ACS Publications最新文献

This study examined the changing character of the last honours of those who died of COVID-19 in Kashmir and the life experiences of the families of the deceased. A semi-structured interview schedule was used to collect information from 21 participants. Using qualitative data analysis approaches, five key themes were identified vis-à-vis the impact of COVID-19 on burial rituals and customs; effects on bereaved families, shades of grief, bereavement care, community response, and coping with loss. Based on examining the pandemic-induced changes related to customs and rituals around death, the study found that the bereaved family members were in danger of marginalization, economic burdens, psychological traumas, and overall reduced quality of life. This study would be a credible addition to the existing literature on death practices as there is a shortage of research on funeral rituals during the post-pandemic period in Kashmir.

The Front Cover shows the synthesis of a new cobalt(II) coordination compound containing two 2,2′-bipyridyl ligands, a water molecule and, most interestingly, a sulfate(VI) anion in the coordination sphere. In addition, the newly presented compound [Co(bipy)₂(SO₄)(H₂O)] is perfectly suited as a catalyst in the oligomerization of olefins and leads to the synthesis of oligomers with unique physicochemical properties. More information can be found in the Research Article by M. Pawlak, D. Jacewicz and co-workers (DOI: 10.1002/ejic.202400755).

Two-dimensional coherent spectroscopy (2DCS) offers significant advantages in terms of high temporal and frequency resolutions and a signal-to-noise ratio. Until now, the response-function (RF) formalism has been the prevalent theoretical description. In this study, we compare the non-Hermitian Hamiltonian (NHH) method with the RF formalism in a three-level system with a constant control field. We obtain the signals from both approaches and compare their population dynamics and 2DCS. We propose quasi-Green functions for the NHH method, which allows all dominant Liouville paths to be inferred. We further simulated the 2DCS of Rh(CO)₂C₅H₇O₂ (RDC) dissolved in hexane with the NHH method, which is in good agreement with the previous experiments. Although the NHH method overestimates relaxations, it provides all important paths by analytical solutions, which are different from the four paths used in the RF formalism. Our results demonstrate that the NHH method is more suitable than the RF formalism for investigating the systems, including relaxation and control fields via the 2DCS.

Acidithiobacillus spp. have traditionally been utilized to extract metals from mineral ores through bioleaching. This process has recently expanded to include artificial ores, such as those derived from municipal solid waste incineration (MSWI) residues. Previous studies have indicated that microbial adaptation enhances bioleaching efficiency, prompting this study to identify proteins involved in the adaptation of A. ferridurans to MSWI residues. We employed data-independent acquisition-parallel accumulation serial fragmentation to determine the proteomic response of A. ferridurans DSM 583 to three distinct materials: bottom ash (BA), kettle ash (KA), and filter ash (FA), which represent typical MSWI residues. Our findings indicate that, irrespective of the residue type, a suite of membrane transporters, porins, efflux pumps, and specific electron and cation transfer proteins was notably upregulated. The upregulation of certain proteins involved in anaerobic pathways suggested the development of a spontaneous microaerobic environment, which minimally impacted the bioleaching efficiency. Additionally, the adaptation was most efficient at half the target FA concentration, marked by a significant increase in the detoxification and efflux systems required by microorganisms to tolerate high heavy metal concentrations. Given that metal recovery peaked at lower FA concentrations for most metals of interest, further adaptation at the level of protein expression may not be warranted for improved bioleaching outcomes.

The photoabsorption and infrared spectra (IR) of molecular systems are heavily influenced by aggregation. In the electronic spectra, the vibronic coupling effect is of utmost importance. Although treating both effects simultaneously can be challenging, it is often the only way to explain the experimental spectrum of molecular clusters. In this work, we study IR spectra and the vibronic coupling effect in the electronic photoabsorption spectra in molecular systems composed of benzene (monomer, dimers, and crystal). Photoabsorption spectra were generated using the direct vibronic coupling method at the density functional theory (DFT) level. We also simulated the spectra with the Liouville-Lanczos approach by calculating the electronic transitions along the main inducing modes for two forbidden transitions (¹A_1g → ¹B_2u and ¹A_1g → ¹B_1u). DFT was also applied to simulate IR spectra. For the monomer, vibronic coupling was crucial to induce the first and second forbidden transitions. On the other hand, molecular aggregation was sufficient to induce the first and second forbidden transitions in almost all dimers. However, when the vibronic coupling is evaluated for the clusters, the band in the energy range of the ¹A_1g → ¹B_1u transition is affected both by the aggregation itself and the inducing modes. Moreover, some inducing modes drastically change the allowed ¹A_1g → ¹E_1u transition, depending on the dimer under study due to symmetry breaking. In terms of IR spectra, clear signatures are present. For instance, the intensities of the C-H stretching modes decrease as aggregation increases. This work shows that aggregation impacts the band shapes differently in relation to the benzene aggregate structure and the excitation under analysis.

Inspired by natural materials, constructing hierarchically porous composite materials can better meet the increasingly demanding needs of engineering materials. Currently, lightweight polyimide components commonly used in aerospace and deep-sea applications are difficult to combine with cross-scale pores due to limitations in performance stability and porogenic strategies. Finding an efficient, environmentally friendly, convenient, and highly controllable method to prepare hierarchically porous polyimide (HPPI) to utilize structural advantages for functional suitability remains a huge challenge. Here, we propose a solvent-assisted supercritical CO₂ foaming strategy to develop ultralarge pore span polyimide (ODA-ODPA). This strategy can not only realize the construction of HPPIs, but also regulate the porosities span from 15 to 75%. The HPPI mechanical parts prepared by controlling the foaming conditions can improve the oil storage and supply capacity and reduce the material quality while maintaining excellent dimensional stability thanks to the combination of micro- and nanopore. The prepared lightweight HPPI foam also shows excellent high-temperature-resistant mechanical properties. Additionally, the versatility of this strategy has been successfully demonstrated in other thermoplastic polyimide systems. This work not only provides a new method for preparing hierarchically porous materials, but also provides more possibilities for further expanding the application areas of special engineering polymers, for example, maintenance-free components for human deep space exploration and high-temperature-resistant fall buffers.

The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. Here, we present PoseidonQ (an acronym for Personal Optimization Software for Efficient Implementation and Derivation of Online QSAR), a user-friendly software solution designed to simplify the derivation of the QSAR model for drug design and discovery. PoseidonQ incorporates 22 machine learning algorithms, 17 types of molecular fingerprints, and 208 RDKit molecular descriptors and enables the quick derivation of both regression and classification models along with a calculated and easily interpretable applicability domain. Importantly, the platform is automatically linked to the latest version of the ChEMBL database, thus providing streamlined access to large amounts of curated bioactivity data. Importantly, the user is also given the option of gathering high-quality experimental data based on customizable filtering settings. Noteworthy, PoseidonQ facilitates the deployment of trained QSAR models as web-based applications through seamless integration with Streamlit Cloud and GitHub, empowering users to share, refine, and integrate models effortlessly. Interestingly, the translation of QSAR models into web-based applications makes them free accessible, portable, and ready for screening large volumes of new data without limits. By unifying data preparation, model generation, and deployment into an intuitive workflow, PoseidonQ makes advanced QSAR modeling for drug design and discovery accessible to a wide audience of researchers irrespective of their skill levels. PoseidonQ bridges the gap between complex machine learning techniques and practical drug discovery applications, enhancing the efficiency, collaboration, and adoption of QSAR approaches in modern drug discovery programs. PoseidonQ is available for Windows and Linux (ubuntu 22.04 distro) operating systems and can be downloaded for free at https://github.com/Muzatheking12/PoseidonQ.

The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic energies for molecules. In this work, we report the implementation and performance of ADAPT-VQE with our recently developed sparse wave function circuit solver (SWCS) in terms of accuracy and efficiency for molecular systems with up to 52 spin orbitals. The SWCS can be tuned to balance computational cost and accuracy, which extends the application of ADAPT-VQE for molecular electronic structure calculations to larger basis sets and a larger number of qubits. Using this tunable feature of the SWCS, we propose an alternative optimization procedure for ADAPT-VQE to reduce the computational cost of the optimization. By preoptimizing a quantum simulation with a parametrized ansatz generated with ADAPT-VQE/SWCS, we aim to utilize the power of classical high-performance computing in order to minimize the work required on noisy intermediate-scale quantum hardware, which offers a promising path toward demonstrating quantum advantage for chemical applications.

Exercise has been shown to promote wound healing, including tendon repair. Myokines released from the exercised muscles are believed to play a significant role in this process. In our previous study, we used an in vitro coculture and loading model to demonstrate that 2% static loading of myoblasts increased the migration and proliferation of cocultured tenocytes─two crucial aspects of wound healing. IGF-1, released from myoblasts in response to 2% static loading, was identified as a contributor to the increased proliferation. However, the factors responsible for the enhanced migration remained unknown. In the current study, we subjected myoblasts in single culture conditions to 2, 5, and 10% static loading and performed proteomic analysis of the cell supernatants. Gene Ontology (GO) analysis revealed that 2% static loading induced the secretion of NBL1, C5, and EFEMP1, which is associated with cell migration and motility. Further investigation by adding exogenous recombinant proteins to human tenocytes showed that NBL1 increased tenocyte migration but not proliferation. This effect was not observed with treatments using C5 and EFEMP1.