Rechargeable Na/Cl2 and Li/Cl2 batteries.

Lithium-ion batteries (LIBs) are widely used in applications ranging from electric vehicles to wearable devices. Before the invention of secondary LIBs, the primary lithium-thionyl chloride (Li-SOCl2) battery was developed in the 1970s using SOCl2 as the catholyte, lithium metal as the anode and amorphous carbon as the cathode1-7. This battery discharges by lithium oxidation and catholyte reduction to sulfur, sulfur dioxide and lithium chloride, is well known for its high energy density and is widely used in real-world applications; however, it has not been made rechargeable since its invention8-13. Here we show that with a highly microporous carbon positive electrode, a starting electrolyte composed of aluminium chloride in SOCl2 with fluoride-based additives, and either sodium or lithium as the negative electrode, we can produce a rechargeable Na/Cl2 or Li/Cl2 battery operating via redox between mainly Cl2/Cl- in the micropores of carbon and Na/Na+ or Li/Li+ redox on the sodium or lithium metal. The reversible Cl2/NaCl or Cl2/LiCl redox in the microporous carbon affords rechargeability at the positive electrode side and the thin alkali-fluoride-doped alkali-chloride solid electrolyte interface stabilizes the negative electrode, both are critical to secondary alkali-metal/Cl2 batteries.

A new variant of the colistin resistance gene MCR-1 with co-resistance to ß-lactam antibiotics reveals a potential novel antimicrobial peptide.

The emerging and global spread of a novel plasmid-mediated colistin resistance gene, mcr-1, threatens human health. Expression of the MCR-1 protein affects bacterial fitness and this cost correlates with lipid A perturbation. However, the exact molecular mechanism remains unclear. Here, we identified the MCR-1 M6 variant carrying two-point mutations that conferred co-resistance to ß-lactam antibiotics. Compared to wild-type (WT) MCR-1, this variant caused severe disturbance in lipid A, resulting in up-regulation of L, D-transpeptidases (LDTs) pathway, which explains co-resistance to ß-lactams. Moreover, we show that a lipid A loading pocket is localized at the linker domain of MCR-1 where these 2 mutations are located. This pocket governs colistin resistance and bacterial membrane permeability, and the mutated pocket in M6 enhances the binding affinity towards lipid A. Based on this new information, we also designed synthetic peptides derived from M6 that exhibit broad-spectrum antimicrobial activity, exposing a potential vulnerability that could be exploited for future antimicrobial drug design.

Shedding light on rechargeable Na/Cl2 battery.

Advancing new ideas of rechargeable batteries represents an important path to meeting the ever-increasing energy storage needs. Recently, we showed rechargeable sodium/chlorine (Na/Cl2) (or lithium/chlorine Li/Cl2) batteries that used a Na (or Li) metal negative electrode, a microporous amorphous carbon nanosphere (aCNS) positive electrode, and an electrolyte containing dissolved aluminum chloride and fluoride additives in thionyl chloride [G. Zhu et al., Nature 596, 525-530 (2021) and G. Zhu et al., J. Am. Chem. Soc. 144, 22505-22513 (2022)]. The main battery redox reaction involved conversion between NaCl and Cl2 trapped in the carbon positive electrode, delivering a cyclable capacity of up to 1,200 mAh g-1 (based on positive electrode mass) at a ~3.5 V discharge voltage [G. Zhu et al., Nature 596, 525-530 (2021) and G. Zhu et al., J. Am. Chem. Soc. 144, 22505-22513 (2022)]. Here, we identified by X-ray photoelectron spectroscopy (XPS) that upon charging a Na/Cl2 battery, chlorination of carbon in the positive electrode occurred to form carbon-chlorine (C-Cl) accompanied by molecular Cl2 infiltrating the porous aCNS, consistent with Cl2 probed by mass spectrometry. Synchrotron X-ray diffraction observed the development of graphitic ordering in the initially amorphous aCNS under battery charging when the carbon matrix was oxidized/chlorinated and infiltrated with Cl2. The C-Cl, Cl2 species and graphitic ordering were reversible upon discharge, accompanied by NaCl formation. The results revealed redox conversion between NaCl and Cl2, reversible graphitic ordering/amorphourization of carbon through battery charge/discharge, and probed trapped Cl2 in porous carbon by XPS.

High-precision tumor resection down to few-cell level guided by NIR-IIb molecular fluorescence imaging.

In vivo fluorescence/luminescence imaging in the near-infrared-IIb (NIR-IIb, 1,500 to 1,700 nm) window under <1,000 nm excitation can afford subcentimeter imaging depth without any tissue autofluorescence, promising high-precision intraoperative navigation in the clinic. Here, we developed a compact imager for concurrent visible photographic and NIR-II (1,000 to 3,000 nm) fluorescence imaging for preclinical image-guided surgery. Biocompatible erbium-based rare-earth nanoparticles (ErNPs) with bright down-conversion luminescence in the NIR-IIb window were conjugated to TRC105 antibody for molecular imaging of CD105 angiogenesis markers in 4T1 murine breast tumors. Under a ∼940 ± 38 nm light-emitting diode (LED) excitation, NIR-IIb imaging of 1,500- to 1,700-nm emission afforded noninvasive tumor­to­normal tissue (T/NT) signal ratios of ∼40 before surgery and an ultrahigh intraoperative tumor-to-muscle (T/M) ratio of ∼300, resolving tumor margin unambiguously without interfering background signal from surrounding healthy tissues. High-resolution imaging resolved small numbers of residual cancer cells during surgery, allowing thorough and nonexcessive tumor removal at the few-cell level. NIR-IIb molecular imaging afforded 10-times-higher and 100-times-higher T/NT and T/M ratios, respectively, than imaging with IRDye800CW-TRC105 in the ∼900- to 1,300-nm range. The vastly improved resolution of tumor margin and diminished background open a paradigm of molecular imaging-guided surgery.

Global trends in PANoptosis research: bibliometrics and knowledge graph analysis.

PANoptosis has recently been discovered as a new type of cell death. PANoptosis mainly refers to the significant interaction among the three programmed cell death pathways of apoptosis, necroptosis, and pyroptosis. Despite this, only a few studies have examined the systematic literature in this area. By analyzing the bibliometric data for PANoptosis, we can visualize the current hotspots and predicted trends in research. This study analyzed bibliometric indicators using the Histcite Pro 2.0 tool, which searches the Web of Science for PANoptosis literature published between 2016 and 2022. A bibliometric analysis was performed using Histcite Pro 2.0, while research trends and hotspots were visualized using VOSviewer, CiteSpace and BioBERT. The output of related literature was low in the four years from the first presentation of PANoptosis in 2016 to 2020. The volume of relevant literature grew exponentially between 2020 and 2022. The United States and China play a leading role in this field. Although China started late, its research in this field is developing rapidly. As research progressed, more focus was placed on the relationship between PANoptosis and pyroptosis, as well as apoptosis and necrosis. Now is a rapid development stage of PANoptosis research. Most of the research focuses on the cellular level, and the focus is more on the treatment of tumor-related diseases. The current focus of this area is PANoptosis mechanisms in cancer and inflammation. It can be seen from the burst analysis of keywords that caspase1 and host defense have consistently been research hotspots in the field of PANoptosis, while the frequency of NLRC4, causes of autoinflammation, recognition, NLRP3, and Gasdermin D has gradually increased, all of which have become research hotspots in recent years. Finally, we used the BioBERT biomedical language model to mine the most documented genes and diseases in the PANoptosis field articles, pointing out the direction for subsequent research steps. According to a bibliometric analysis, researchers have shown an increased interest in PANoptosis over the past few years. Researchers initially focused on the molecular mechanism of PANoptosis and pyroptosis, apoptosis, and necroptosis. The role of PANoptosis in diseases and conditions such as inflammation and tumors is one of the current research hotspots in this area. The focus is more on treating inflammation-related diseases, which will become the key development direction of future research.

Recent advances of m6A methylation in skeletal system disease.

Skeletal system disease (SSD) is defined as a class of chronic disorders of skeletal system with poor prognosis and causes heavy economic burden. m6A, methylation at the N6 position of adenosine in RNA, is a reversible and dynamic modification in posttranscriptional mRNA. Evidences suggest that m6A modifications play a crucial role in regulating biological processes of all kinds of diseases, such as malignancy. Recently studies have revealed that as the most abundant epigentic modification, m6A is involved in the progression of SSD. However, the function of m6A modification in SSD is not fully illustrated. Therefore, make clear the relationship between m6A modification and SSD pathogenesis might provide novel sights for prevention and targeted treatment of SSD. This article will summarize the recent advances of m6A regulation in the biological processes of SSD, including osteoporosis, osteosarcoma, rheumatoid arthritis and osteoarthritis, and discuss the potential clinical value, research challenge and future prospect of m6A modification in SSD.

Reconfigurable multi-channel microwave photonic receiver for a multi-band signal based on cascaded microring resonator banks.

What we believe to be a novel reconfigurable multi-channel microwave photonic (MWP) receiver for multi-band RF signal is demonstrated for the first time, to the best of our knowledge. A reconfigurable MWP signal processing chip based on two cascaded microring filter banks is employed in the proposed receiver, which slices the multi-band RF input into several narrow band signals and selects optical frequency comb lines for frequency converting of each channel. Due to the significant reconfigurability of the signal processing chip, the proposed receiver can flexibly choose the output frequency band of each channel, and thus different frequency components of the multi-band RF input can be down converted to the intermediate frequency (IF) band for receiving or converted to other frequency band for forwarding. A multi-band RF signal composed of a linear frequency modulation (LFM) signal with 2 GHz bandwidth and a quad-phase shift keyed (QPSK) signal with 100 Mbit/s rate is experimentally received and reconstructed by the proposed receiver, where the reconstructed LFM component exhibits a signal to noise ratio (SNR) of 10.2 dB, and the reconstructed QPSK component reaches a high SNR of 26.1 dB and a great error vector magnitude (EVM) of 11.73%. On the other hand, the QPSK component of the multi-band RF signal centered at 13.5 GHz is successfully converted to 3.1 GHz.

Comparing the Catalytic Effect of Metals for Energetic Materials: Machine Learning Prediction of Adsorption Energies on Metals.

Energetic materials (EMs) and metals are the important components of solid propellants, and a strong catalysis of metals on EMs could further enhance the combustion performance of solid propellants. Accordingly, the study on the adsorption of EMs such as octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), and ammonium dinitramide (ADN) on metals (Ti, Zr, Fe, Ni, Cu, and Al) was carried out by density functional theory (DFT) to reveal the catalytic effect of metals. The deep dissociation of EMs on Ti and Zr represents a stronger interaction and corresponds to the rapid thermal decomposition behavior of the EMs/metal composite in the experiment. It is expected that DFT calculation can be selected instead of experiments to compare the catalytic effect of metals and preliminarily screen out potential high-performance metals. Based on the data set of the calculated adsorption energy, further machine learning (ML) was used to predict the adsorption energy of EMs on metals for a convenient comparison of the catalytic effect of metals, since a quite high adsorption energy value represents a more thorough dissociation. The kernel ridge regression (KRR) method shows the best performance on predicting adsorption energy and helps to choose the metals for efficiently catalyzing ammonium nitrate (AN) and hexanitrohexaazaisowurtzitane (CL-20). Such adsorption computation and ML not only reveal the decomposition mechanism of EMs on metals but also provide a simple underlying method to predict the catalytic effect of metals.

Qualitative and Quantitative Analysis of Three-Dimensional Fluorescence Spectra by Improved Parallel Factor Analysis with Internal Standard Sample Embedding.

The strategy of parallel factor analysis, combined with the internal standard method, has been increasingly applied to the qualitative and quantitative analysis of three-dimensional fluorescence spectra of unknown mixed fluorophores. Nevertheless, the disparity in the number of fluorophores included in the internal standard sample set and the number included in test samples may impact the qualitative and quantitative outcomes of parallel factor analysis. In this work, we systematically established the framework of the parallel factor analysis with internal standard sample embedding (ISSE-PARAFAC) strategy. We applied this framework to six datasets representing two scenarios and a real dataset and conducted a detailed discussion on the effects of the disparity between the number of fluorophores in the internal standard sample set and the number in the test set on both qualitative and quantitative results. Additionally, we introduced an enhancement to PARAFAC by aggregating fluorophores with similar emission wavelengths, corresponding to the peaks of emission loadings (spectra) obtained from PARAFAC, as a single fluorophore. This aggregation aimed to mitigate the strong correlation between similar fluorophores. The results imply that the presence of irrelevant fluorophores in the internal standard sample set, whether increased or decreased, does not significantly affect the qualitative and quantitative analysis of target fluorophores in the test set. Moreover, we demonstrated that the improved parallel factor analysis with internal standard sample embedding not only fully decomposes the uncorrelated mixed fluorophores for qualitative analysis but also allows the established linear concentration model for fluorescent components to predict the corresponding fluorophore concentration of test samples, enabling quantitative analysis at the ppm level (mg/L).

Chemical Potentials and the One-Electron Hamiltonian of the Second-Order Perturbation Theory from the Functional Derivative Approach.

We develop a functional derivative approach to calculate the chemical potentials of second-order perturbation theory (MP2). In the functional derivative approach, the correlation part of the MP2 chemical potential, which is the derivative of the MP2 correlation energy with respect to the occupation number of frontier orbitals, is obtained from the chain rule via the noninteracting Green's function. First, the MP2 correlation energy is expressed in terms of the noninteracting Green's function, and its functional derivative to the noninteracting Green's function is the second-order self-energy. Then, the derivative of the noninteracting Green's function to the occupation number is obtained by including the orbital relaxation effect. We show that the MP2 chemical potentials obtained from the functional derivative approach agree with that obtained from the finite difference approach. The one-electron Hamiltonian, defined as the derivative of the MP2 energy with respect to the one particle density matrix, is also derived using the functional derivative approach, which can be used in the self-consistent calculations of MP2 and double-hybrid density functionals. The developed functional derivative approach is promising for calculating the chemical potentials and the one-electron Hamiltonian of approximate functionals and many-body perturbation approaches dependent explicitly on the noninteracting Green's function.

[A unicenter real-world study of the correlation factors for complete clinical response in idiopathic inflammatory myopathies].

OBJECTIVE: To investigate the correlation factors of complete clinical response in idiopathic inflammatory myopathies (IIMs) patients receiving conventional treatment. METHODS: Patients diagnosed with IIMs hospitalized in Peking University People's Hospital from January 2000 to June 2023 were included. The correlation factors of complete clinical response to conventional treatment were identified by analyzing the clinical characteristics, laboratory features, peripheral blood lymphocytes, immunological indicators, and therapeutic drugs. RESULTS: Among the 635 patients included, 518 patients finished the follow-up, with an average time of 36.8 months. The total complete clinical response rate of IIMs was 50.0% (259/518). The complete clinical response rate of dermatomyositis (DM), anti-synthetase syndrome (ASS) and immune-mediated necrotizing myopathy (IMNM) were 53.5%, 48.9% and 39.0%, respectively. Fever (P=0.002) and rapid progressive interstitial lung disease (RP-ILD) (P=0.014) were observed much more frequently in non-complete clinical response group than in complete clinical response group. The aspartate transaminase (AST), lactate dehydrogenase (LDH), D-dimer, erythrocyte sedimentation rate (ESR), C-reaction protein (CRP) and serum ferritin were significantly higher in non-complete clinical response group as compared with complete clinical response group. As for the treatment, the percentage of glucocorticoid received and intravenous immunoglobin (IVIG) were significantly higher in non-complete clinical response group than in complete clinical response group. Risk factor analysis showed that IMNM subtype (P=0.007), interstitial lung disease (ILD) (P=0.001), eleva-ted AST (P=0.012), elevated serum ferritin (P=0.016) and decreased count of CD4+T cells in peripheral blood (P=0.004) might be the risk factors for IIMs non-complete clinical response. CONCLUSION: The total complete clinical response rate of IIMs is low, especially for IMNM subtype. More effective intervention should be administered to patients with ILD, elevated AST, elevated serum ferritin or decreased count of CD4+T cells at disease onset.

Influence of ambient temperature on the CO2 emitted of light-duty vehicle.

Because of global warming, people have paid more attention to greenhouse gas emitted by vehicles. To quantify the impact of temperature on vehicle CO2 emissions, this study was conducted using the world light vehicle test cycle on two light-duty E10 gasoline vehicles at ambient temperatures of -10, 0, 23, and 40℃, and found that CO2 emission factors of Vehicle 1 in the low-speed phase were 22.07% and 20.22% higher than those of Vehicle 2 at cold start and hot start under -10℃. The reason was vehicle 1 had a larger displacement and more friction pairs than vehicle 2. There was the highest CO2 emission at the low-speed phase due to low average speed, frequent acceleration, and deceleration. The CO2 temperature factor and the ambient temperature had a strong linear correlation (R2 = 0.99). According to CO2 temperature factors and their relationships, CO2 emission factors of other ambient temperatures could be calculated when the CO2 emission factor of 23℃ was obtained, and the method also could be used to obtain the CO2 temperature factors of different vehicles. To separate the effect of load setting and temperature variation on CO2 emission quantitatively, a method was proposed. And results showed that the load setting was dominant for the CO2 emission variation. Compared with 23℃, the CO2 emission for vehicle 1 caused by load setting variation were 62.83 and 47.42 g/km, respectively at -10 and 0℃, while those for vehicle 2 were 45.01 and 35.63 g/km, respectively.

Prediction of Antibiotic Resistance Evolution by Growth Measurement of All Proximal Mutants of Beta-Lactamase.

The antibiotic resistance crisis continues to threaten human health. Better predictions of the evolution of antibiotic resistance genes could contribute to the design of more sustainable treatment strategies. However, comprehensive prediction of antibiotic resistance gene evolution via laboratory approaches remains challenging. By combining site-specific integration and high-throughput sequencing, we quantified relative growth under the respective selection of cefotaxime or ceftazidime selection in ∼23,000 Escherichia coli MG1655 strains that each carried a unique, single-copy variant of the extended-spectrum ß-lactamase gene blaCTX-M-14 at the chromosomal att HK022 site. Significant synergistic pleiotropy was observed within four subgenic regions, suggesting key regions for the evolution of resistance to both antibiotics. Moreover, we propose PEARP and PEARR, two deep-learning models with strong clinical correlations, for the prospective and retrospective prediction of blaCTX-M-14 evolution, respectively. Single to quintuple mutations of blaCTX-M-14 predicted to confer resistance by PEARP were significantly enriched among the clinical isolates harboring blaCTX-M-14 variants, and the PEARR scores matched the minimal inhibitory concentrations obtained for the 31 intermediates in all hypothetical trajectories. Altogether, we conclude that the measurement of local fitness landscape enables prediction of the evolutionary trajectories of antibiotic resistance genes, which could be useful for a broad range of clinical applications, from resistance prediction to designing novel treatment strategies.

Single-pixel reconstructive mid-infrared micro-spectrometer.

Miniaturized spectrometers in the mid-infrared (MIR) are critical in developing next-generation portable electronics for advanced sensing and analysis. The bulky gratings or detector/filter arrays in conventional micro-spectrometers set a physical limitation to their miniaturization. In this work, we demonstrate a single-pixel MIR micro-spectrometer that reconstructs the sample transmission spectrum by a spectrally dispersed light source instead of spatially grated light beams. The spectrally tunable MIR light source is realized based on the thermal emissivity engineered via the metal-insulator phase transition of vanadium dioxide (VO2). We validate the performance by showing that the transmission spectrum of a magnesium fluoride (MgF2) sample can be computationally reconstructed from sensor responses at varied light source temperatures. With potentially minimum footprint due to the array-free design, our work opens the possibility where compact MIR spectrometers are integrated into portable electronic systems for versatile applications.

Comparison of heterologous prime-boost immunization strategies with DNA and recombinant vaccinia virus co-expressing GP3 and GP5 of European type porcine reproductive and respiratory syndrome virus in pigs.

Vaccination is principally used to control and treat porcine reproductive and respiratory syndrome virus (PRRSV) infection. This study investigated immunogenicity and protective efficacy of heterologous prime-boost regimens in pigs, including recombinant DNA and vaccinia virus vectors coexpressing PRRSV European genotype (EU) isolate GP3 and GP5: group A, pVAX1-EU-GP3-GP5 prime and rddVTT-EU-GP3-GP5 boost; group B, rddVTT-EU-GP3-GP5 prime and pVAX1-EU-GP3-GP5 boost; group C, empty vector pVAX1; group D, E3L gene-deleted vaccinia virus E3L- VTT. Vaccine efficacy was tested in an EU-type PRRSV (Lelystad virus strain) challenge pig model based on evaluating PRRSV-specific antibody responses, neutralizing antibodies, cytokines, T lymphocyte proliferation, CD4+ and CD8+ T lymphocytes, clinical symptoms, viremia and tissue virus loads. Plasmid DNA was delivered as chitosan-DNA nanoparticles, and Quil A (Quillaja) was used to increase vaccine efficiency. All piglets were boosted 21 days post the initial inoculation (dpi) and then challenged 14 days later. At 14, 21, 28 and 35 dpi, groups A and B developed significantly higher PRRSV-specific antibody responses compared with control groups C and D. Two weeks after the boost, significant differences in neutralizing antibody and IFN-γ levels were observed between groups A, C, D and B. At 49 dpi, groups A and B had markedly increased peripheral blood CD3+CD4+ T cell levels. Following virus challenge, group A showed viremia, but organ virus loads were lower than those in other groups. Thus, a heterologous prime-boost vaccine regimen (rddVTT-EU-GP3-GP5 prime, pVAX1-EU-GP3-GP5 boost) can improve humoral- and cell-mediated immune responses to provide resistance to EU-type PRRSV infection in vivo.

CINS: Cell Interaction Network inference from Single cell expression data.

Studies comparing single cell RNA-Seq (scRNA-Seq) data between conditions mainly focus on differences in the proportion of cell types or on differentially expressed genes. In many cases these differences are driven by changes in cell interactions which are challenging to infer without spatial information. To determine cell-cell interactions that differ between conditions we developed the Cell Interaction Network Inference (CINS) pipeline. CINS combines Bayesian network analysis with regression-based modeling to identify differential cell type interactions and the proteins that underlie them. We tested CINS on a disease case control and on an aging mouse dataset. In both cases CINS correctly identifies cell type interactions and the ligands involved in these interactions improving on prior methods suggested for cell interaction predictions. We performed additional mouse aging scRNA-Seq experiments which further support the interactions identified by CINS.

Reconstructing COVID-19 incidences from positive RT-PCR tests by deconvolution.

BACKGROUND: The emergency of new COVID-19 variants over the past three years posed a serious challenge to the public health. Cities in China implemented mass daily RT-PCR tests by pooling strategies. However, a random delay exists between an infection and its first positive RT-PCR test. It is valuable for disease control to know the delay pattern and daily infection incidences reconstructed from RT-PCR test observations. METHODS: We formulated the convolution model between daily incidences and positive RT-PCR test counts as a linear inverse problem with positivity restrictions. Consequently, the Richard-Lucy deconvolution algorithm was used to reconstruct COVID-19 incidences from daily PCR tests. A real-time deconvolution was further developed based on the same mathematical principle. The method was applied to an Omicron epidemic data set of a bar outbreak in Beijing and another in Wuxi in June 2022. We estimated the delay function by maximizing likelihood via an E-M algorithm. RESULTS: The delay function of the bar-outbreak in 2022 differs from that reported in 2020. Its mode was shortened to 4 days by one day. A 95% confidence interval of the mean delay is [4.43,5.55] as evaluated by bootstrap. In addition, the deconvolved infection incidences successfully detected two associated infection events after the bar was closed. The application of the real-time deconvolution to the Wuxi data identified all explosive incidence increases. The results revealed the progression of the two COVID-19 outbreaks and provided new insights for prevention and control strategies, especially for the role of mass daily RT-PCR testing. CONCLUSIONS: The proposed deconvolution method is generally applicable to other infectious diseases if the delay model can be assumed to be approximately valid. To ensure a fair reconstruction of daily infection incidences, the delay function should be estimated in a similar context in terms of virus variant and test protocol. Both the delay estimate from the E-M algorithm and the incidences resulted from deconvolution are valuable for epidemic prevention and control. The real-time feedback is particularly useful during the epidemic's acute phase because it can help the local disease control authorities modify the control measures more promptly and precisely.

Linear Scaling Calculations of Excitation Energies with Active-Space Particle-Particle Random-Phase Approximation.

We developed an efficient active-space particle-particle random-phase approximation (ppRPA) approach to calculate accurate charge-neutral excitation energies of molecular systems. The active-space ppRPA approach constrains both indexes in particle and hole pairs in the ppRPA matrix, which only selects frontier orbitals with dominant contributions to low-lying excitation energies. It employs the truncation in both orbital indexes in the particle-particle and the hole-hole spaces. The resulting matrix, whose eigenvalues are excitation energies, has a dimension that is independent of the size of the systems. The computational effort for the excitation energy calculation, therefore, scales linearly with system size and is negligible compared with the ground-state calculation of the (N - 2)-electron system, where N is the electron number of the molecule. With the active space consisting of 30 occupied and 30 virtual orbitals, the active-space ppRPA approach predicts the excitation energies of valence, charge-transfer, Rydberg, double, and diradical excitations with the mean absolute errors (MAEs) smaller than 0.03 eV compared with the full-space ppRPA results. As a side product, we also applied the active-space ppRPA approach in the renormalized singles (RS) T-matrix approach. Combining the non-interacting pair approximation that approximates the contribution to the self-energy outside the active space, the active-space GRSTRS@PBE approach predicts accurate absolute and relative core-level binding energies with the MAEs around 1.58 and 0.3 eV, respectively. The developed linear scaling calculation of excitation energies is promising for applications to large and complex systems.

Knowledge, attitudes and practices of patients with chronic pharyngitis toward laryngopharyngeal reflux in Suzhou, China.

BACKGROUND: This study aimed to investigate the knowledge, attitudes and practices (KAP) of patients with chronic pharyngitis in Suzhou, China toward laryngopharyngeal reflux (LPR). METHODS: This cross-sectional study was conducted in patients with chronic pharyngitis in Suzhou, China at the otolaryngology outpatient clinic of the First Affiliated Hospital of Soochow University between November, 2022, and May, 2023. Data was collected through a self-designed online questionnaire encompassing the sociodemographic characteristics and three dimensions of KAP. The questionnaire was administered using SoJump, and data were exported from this platform. Subsequently, statistical analysis, including Structural Equation Modeling, was performed using SPSS 22 software to evaluate the KAP scores. RESULTS: A total of 487 valid questionnaires were collected, with 275 (56.35%) female patients. The mean score of KAP were 4.76 ± 2.93 (possible range: 0-11), 33.10 ± 4.46 (possible range: 8-40), 31.29 ± 6.04 (possible range: 8-40), respectively. Pearson's correlation analysis showed significant positive correlations between knowledge and attitude dimensions (r = 0.413, P < 0.001), knowledge and practice dimensions (r = 0.355, P < 0.001), and attitude and practice dimensions (r = 0.481, P < 0.001). Structural equation modeling revealed that education exhibited positive effect on knowledge (ß = 0.476, P < 0.001) and attitude (ß = 0.600, P < 0.001), and having family history of chronic pharyngitis showed positive effect on knowledge (ß = 0.580, P = 0.047), experienced with reflux symptoms showed positive effect on knowledge (ß = 0.838, P = 0.001) and attitude (ß = 0.631, P = 0.085). Moreover, knowledge showed positive effect on attitude (ß = 0.555, P < 0.001) and practice (ß = 0.351, P < 0.001). Attitude, in turn, showed positive effect on practice (ß = 0.511, P < 0.001). CONCLUSION: Patients with chronic pharyngitis had inadequate knowledge, positive attitudes and suboptimal practices toward LPR. Education, family history of chronic pharyngitis, experienced with reflux symptoms might have effect on their KAP.

A high-performance potassium metal battery using safe ionic liquid electrolyte.

Potassium secondary batteries are contenders of next-generation energy storage devices owing to the much higher abundance of potassium than lithium. However, safety issues and poor cycle life of K metal battery have been key bottlenecks. Here we report an ionic liquid electrolyte comprising 1-ethyl-3-methylimidazolium chloride/AlCl3/KCl/potassium bis(fluorosulfonyl) imide for safe and high-performance batteries. The electrolyte is nonflammable and exhibits a high ionic conductivity of 13.1 mS cm-1 at room temperature. A 3.6-V battery with K anode and Prussian blue/reduced graphene oxide cathode delivers a high energy and power density of 381 and 1,350 W kg-1, respectively. The battery shows an excellent cycling stability over 820 cycles, retaining ∼89% of the original capacity with high Coulombic efficiencies of ∼99.9%. High cyclability is also achieved at elevated temperatures up to 60 °C. Uniquely, robust K, Al, F, and Cl-containing passivating interphases are afforded with this electrolyte, which is key to superior battery cycling performances.