Electrically Detectable Photoinduced Polarization Switching in a Molecular Prussian Blue Analogue.

Light, a nondestructive and remotely controllable external stimulus, effectively triggers a variety of electron-transfer phenomena in metal complexes. One prime example includes using light in molecular cyanide-bridged [FeCo] bimetallic Prussian blue analogues, where it switches the system between the electron-transferred metastable state and the system's ground state. If this process is coupled to a ferroelectric-type phase transition, the generation and disappearance of macroscopic polarization, entirely under light control, become possible. In this research, we successfully executed a nonpolar-to-polar phase transition in a trinuclear cyanide-bridged [Fe2Co] complex crystal via directional electron transfer. Intriguingly, by exposing the crystal to the wavelength of light─785 nm─without any electric field─we can drive this ferroelectric phase transition to completely depolarize the crystal, during which a measurable electric current response can be detected. These discoveries signify an important step toward the realization of fully light-controlled ferroelectric memory devices.

Development of an FeII Complex Exhibiting Intermolecular Proton Shifting Coupled Spin Transition.

In this study, we investigated reversible intermolecular proton shifting (IPS) coupled with spin transition (ST) in a novel FeII complex. The host FeII complex and the guest carboxylic acid anion were connected by intermolecular hydrogen bonds (IHBs). We extended the intramolecular proton transfer coupled ST phenomenon to the intermolecular system. The dynamic phenomenon was confirmed by variable-temperature single-crystal X-ray diffraction, neutron crystallography, and infrared spectroscopy. The mechanism of IPS was further validated using density functional theory calculations. The discovery of IPS-coupled ST in crystalline molecular materials provides good insights into fundamental processes and promotes the design of novel multifunctional materials with tunable properties for various applications, such as optoelectronics, information storage, and molecular devices.

Fully Optical Control of Polarization Current Direction in a Cyanide-Bridged Trinuclear Complex.

As a remote and non-contact stimulus, light offers the potential for manipulating the polarization of ferroelectric materials without physical contact. However, in current research, the non-contact write-read (erase) process lacks direct observation through the stable current as output signal. To address this limitation, we investigated the photoinduced polarization switching capabilities of the cyanide-bridged compound [Fe2Co] using visible light, leading to the achievement of rewritable polarization. By subjecting [Fe2Co] crystals to alternating irradiation with 785 nm and 532 nm light, the polarization changes exhibited a distinct square wave pattern, confirming the reliability of the writing and erasing processes. Initialization involved exposing specific crystal units to 532 nm light for storing "1" or "0" information, while reading was accomplished by scanning the units with 785 nm light, resulting in brief current pulses for "1" states and no current signal for "0" states. This research unveils new possibilities for optical storage systems, paving the way for efficient and rewritable data storage and retrieval technologies, such as the next-generation memories.

Magnetoelectricity Enhanced by Electron Redistribution in a Spin Crossover [FeCo] Complex.

Molecular-based magnetoelectric materials are among the most promising materials for next-generation magnetoelectric memory devices. However, practical application of existing molecular systems has proven difficult largely because the polarization change is far lower than the practical threshold of the ME memory devices. Herein, we successfully obtained an [FeCo] dinuclear complex that exhibits a magnetic field-induced spin crossover process, resulting in a significant polarization change of 0.45 µC cm-2. Mössbauer spectroscopy and theoretical calculations suggest that the asymmetric structural change, coupled with electron redistribution, leads to the observed polarization change. Our approach provides a new strategy toward rationally enhancing the polarization change.

Fluorogenic methodology for visualization of phase separation in chemical biology.

Phase separation is a common biological phenomenon in the liquid environment of organisms. Phase separation has been shown to be a key cause of many existing incurable diseases, such as the protein aggregates formed by phase separation of Alzheimer's Disease, Amyotrophic Lateral Sclerosis, Parkinson's disease, etc. Tracking the occurrence of phase separation in vivo is critical to many disease detection methods and solving many treatment problems. Its physicochemical properties and visual detection methods have flourished in the last few years in chemical biology, among which the fluorogenic toolbox has great application potential compared to the traditional detection methods that cannot visualize the phase separation process intuitively, but just show some parameters indirectly. This paper reviews the mechanism and disease correlation proven in recent years for phase separation and analyzes the detection methods for phase separation, including functional microscope imaging techniques, turbidity monitoring, macromolecule congestion sensing, in silico analysis, etc. It is worth mentioning that the qualitative and quantitative analysis of aggregates formed by phase separation using in vitro parameters has successfully provided basic physical and chemical properties for phase separation aggregates, and is an important cornerstone for researchers to carry forward the past and break through the existing technical shackles to create new in vivo monitoring methods such as fluorescence methodology. Crucially, fluorescence methods for cell microenvironment imaging based on different mechanisms are discussed, such as AIE-based probes, TICT-based probes and FRET-based probes, etc.

Uncertainty Management in Assessment of FMEA Expert Based on Negation Information and Belief Entropy.

The failure mode and effects analysis (FMEA) is a commonly adopted approach in engineering failure analysis, wherein the risk priority number (RPN) is utilized to rank failure modes. However, assessments made by FMEA experts are full of uncertainty. To deal with this issue, we propose a new uncertainty management approach for the assessments given by experts based on negation information and belief entropy in the Dempster-Shafer evidence theory framework. First, the assessments of FMEA experts are modeled as basic probability assignments (BPA) in evidence theory. Next, the negation of BPA is calculated to extract more valuable information from a new perspective of uncertain information. Then, by utilizing the belief entropy, the degree of uncertainty of the negation information is measured to represent the uncertainty of different risk factors in the RPN. Finally, the new RPN value of each failure mode is calculated for the ranking of each FMEA item in risk analysis. The rationality and effectiveness of the proposed method is verified through its application in a risk analysis conducted for an aircraft turbine rotor blade.

A New Reliability Coefficient Using Betting Commitment Evidence Distance in Dempster-Shafer Evidence Theory for Uncertain Information Fusion.

Dempster-Shafer evidence theory is widely used to deal with uncertain information by evidence modeling and evidence reasoning. However, if there is a high contradiction between different pieces of evidence, the Dempster combination rule may give a fusion result that violates the intuitive result. Many methods have been proposed to solve conflict evidence fusion, and it is still an open issue. This paper proposes a new reliability coefficient using betting commitment evidence distance in Dempster-Shafer evidence theory for conflict and uncertain information fusion. The single belief function for belief assignment in the initial frame of discernment is defined. After evidence preprocessing with the proposed reliability coefficient and single belief function, the evidence fusion result can be calculated with the Dempster combination rule. To evaluate the effectiveness of the proposed uncertainty measure, a new method of uncertain information fusion based on the new evidence reliability coefficient is proposed. The experimental results on UCI machine learning data sets show the availability and effectiveness of the new reliability coefficient for uncertain information processing.

Failure Mode and Effects Analysis on the Air System of an Aero Turbofan Engine Using the Gaussian Model and Evidence Theory.

Failure mode and effects analysis (FMEA) is a proactive risk management approach. Risk management under uncertainty with the FMEA method has attracted a lot of attention. The Dempster-Shafer (D-S) evidence theory is a popular approximate reasoning theory for addressing uncertain information and it can be adopted in FMEA for uncertain information processing because of its flexibility and superiority in coping with uncertain and subjective assessments. The assessments coming from FMEA experts may include highly conflicting evidence for information fusion in the framework of D-S evidence theory. Therefore, in this paper, we propose an improved FMEA method based on the Gaussian model and D-S evidence theory to handle the subjective assessments of FMEA experts and apply it to deal with FMEA in the air system of an aero turbofan engine. First, we define three kinds of generalized scaling by Gaussian distribution characteristics to deal with potential highly conflicting evidence in the assessments. Then, we fuse expert assessments with the Dempster combination rule. Finally, we obtain the risk priority number to rank the risk level of the FMEA items. The experimental results show that the method is effective and reasonable in dealing with risk analysis in the air system of an aero turbofan engine.

RPDNet: Automatic Fabric Defect Detection Based on a Convolutional Neural Network and Repeated Pattern Analysis.

On a global scale, the process of automatic defect detection represents a critical stage of quality control in textile industries. In this paper, a semantic segmentation network using a repeated pattern analysis algorithm is proposed for pixel-level detection of fabric defects, which is termed RPDNet (repeated pattern defect network). Specifically, we utilize a repeated pattern detector based on convolutional neural network (CNN) to detect periodic patterns in fabric images. Through the acquired repeated pattern information and proper guidance of the network in a high-level semantic space, the ability to understand periodic feature knowledge and emphasize potential defect areas is realized. Concurrently, we propose a semi-supervised learning scheme to inject the periodic knowledge into the model separately, which enables the model to function independently from further pre-calculation during detection, so there is no additional network capacity required and no loss in detection speed caused. In addition, the model integrates two advanced architectures of DeeplabV3+ and GhostNet to effectively implement lightweight fabric defect detection. The comparative experiments on repeated pattern fabric images highlights the potential of the algorithm to determine competitive detection results without incurring further computational cost.

High-Sensitivity Flexible Piezoresistive Pressure Sensor Using PDMS/MWNTS Nanocomposite Membrane Reinforced with Isopropanol for Pulse Detection.

Flexible pressure sensors with high sensitivity and good linearity are in high demand to meet the long-term and accurate detection requirements for pulse detection. In this study, we propose a composite membrane pressure sensor using polydimethylsiloxane (PDMS) and multiwalled carbon nanotubes (MWNTS) reinforced with isopropanol prepared by solution blending and a self-made 3D-printed mold. The device doped with isopropanol had a higher sensitivity and linearity owning to the construction of additional conductive paths. The optimal conditions for realizing a high-performance pressure sensor are a multiwalled carbon nanotube mass ratio of 7% and a composite membrane thickness of 490 µm. The membrane achieves a high linear sensitivity of -57.07 kΩ∙kPa-1 and a linear fitting correlation coefficient of 98.78% in the 0.13~5.2 kPa pressure range corresponding to pulse detection. Clearly, this device has great potential for application in pulse detection.

Photoinduced Persistent Polarization Change in a Spin Transition Crystal.

Using light as a local heat source to induce a temporary pyroelectric current is widely recognized as an effective way to control the polarization of crystalline materials. In contrast, harnessing light directly to modulate the polarization of a crystal via excitation of the electronic bands remains less explored. In this study, we report an FeII spin crossover crystal that exhibits photoinduced macroscopic polarization change upon excitation by green light. When the excited crystal relaxes to the ground state, the corresponding pyroelectric current can be detected. An analysis of the structures, magnetic properties and the Mössbauer and infrared spectra of the complex, supported by calculations, revealed that the polarization change is dictated by the directional relative movement of ions during the spin transition process. The spin transition and polarization change occur simultaneously in response to light stimulus, which demonstrates the enormous potential of polar spin crossover systems in the field of optoelectronic materials.

Comprehensive identification and isolation policies have effectively suppressed the spread of COVID-19.

The outbreak of COVID-19 has caused severe life and economic damage worldwide. Since the absence of medical resources or targeted therapeutics, systemic containment policies have been prioritized but some critics query what extent can they mitigate this pandemic. We construct a fine-grained transmission dynamics model to forecast the crucial information of public concern, therein using dynamical coefficients to quantify the impact of the implement schedule and intensity of the containment policies on the spread of epidemic. Statistical evidences show the comprehensive identification and quarantine policies eminently contributed to reduce casualties during the phase of a dramatic increase in diagnosed cases in Wuhan and postponing or weakening such policies would undoubtedly exacerbate the epidemic. Hence we suggest that governments should swiftly execute the forceful public health interventions in the initial stage until the pandemic is blocked.

Glt25d2 Knockout Directly Increases CD25+CD69- but Decreases CD25-CD69+ Subset Proliferation and is Involved in Concanavalin-Induced Hepatitis.

BACKGROUND/AIMS: The elaborate structure of the extracellular matrix (ECM) and the appropriate surface glycoforms upon it are indispensable to CD4+ T cell regulation. METHODS: To explore the effects of Glcα1,2Galß1 glycosylation mediated by GLT25D2 (Colgalt2) for CD4+ T cell regulation, we prepared C57BL/6J Glt25d2-/- mice. In the induction of hepatitis, after concanavalin A (Con A) challenge for 6, 12, and 24 h, more extensive parenchymal injury was noted in Glt25d2-/- mice than in wild-type (WT) mice at 12 h. Immunohistochemistry and laser scanning confocal microscopy were used to detect GLT25D2 expression, and subsets of CD4+T cells was analyzed by flow cytometry. A total of 26 cytokines in serum samples were determined using Luminex technology. RESULTS: The trend in liver injury score variation was consistent with serum alanine aminotransferase and aspartate aminotransferase levels. The levels of interleukin 4 (IL-4), IL-1ß, IL-9, and several chemokines such as macrophage inflammatory protein-2, eotaxin, and growth-related oncogene α were significantly increased in Glt25d2-/- mice compared with WT mice after Con A challenge. A further phenotype analysis of primary Glt25d2-/- CD4+ T cells showed that Glt25d2 knockout increased the frequency of the CD25+CD69- subset but decreased the frequency of the CD25-CD69+ subset after Con A challenge for 6, 12, and 24 h compared with those of WT CD4+ T cells. Activation-induced apoptosis was also significantly increased in Glt25d2-/- CD4+ T cells after Con A challenge compared with WT CD4+ T cells. Lectin microarray hybridization showed that Glt25d2 knockout increased the binding activity of Narcissus pseudonarcissus lectin to CD4+ T cells but Amaranthus caudatus lectin-binding activity was lost during Con A challenge. CONCLUSION: The present results suggest that collagen glycosylation mediated by GLT25D2 may regulate a subset of CD4+ T cells and be involved in the pathogenesis of Con A-induced hepatitis.

NRhFluors: Quantitative Revealing the Interaction between Protein Homeostasis and Mitochondria Dysfunction via Fluorescence Lifetime Imaging.

Degenerative diseases are closely related to the changes of protein conformation beyond the steady state. The development of feasible tools for quantitative detection of changes in the cellular environment is crucial for investigating the process of protein conformational variations. Here, we have developed a near-infrared AIE probe based on the rhodamine fluorophore, which exhibits dual responses of fluorescence intensity and lifetime to local viscosity changes. Notably, computational analysis reveals that NRhFluors fluorescence activation is due to inhibition of the RACI mechanism in viscous environment. In the chemical regulation of rhodamine fluorophores, we found that variations of electron density distribution can effectively regulate CI states and achieve fluorescence sensitivity of NRhFluors. In addition, combined with the AggTag method, the lifetime of probe A9-Halo exhibits a positive correlation with viscosity changes. This analytical capacity allows us to quantitatively monitor protein conformational changes using fluorescence lifetime imaging (FLIM) and demonstrate that mitochondrial dysfunction leads to reduced protein expression in HEK293 cells. In summary, this work developed a set of near-infrared AIE probes activated by the RACI mechanism, which can quantitatively detect cell viscosity and protein aggregation formation, providing a versatile tool for exploring disease-related biological processes and therapeutic approaches.

Effects of dietary phytosterols or phytosterol esters supplementation on growth performance, biochemical blood indices and intestinal flora of C57BL/6 mice.

This study was conducted to evaluate the effects of phytosterols (PS) and phytosterol esters (PSE) on C57BL/6 mice. Three groups of 34 six-week-old C57BL/6 mice of specific pathogen free (SPF) grade, with an average initial body weight (IBW) of 17.7g, were fed for 24 days either natural-ingredient diets without supplements or diets supplemented with 89 mg/kg PS or diets supplemented with 400 mg/kg PSE. Growth performance, blood biochemistry, liver and colon morphology as well as intestinal flora status were evaluated. Both PS and PSE exhibited growth promotion and feed digestibility in mice. In blood biochemistry, the addition of both PS and PSE to the diet resulted in a significant decrease in Total Cholesterol (TC) and Triglyceride (TG) levels and an increase in Superoxide Dismutase (SOD) activity. No significant changes in liver and intestinal morphology were observed. Both increased the level of Akkermansia in the intestinal tract of mice. There was no significant difference between the effects of PS and PSE. It was concluded that dietary PS and PSE supplementation could improve growth performance, immune performance and gut microbiome structure in mice, providing insights into its application as a potential feed additive in animals production.

Photo-induced valence tautomerism and polarization switching in mononuclear cobalt complexes with an enantiopure chiral ligand.

Light-induced polarization switchable molecular materials have attracted attention for decades owing to their potential remote manipulation and ultrafast responsiveness. Here we report a valence tautomeric (VT) complex with an enantiopure chiral ligand. By a suitable choice of counter anions, a significant improvement in photoconversion has been demonstrated, leading to novel photo-responsive polarization switching materials.

Chlamydia psittaci pneumonia: a clinical analysis of 12 patients.

Background: We conducted a retrospective analysis to explore the clinical characteristics, laboratory examination, imaging features, treatment outcomes, and prognosis of the Chlamydia psittaci (C. psittaci) pneumonia, aiming to improve early diagnosis and treatment. Methods: The clinical data of 12 patients with C. psittaci pneumonia diagnosed by metagenomic next-generation sequencing (mNGS) in our hospital were retrospectively analyzed. These data included baseline information, epidemiological history, clinical symptoms and signs, laboratory and chest computed tomography (CT) examination findings, treatment schemes, and prognosis. Results: The average age of the 12 patients was 58.25±13.27 years, and there were 7 (58.3%) males and 5 (41.7%) females in this cohort. Five patients had clear exposure to poultry or birds. The main clinical manifestations included fever (12/12, 100.0%), cough (12/12, 100.0%), expectoration (10/12, 83.3%), and dyspnea (10/12, 83.3%). Laboratory examination showed marked elevation of the total white blood cell (WBC) count, neutrophil (NEUT) count, C-reactive protein (CRP), procalcitonin (PCT), D-dimer, aspartate aminotransferase (AST), alanine aminotransferase (ALT), serum creatinine, and creatine kinase (CK) levels; as well as decreased hemoglobin (HGB), blood platelet (PLT), and albumin (ALB) levels. Arterial blood gas analysis showed that the average value of the oxygenation index (PO2/FiO2) was 290.9±83.1, which was less than 300 in 6 cases (50.0%). The main chest CT features were patchy or consolidation in the bilateral or unilateral lungs, and the boundary was not clear but showed a bronchial inflation sign. Also, some of the cases were accompanied by pleural effusion. Once the etiology was obtained, the patients were quickly treated with doxycycline combined with other antibiotics. All 12 patients improved and were discharged from the hospital. However, two severe patients were admitted to the intensive care unit (ICU) and received ventilation and monitoring treatment. There were no deaths. Conclusions: C. psittaci pneumonia is an atypical community-acquired pneumonia (CAP) caused by C. psittaci infection, with its own laboratory and imaging characteristics. In this study, diagnosis was established based on the application of mNGS owing to the absence of easily available conventional pathogenic evidence. In addition, an aggressive and precise treatment strategy can help achieve a favorable prognosis for patients.

Analysis of Efflux Pump System and Other Drug Resistance Related Gene Mutations in Tigecycline-Resistant Acinetobacter baumannii.

Background: The isolation of tigecycline-resistant Acinetobacter baumannii in recent years has brought great difficulties to clinical prevention and treatment. Purpose: To explore the effect of efflux pump system and other resistance related gene mutations on tigecycline resistance in Acinetobacter baumannii. Methods: Fluorescence quantitative PCR was used to detect the expression levels of major efflux pump genes (adeB, adeJ, and adeG) in extensive drug-resistant Acinetobacter baumannii. The minimum inhibitory concentration (MIC) of tigecycline was detected by the broth microdilution testing and efflux pump inhibition experiment to assess the role of efflux pump in tigecycline resistance of Acinetobacter baumannii. Efflux pump regulatory genes (adeR and adeS) and tigecycline resistance related genes (rpsJ, trm, and plsC) were amplified by PCR and sequenced. By sequence alignment, tigecycline sensitive and tigecycline-insensitive Acinetobacter baumannii were compared with standard strains to analyze the presence of mutations in these genes. Results: The relative expression of adeB in the tigecycline-insensitive Acinetobacter baumannii was significantly higher than that in the tigecycline sensitive Acinetobacter baumannii (114.70 (89.53-157.43) vs 86.12 (27.23-129.34), P = 0.025). When efflux pump inhibitor carbonyl cyanide 3-chlorophenylhydrazone (CCCP) was added, the percentage of tigecycline-insensitive Acinetobacter baumannii with tigecycline MIC decreased was significantly higher than that of tigecycline-sensitive Acinetobacter baumannii (10/13 (76.9%) vs 26/59 (44.1%)), P = 0.032); the relative expression of adeB in the MIC decreased group was significantly higher than that in the MIC unchanged group (110.29 (63.62-147.15) vs 50.06 (26.10-122.59), P = 0.02); The relative expression levels of efflux pumps adeG and adeJ did not increase significantly, and there was no significant difference between these groups. One adeR point mutation (Gly232Ala) and eight adeS point mutations (Ala97Thr, Leu105Phe, Leu172Pro, Arg195Gln, Gln203Leu, Tyr303Phe, Lys315Asn, Gly319Ser) were newly detected. Consistent mutations in trm and plsC genes were detected in both tigecycline-insensitive and tigecycline-sensitive Acinetobacter baumannii, but no mutation in rpsJ gene was detected in them. Conclusion: Tigecycline-insensitive Acinetobacter baumannii efflux pump adeABC overexpression was an important mechanism for tigecycline resistance, and the mutations of efflux pump regulator genes (adeR and adeS) are responsible for adeABC overexpression. The effect of trm, plsC, and rpsJ gene mutations on the development of tigecycline resistance in Acinetobacter baumannii remains controversial.

A new basic probability assignment generation and combination method for conflict data fusion in the evidence theory.

Dempster-Shafer evidence theory is an effective method to deal with information fusion. However, how to deal with the fusion paradoxes while using the Dempster's combination rule is still an open issue. To address this issue, a new basic probability assignment (BPA) generation method based on the cosine similarity and the belief entropy was proposed in this paper. Firstly, Mahalanobis distance was used to measure the similarity between the test sample and BPA of each focal element in the frame of discernment. Then, cosine similarity and belief entropy were used respectively to measure the reliability and uncertainty of each BPA to make adjustments and generate a standard BPA. Finally, Dempster's combination rule was used for the fusion of new BPAs. Numerical examples were used to prove the effectiveness of the proposed method in solving the classical fusion paradoxes. Besides, the accuracy rates of the classification experiments on datasets were also calculated to verify the rationality and efficiency of the proposed method.

A new correlation belief function in Dempster-Shafer evidence theory and its application in classification.

Uncertain information processing is a key problem in classification. Dempster-Shafer evidence theory (D-S evidence theory) is widely used in uncertain information modelling and fusion. For uncertain information fusion, the Dempster's combination rule in D-S evidence theory has limitation in some cases that it may cause counterintuitive fusion results. In this paper, a new correlation belief function is proposed to address this problem. The proposed method transfers the belief from a certain proposition to other related propositions to avoid the loss of information while doing information fusion, which can effectively solve the problem of conflict management in D-S evidence theory. The experimental results of classification on the UCI dataset show that the proposed method not only assigns a higher belief to the correct propositions than other methods, but also expresses the conflict among the data apparently. The robustness and superiority of the proposed method in classification are verified through experiments on different datasets with varying proportion of training set.