition, mapping RNA polymerase activity uncovers that head-to-head interactions between replication and transcription machinery result in 60% DSB contribution to the head-on compared to 40% for co-directional. Taken together we reveal TTR as a fragile class and show how the linear interaction between transcription and replication impacts genome stability.

Abstract Isofagomine (IFG) and its analogues possess promising glycosidase inhibitory activities. However, a flexible synthetic strategy toward both C5a-functionalized IFGs remains to be explored. Here we show a practical synthesis of C5a-S and R aminomethyl IFG-based derivatives via the diastereoselective addition of cyanide to cyclic nitrone 1. Nitrone 1 was conveniently prepared on a gram scale and in high yield from inexpensive (−)-diethyl d-tartrate via a straightforward method, with a stereoselective Michael addition of a nitroolefin and a Nef reaction as key steps. A 268-membered library (134 × 2) of the C5a-functionalized derivatives was submitted to enzyme- or cell-based bio-evaluations, which resulted in the identification of a promising β-glucocerebrosidase (GCase) stabilizer demonstrating a 2.7-fold enhancement at 25 nM in p.Asn370Ser GCase activity and a 13-fold increase at 1 μM in recombinant human GCase activity in Gaucher cell lines.

Abstract Background Based on a longitudinal cohort design, the aim of this study was to investigate whether individual-based 18F fluorodeoxyglucose positron emission tomography (18F-FDG-PET) regional signals can predict dementia conversion in patients with mild cognitive impairment (MCI). Methods We included 44 MCI converters (MCI-C), 38 non-converters (MCI-NC), 42 patients with Alzheimer’s disease with dementia, and 40 cognitively normal controls. Data from annual cognitive measurements, 3D T1 magnetic resonance imaging (MRI) scans, and 18F-FDG-PET scans were used for outcome analysis. An individual-based FDG-PET approach was applied using seven volumes of interest (VOIs), Z transformed using a normal FDG-PET template. Hypometabolism was defined as a Z score < -2 of regional standard uptake value ratio. For the longitudinal cognitive test scores, generalized estimating equations were used. A linear mixed-effects model was used to compare the temporal impact of cortical hypometabolism and cortical thickness degeneration. Results The clinical follow-up period was 6.6 ± 3.8 years (range 3.1 to 16.0 years). The trend of cognitive decline could differentiate MCI-C from MCI-NC after 3 years of follow-up. In the baseline 18F-FDG-PET scan of the patients with MCI, medial temporal lobe (MTL; 94.7% sensitivity, 80.5% specificity) and posterior cingulate cortex (PCC; 89.5% sensitivity, 73.1% specificity) hypometabolism predicted conversion with high accuracy. 18F-FDG-PET hypometabolism preceded dementia conversion at an interval of 3.70 ± 1.68 years and was earlier than volumetric changes, with the exception of the MTL. Conclusions Our finding supports the use of individual-based 18F-FDG-PET analysis to predict MCI conversion to dementia. Reduced FDG-PET metabolism in the MTL and PCC were strongly associated with future cognitive decline in the MCI-C group. Changes in 18F-FDG-PET occurred 1 to 8 years prior to conversion to dementia. Progressive hypometabolism in the PCC, precuneus and lateral temporal lobe, but not MTL, preceded MRI findings at the MCI stage.