Dispersion-assisted high-dimensional photodetector.

Intensity, polarization and wavelength are intrinsic characteristics of light. Characterizing light with arbitrarily mixed information on polarization and spectrum is in high demand1-4. Despite the extensive efforts in the design of polarimeters5-18 and spectrometers19-27, concurrently yielding high-dimensional signatures of intensity, polarization and spectrum of the light fields is challenging and typically requires complicated integration of polarization- and/or wavelength-sensitive elements in the space or time domains. Here we demonstrate that simple thin-film interfaces with spatial and frequency dispersion can project and tailor polarization and spectrum responses in the wavevector domain. By this means, high-dimensional light information can be encoded into single-shot imaging and deciphered with the assistance of a deep residual network. To the best of our knowledge, our work not only enables full characterization of light with arbitrarily mixed full-Stokes polarization states across a broadband spectrum with a single device and a single measurement but also presents comparable, if not better, performance than state-of-the-art single-purpose miniaturized polarimeters or spectrometers. Our approach can be readily used as an alignment-free retrofit for the existing imaging platforms, opening up new paths to ultra-compact and high-dimensional photodetection and imaging.

Explorer: efficient DNA coding by De Bruijn graph toward arbitrary local and global biochemical constraints.

With the exponential growth of digital data, there is a pressing need for innovative storage media and techniques. DNA molecules, due to their stability, storage capacity, and density, offer a promising solution for information storage. However, DNA storage also faces numerous challenges, such as complex biochemical constraints and encoding efficiency. This paper presents Explorer, a high-efficiency DNA coding algorithm based on the De Bruijn graph, which leverages its capability to characterize local sequences. Explorer enables coding under various biochemical constraints, such as homopolymers, GC content, and undesired motifs. This paper also introduces Codeformer, a fast decoding algorithm based on the transformer architecture, to further enhance decoding efficiency. Numerical experiments indicate that, compared with other advanced algorithms, Explorer not only achieves stable encoding and decoding under various biochemical constraints but also increases the encoding efficiency and bit rate by ¿10%. Additionally, Codeformer demonstrates the ability to efficiently decode large quantities of DNA sequences. Under different parameter settings, its decoding efficiency exceeds that of traditional algorithms by more than two-fold. When Codeformer is combined with Reed-Solomon code, its decoding accuracy exceeds 99%, making it a good choice for high-speed decoding applications. These advancements are expected to contribute to the development of DNA-based data storage systems and the broader exploration of DNA as a novel information storage medium.

Genes associated with cortical thickness alterations in behavioral addiction.

Behavioral addiction (BA) is a conceptually new addictive phenotype characterized by compulsive reward-seeking behaviors despite adverse consequences. Currently, its underlying neurogenetic mechanism remains unclear. Here, this study aimed to investigate the association between cortical thickness (CTh) and genetic phenotypes in BA. We conducted a systematic search in five databases and extracted gene expression data from the Allen Human Brain Atlas. Meta-analysis of 10 studies (343 addicted individuals and 355 controls) revealed that the BA group showed thinner CTh in the precuneus, postcentral gyrus, orbital-frontal cortex, and dorsolateral prefrontal cortex (P < 0.005). Meta-regression showed that the CTh in the precuneus and postcentral gyrus were negatively associated with the addiction severity (P < 0.0005). More importantly, the CTh phenotype of BA was spatially correlated with the expression of 12 genes (false discovery rate [FDR] < 0.05), and the dopamine D2 receptor had the highest correlation (rho = 0.55). Gene enrichment analysis further revealed that the 12 genes were involved in the biological processes of behavior regulation and response to stimulus (FDR < 0.05). In conclusion, our findings demonstrated the thinner CTh in cognitive control-related brain areas in BA, which could be associated with the expression of genes involving dopamine metabolism and behavior regulation.

A novel mRNA multi-epitope vaccine of Acinetobacter baumannii based on multi-target protein design in immunoinformatic approach.

Acinetobacter baumannii is a gram-negative bacillus prevalent in nature, capable of thriving under various environmental conditions. As an opportunistic pathogen, it frequently causes nosocomial infections such as urinary tract infections, bacteremia, and pneumonia, contributing to increased morbidity and mortality in clinical settings. Consequently, developing novel vaccines against Acinetobacter baumannii is of utmost importance. In our study, we identified 10 highly conserved antigenic proteins from the NCBI and UniProt databases for epitope mapping. We subsequently screened and selected 8 CTL, HTL, and LBL epitopes, integrating them into three distinct vaccines constructed with adjuvants. Following comprehensive evaluations of immunological and physicochemical parameters, we conducted molecular docking and molecular dynamics simulations to assess the efficacy and stability of these vaccines. Our findings indicate that all three multi-epitope mRNA vaccines designed against Acinetobacter baumannii are promising; however, further animal studies are required to confirm their reliability and effectiveness.

Early detection of uterine corpus endometrial carcinoma utilizing plasma cfDNA fragmentomics.

BACKGROUND: Uterine corpus endometrial carcinoma (UCEC) is a prevalent gynecologic malignancy with a favorable prognosis if detected early. However, there is a lack of accurate and reliable early detection tests for UCEC. This study aims to develop a precise and non-invasive diagnostic method for UCEC using circulating cell-free DNA (cfDNA) fragmentomics. METHODS: Peripheral blood samples were collected from all participants, and cfDNA was extracted for analysis. Low-coverage whole-genome sequencing was performed to obtain cfDNA fragmentomics data. A robust machine learning model was developed using these features to differentiate between UCEC and healthy conditions. RESULTS: The cfDNA fragmentomics-based model showed high predictive power for UCEC detection in training (n = 133; AUC 0.991) and validation cohorts (n = 89; AUC 0.994). The model manifested a specificity of 95.5% and a sensitivity of 98.5% in the training cohort, and a specificity of 95.5% and a sensitivity of 97.8% in the validation cohort. Physiological variables and preanalytical procedures had no significant impact on the classifier's outcomes. In terms of clinical benefit, our model would identify 99% of Chinese UCEC patients at stage I, compared to 21% under standard care, potentially raising the 5-year survival rate from 84 to 95%. CONCLUSION: This study presents a novel approach for the early detection of UCEC using cfDNA fragmentomics and machine learning showing promising sensitivity and specificity. Using this model in clinical practice could significantly improve UCEC management and control, enabling early intervention and better patient outcomes. Further optimization and validation of this approach are warranted to establish its clinical utility.

Risk Factors for Breast Cancer-Related Lymphedema: An Umbrella Review.

BACKGROUND: Identification of risk factors facilitates the prevention of breast cancer-related lymphedema (BCRL). Several published systematic reviews have already addressed the risk factors for BCRL. This study aimed to systematically identify potential risk factors for BCRL and evaluate the quality of evidence. METHODS: The study followed methodologic guidance from the Joanna Briggs Institute, and the Cochrane Handbook. The following electronic databases were systematically searched from inception to 15 November 2022: PubMed, Embase, CINAHL, Web of Science, Scopus, CNKI, SinoMed, Wanfang, JBI Database, Cochrane Database, ProQuest, and PROSPERO. Two authors independently screened studies, extracted data, and assessed methodologic quality using AMSTAR2, risk of bias using ROBIS, and evidence quality using GRADE. The study evaluated overlap, assessed the small-study effect, and calculated the I2 statistic and Egger's P value as needed. RESULTS: The study included 14 publications comprising 10 meta-analyses and 4 systematic reviews. The authors identified 39 factors and 30 unique meta-analyses. In the study, 13 innate personal trait-related risk factors, such as higher body mass index (BMI) and axillary lymph nodes dissection, showed statistically significant associations with BCRL incidence. Breast reconstruction was found to be a protective factor. The methodologic quality was low or critically low. The majority of the systematic reviews and/or meta-analyses were rated as having a high risk of bias. Evidence quality was low for 22 associations and moderate for 8 associations. CONCLUSIONS: The currently identified risk factors for BCRL all are innate personal trait-related factors. Future well-designed studies and robust meta-analyses are needed to explore potential associations between behavioral-, interpersonal-, and environmental-related factors and BCRL, as well as the role of genetic variations and pathophysiologic factors.

Role of Additional MRI-Based Morphologic Measurements on the Performance of VI-RADS for Muscle-Invasive Bladder Cancer.

BACKGROUND: Vesical Imaging-Reporting and Data System (VI-RADS) is a pathway for the standardized imaging and reporting of bladder cancer staging using multiparametric (mp) MRI. PURPOSE: To investigate additional role of morphological (MOR) measurements to VI-RADS for the detection of muscle-invasive bladder cancer (MIBC) with mpMRI. STUDY TYPE: Retrospective. POPULATION: A total of 198 patients (72 MIBC and 126 NMIBC) underwent bladder mpMRI was included. FIELD STRENGTH/SEQUENCE: 3.0 T/T2-weighted imaging with fast-spin-echo sequence, spin-echo-planar diffusion-weighted imaging and dynamic contrast-enhanced imaging with fast 3D gradient-echo sequence. ASSESSMENT: VI-RADS score and MOR measurement including tumor location, number, stalk, cauliflower-like surface, type of tumor growth, tumor-muscle contact margin (TCM), tumor-longitudinal length (TLL), and tumor cellularity index (TCI) were analyzed by three uroradiologists (3-year, 8-year, and 15-year experience of bladder MRI, respectively) who were blinded to histopathology. STATISTICAL TESTS: Significant MOR measurements associated with MIBC were tested by univariable and multivariable logistic regression (LR) analysis with odds ratio (OR). Area under receiver operating characteristic curve (AUC) with DeLong's test and decision curve analysis (DCA) were used to compared the performance of unadjusted vs. adjusted VI-RADS. A P-value <0.05 was considered statistically significant. RESULTS: TCM (OR 9.98; 95% confidence interval [CI] 4.77-20.8), TCI (OR 5.72; 95% CI 2.37-13.8), and TLL (OR 3.35; 95% CI 1.40-8.03) were independently associated with MIBC at multivariable LR analysis. VI-RADS adjusted by three MORs achieved significantly higher AUC (reader 1 0.908 vs. 0.798; reader 2 0.906 vs. 0.855; reader 3 0.907 vs. 0.831) and better clinical benefits than unadjusted VI-RADS at DCA. Specially in VI-RADS-defined equivocal lesions, MOR-based adjustment resulted in 55.5% (25/45), 70.4% (38/54), and 46.4% (26/56) improvement in accuracy for discriminating MIBC in three readers, respectively. DATA CONCLUSION: MOR measurements improved the performance of VI-RADS in detecting MIBC with mpMRI, especially for equivocal lesions. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Photocatalytic PAN Nanofibrous Membrane through Anchoring a Nanoflower-Branched CoAl-LDH@PANI Heterojunction for Organic Hazards Degradation and Oil-Containing Emulsified Wastewater Separation.

The synergistic treatment of oily wastewater containing organic hazards and emulsified oils remains a big challenge for membrane separation technology. Herein, the photocatalytic membrane, which combined the physical barrier and catalytic oxidation-driven degradation functionality, was fabricated via anchoring a nanoflower-branched CoAl-LDH@PANI Z-scheme heterojunction onto a porous polyacrylonitrile mat and using tannic acid as an adhesive. The assembly of such a Z-scheme heterojunction offered the superior photocatalytic degradation performance of soluble dyes and tetracycline (up to 94.3%) to the membrane with the improved photocatalytic activity of 2.33 times compared with the CoAl-LDH@pPAN membrane. Quenching experiments suggested that the •O2- was the most reactive oxygen species in the catalytic reaction system of the composite membrane. The greatly enhanced photocatalytic activity was attributed to the effective inhibition of photogenerated hole-electron combination using PANI as a carrier, with charge transferring from LDH to PANI. The possible photocatalytic degradation mechanism was proposed based on VB-XPS, electron spin resonance spectroscopy, and DRS technologies, which was confirmed by density functional theory calculation. Meanwhile, benefiting from the superhydrophilic/oleophobic feature and low oil adhesion, the membrane exhibited high permeability for isooctane emulsion (3990.39 L·m-2·h-1), high structure stability, and satisfactory cycling performance. This work provided a strategy to develop superwetting and photocatalytic composite membranes for treating complex multicomponent pollutants in the chemical industry.

Design of Cryptococcus neoformans multiepitope vaccine based on immunoinformatics method.

Cryptococcus neoformans is a widely distributed opportunistic pathogenic fungus. While Cryptococcus neoformans commonly infects immunocompromised individuals, it can also affect those who are immunocompetent. Transmission of Cryptococcus neoformans primarily occurs through the respiratory tract, leading to the development of meningitis. The mortality rate of Cryptococcal meningitis is high, and treatment options are limited. Cryptococcus neoformans infections pose a significant public health threat and currently lack targeted and effective response strategies. This study aimed to screen T lymphocyte(CTL, HTL) and B lymphocyte (LBL) epitopes derived from four Cryptococcus neoformans antigens and develop two multi-epitope vaccines by combining them with various adjuvants. Molecular docking results demonstrated that the vaccines bind stably to TLR4 and induce innate immunity. The credibility of the molecular docking results was validated through subsequent molecular dynamics simulations. Furthermore, the results of immune simulation analyses underscored the multi-epitope vaccine's capability to effectively induce robust humoral and cellular immune responses within the host organism. These two vaccines have demonstrated theoretical efficacy against Cryptococcus neoformans infection as indicated by computer analysis. Nevertheless, additional experimental validation is essential to substantiate the protective efficacy of the vaccines.

A multi-epitope Cryptococcus neoformans vaccine covering the most common A and D phenotypes was designed using bioinformatics methods.

Effects of geniposide on innate immunity and antiviral activity of Scyllaparamamosain.

In this study, we examined the impact of geniposide on the innate immunity of the mud crab Scylla paramamosain, specifically in relation to WSSV infection. Through the use of in vitro cell culture experiments, we assessed the effects of geniposide on various parameters of hemocyte activity in S. paramamosain. Our findings revealed that high doses of geniposide inhibited hemocyte growth, with an optimal dose of 100 mg/kg determined. Additionally, we observed that geniposide increased the total hemocyte counts in S. paramamosain following WSSV infection. Geniposide also enhanced the enzymatic activities in hemolymph following treatment. The enzymes affected by geniposide encompassed ACP (acid phosphatase), POD (phenol oxidase catalase), PO (phenoloxidase), SOD (superoxide dismutase), CAT (catalase), and LZM (lysozyme). Furthermore, the activities of ACP, POD, PO, and LZM were also observed to increase subsequent to infection with WSSV. Notably, geniposide was found to enhance the phagocytosis of V. alginolyticus within the hemocytes. Geniposide can reduce hemocyte apoptosis rates after treatment, as well as hemocytes infected with WSSV. Furthermore, geniposide treatment significantly up-regulated the expression level of Myosin, but expression levels of Astakine, C-type lectin (CTL), STAT, JAK, proPO, minichromosome maintenance protein (MCM7), caspase-3 and crustin were down-regulated in the hemocytes. Additionally, geniposide treatment inhibited WSSV replication in hemocytes of S. paramamosain, and enhanced the survival rates of mud crabs following WSSV infection. These experimental results provide evidence that geniposide can improve the immune response by regulating humoral immunity and cellular immunity, and enhance pathogen resistance in S. paramamosain.

Identification of novel disulfidptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of skin cutaneous melanoma patients.

BACKGROUND: Skin cutaneous melanoma (SKCM) is an aggressive form of malignant melanoma with poor prognosis and high mortality rates. Disulfidptosis is a newly discovered cell death regulatory mechanism caused by the abnormal accumulation of disulfides. This unique pathway is guiding significant new research to understand cancer progression for targeted treatment. However, the correlation between disulfidptosis with long non-coding RNAs (lncRNAs) in SKCM remains unknown at present. METHODS: The Cancer Genome Atlas database furnished lncRNA expression data and clinical information for SKCM patients. Pearson correlation and Cox regression analyses identified disulfidptosis-related lncRNAs associated with SKCM prognosis. ROC curves and a nomogram validated the model. TME, immune infiltration, GSEA analysis, immune checkpoint gene expression profiling, and drug sensitivity were assessed in high and low-risk groups. Consistent clustering categorized SKCM patients for personalized clinical treatment guidance. RESULTS: A total of twelve disulfidptosis-related lncRNAs were identified for the development of prognosis prediction models. The area under the curve (AUC) values of the ROC curve and the nomogram provided reliable discrimination to evaluate the prognostic potential for SKCM patients. The TME played a crucial role in tumorigenesis, progression and prognosis, and the risk scores were closely related to immune cell infiltration. Meanwhile, the combination of chemotherapy, targeted therapy, and immunotherapy was recommended for low-risk patients based on drug sensitivity and immune efficacy analyses. CONCLUSION: We identified a risk model of twelve disulfidptosis-related lncRNAs that could be used to predict the prognosis of SKCM patients and help guide immunotherapy and chemotherapy for personalized treatment plans.

Optimizing the management of electrophysiology labs in Chinese hospitals using a discrete event simulation tool.

BACKGROUND: The growing demand for electrophysiology (EP) treatment in China presents a challenge for current EP care delivery systems. This study constructed a discrete event simulation (DES) model of an inpatient EP care delivery process, simulating a generalized inpatient journey of EP patients from admission to discharge in the cardiology department of a tertiary hospital in China. The model shows how many more patients the system can serve under different resource constraints by optimizing various phases of the care delivery process. METHODS: Model inputs were based on and validated using real-world data, simulating the scheduling of limited resources among competing demands from different patient types. The patient stay consists of three stages, namely: the pre-operative stay, the EP procedure, and the post-operative stay. The model outcome was the total number of discharges during the simulation period. The scenario analysis presented in this paper covers two capacity-limiting scenarios (CLS): (1) fully occupied ward beds and (2) fully occupied electrophysiology laboratories (EP labs). Within each CLS, we investigated potential throughput when the length of stay or operative time was reduced by 10%, 20%, and 30%. The reductions were applied to patients with atrial fibrillation, the most common indication accounting for almost 30% of patients. RESULTS: Model validation showed simulation results approximated actual data (137.2 discharges calculated vs. 137 observed). With fully occupied wards, reducing pre- and/or post-operative stay time resulted in a 1-7% increased throughput. With fully occupied EP labs, reduced operative time increased throughput by 3-12%. CONCLUSIONS: Model validation and scenario analyses demonstrated that the DES model reliably reflects the EP care delivery process. Simulations identified which phases of the process should be optimized under different resource constraints, and the expected increases in patients served.

Effects of different salinity reduction intervals on osmoregulation, anti-oxidation and apoptosis of Eriocheir sinensis megalopa.

Eriocheir sinensis megalopa has a special life history of migrating from seawater to freshwater. In order to investigate how the megalopa adapt themselves to the freshwater environment, we designed an experiment to reduce the salinity of water from 30 ppt to 0 at rates of 30 ppt, 15 ppt, 10 ppt, and 5 ppt per 24 h to evaluate the effects of different degrees of hyposaline stress on the osmotic regulation ability and antioxidant system of the megalopa. Experimental results related to osmotic pressure regulation show that the gill tissue of megalopa in the treatment group of 30 ppt/24 h rapid reduction of salinity was damaged, while in the treatment group of 5 ppt/24 h it was intact. At the same time, the experiment also found that in each treatment group with different salinity reduction rates, compared with the control salinity, the NKA activity of megalopa increased significantly after the salinity was reduced to 20 ppt (p < 0.05). In addition, two genes involved in chloride ion transmembrane absorption have different expression patterns in the treatment groups with different salinity reduction rates. Among them, Clcn2 was significantly highly expressed only in the rapid salinity reduction intervals of 30 ppt/24 h and 15 ppt/24 h (p < 0.05). Slc26a6 was significantly highly expressed only in the slow salinity reduction intervals of 10 ppt/24 h and 5 ppt/24 h (p < 0.05). On the other hand, the results of antioxidant and apoptosis related experiments showed that in all treatment groups with different rates of salinity reduction, the activities of T-AOC, GSH-PX, and CAT basically increased significantly after salinity reduction compared to the control salinity. Moreover, the activities of T-AOC and CAT were significantly higher in the 10 ppt/24 h and 5 ppt/24 h treatment groups than in the 30 ppt/24 h and 15 ppt/24 h treatment groups. Finally, the experimental results related to apoptosis showed that the expression trends of Capase3 and Bax-2 were basically the same in the treatment groups with different salinity reduction rates, and their expressions were significantly higher in the 10 ppt/24 h and 5 ppt/24 h treatment groups than in the 30 ppt/24 h and 15 ppt/24 h treatment groups. In summary, the present study found that megalopa had strong hyposaline tolerance and were able to regulate osmolality at different rates of salinity reduction, but the antioxidant capacity differed significantly between treatment groups, with rapid salinity reduction leading to oxidative damage in the anterior gills and reduced antioxidant enzyme activity and apoptosis levels.

Preparation of Surface Dispersed WO3/BiVO4 Heterojunction Arrays and Their Photoelectrochemical Performance for Water Splitting.

In this work, a surface dispersed heterojunction of BiVO4-nanoparticle@WO3-nanoflake was successfully prepared by hydrothermal combined with solvothermal method. We optimized the morphology of the WO3 nanoflakes and BiVO4 nanoparticles by controlling the synthesis conditions to get the uniform BiVO4 loaded on the surface of WO3 arrays. The phase composition and morphology evolution with different reaction precursors were investigated in detail. When used as photoanodes, the WO3/BiVO4 composite exhibits superior activity with photocurrent at 3.53 mA cm-2 for photoelectrochemical (PEC) water oxidation, which is twice that of pure WO3 photoanode. The superior surface dispersion structure of the BiVO4-nanoparticle@WO3-nanoflake heterojunction ensures a large effective heterojunction area and relieves the interfacial hole accumulation at the same time, which contributes to the improved photocurrents together with the stability of the WO3/BiVO4 photoanodes.

Selective Removal of Hemicellulose by Diluted Sulfuric Acid Assisted by Aluminum Sulfate.

Hemicellulose can be selectively removed by acid pretreatment. In this study, selective removal of hemicellulose was achieved using dilute sulfuric acid assisted by aluminum sulfate pretreatment. The optimal pretreatment conditions were 160 °C, 1.5 wt% aluminum sulfate, 0.7 wt% dilute sulfuric acid, and 40 min. A component analysis showed that the removal rate of hemicellulose and lignin reached 98.05% and 9.01%, respectively, which indicated that hemicellulose was removed with high selectivity by dilute sulfuric acid assisted by aluminum sulfate pretreatment. Structural characterizations (SEM, FTIR, BET, TGA, and XRD) showed that pretreatment changed the roughness, crystallinity, pore size, and functional groups of corn straw, which was beneficial to improve the efficiency of enzymatic hydrolysis. This study provides a new approach for the high-selectivity separation of hemicellulose, thereby offering novel insights for its subsequent high-value utilization.

BAGAIL: Multi-modal imitation learning from imbalanced demonstrations.

Expert demonstrations in imitation learning often contain different behavioral modes, e.g., driving modes such as driving on the left, keeping the lane, and driving on the right in the driving tasks. Although most existing multi-modal imitation learning methods allow learning from demonstrations of multiple modes, they have strict constraints on the data of each mode, generally requiring a near data ratio of all modes. Otherwise, it tends to fall into a mode collapse or only learn the data distribution of the mode that has the largest data volume. To address the problem, an algorithm that balances real-fake loss and classification loss by modifying the output of the discriminator, referred to as BAlanced Generative Adversarial Imitation Learning (BAGAIL), is proposed. With this modification, the generator is only rewarded for generating real trajectories with correct modes. BAGAIL is therefore able to deal with imbalanced expert demonstrations and carry out efficient learning for each mode. The learning process of BAGAIL is divided into a pre-training stage and an imitation learning stage. During the pre-training stage, BAGAIL initializes the generator parameters by means of conditional Behavioral Cloning, laying the foundation for the direction of parameter optimization. During the imitation learning stage, BAGAIL optimizes the parameters by using the adversary between the generator and the modified discriminator so that the finally obtained policy can successfully learn the distribution of imbalanced expert data. The experiments showed that BAGAIL accurately distinguished different behavioral modes with imbalanced demonstrations. What is more, the learning result of each mode is close to the expert standard and more stable than other multi-modal imitation learning methods.

Multi-objective molecular generation via clustered Pareto-based reinforcement learning.

De novo molecular design is the process of learning knowledge from existing data to propose new chemical structures that satisfy the desired properties. By using de novo design to generate compounds in a directed manner, better solutions can be obtained in large chemical libraries with less comparison cost. But drug design needs to take multiple factors into consideration. For example, in polypharmacology, molecules that activate or inhibit multiple target proteins produce multiple pharmacological activities and are less susceptible to drug resistance. However, most existing molecular generation methods either focus only on affinity for a single target or fail to effectively balance the relationship between multiple targets, resulting in insufficient validity and desirability of the generated molecules. To address the problems, an approach called clustered Pareto-based reinforcement learning (CPRL) is proposed. In CPRL, a pre-trained model is constructed to grasp existing molecular knowledge in a supervised learning manner. In addition, the clustered Pareto optimization algorithm is presented to find the best solution between different objectives. The algorithm first extracts an update set from the sampled molecules through the designed aggregation-based molecular clustering. Then, the final reward is computed by constructing the Pareto frontier ranking of the molecules from the updated set. To explore the vast chemical space, a reinforcement learning agent is designed in CPRL that can be updated under the guidance of the final reward to balance multiple properties. Furthermore, to increase the internal diversity of the molecules, a fixed-parameter exploration model is used for sampling in conjunction with the agent. The experimental results demonstrate that CPRL is capable of balancing multiple properties of the molecule and has higher desirability and validity, reaching 0.9551 and 0.9923, respectively.

The Roles of Proactive Personality and Career Satisfaction in the Impact of Employer Brand Attributes Congruence on Creativity.

Although the relationship between employer brand and employee creativity has become a popular theme, this nexus is indirect and ambiguous. Additionally, most studies ignore the consistency of instrumental and symbolic attributes when discussing the consequences of employer brand. This study explored the mechanism of employer brand attributes congruence on employee creativity through career satisfaction, and further revealed the moderating role of proactive personality. Based on the cue consistency theory and the social information processing theory, a polynomial regression model was created and a response surface analysis was conducted using 488 paired questionnaires. The results showed that employer brand attributes congruence impacted employee creativity via career satisfaction. A consistent employer brand strategy is more effective for the creativity of less proactive individuals, while a high-level proactive personality can compensate for the deficiencies of employer brand attributes incongruence. The results complemented employer brand research from the perspective of the instrumental-symbolic attribute configuration and provided supportive empirical evidence of employer brand practices aiming at improving employee creativity. This study has certain practical implications for HR practitioners.

RM-GPT: Enhance the comprehensive generative ability of molecular GPT model via LocalRNN and RealFormer.

Due to the surging of cost, artificial intelligence-assisted de novo drug design has supplanted conventional methods and become an emerging option for drug discovery. Although there have arisen many successful examples of applying generative models to the molecular field, these methods struggle to deal with conditional generation that meet chemists' practical requirements which ask for a controllable process to generate new molecules or optimize basic molecules with appointed conditions. To address this problem, a Recurrent Molecular-Generative Pretrained Transformer model is proposed, supplemented by LocalRNN and Residual Attention Layer Transformer, referred to as RM-GPT. RM-GPT rebuilds GPT model's architecture by incorporating LocalRNN and Residual Attention Layer Transformer so that it is able to extract local information and build connectivity between attention blocks. The incorporation of Transformer in these two modules enables leveraging the parallel computing advantages of multi-head attention mechanisms while extracting local structural information effectively. Through exploring and learning in a large chemical space, RM-GPT absorbs the ability to generate drug-like molecules with conditions in demand, such as desired properties and scaffolds, precisely and stably. RM-GPT achieved better results than SOTA methods on conditional generation.

Production and quality evaluation of a novel γ-aminobutyric acid-enriched yogurt.

Objective: γ-aminobutyric acid (GABA) is a neurotransmitter inhibitor that has beneficial effects on various health conditions such as hypertension, cognitive dysfunction, and anxiety. In this study, we investigated a novel yogurt naturally enriched with GABA using a Levilactobacillus brevis strain isolated in our laboratory; the specific optimum yogurt production conditions for this strain were determined. Methods: We isolated an L. brevis strain and used it to produce yogurt naturally enriched with GABA. We explored the optimal conditions to enhance GABA yield, including fermentation temperature, inoculation amount, L-monosodium glutamate (L-MSG) concentration, fermentation time, and sucrose content. We also performed mixed fermentation with Streptococcus thermophilus and evaluated the quality of the yogurt. Results: Following optimization (43°C, 8% inoculation amount, 1.5 g/L L-MSG, and 8% sucrose for 40 h of fermentation), the GABA yield of the yogurt increased by 2.2 times, reaching 75.3 mg/100 g. Mixed fermentation with S. thermophilus demonstrated favorable results, achieving a GABA yield akin to that found in some commercially available functional foods. Moreover, the viable microbe count in the GABA-enriched yogurt exceeded 1 × 108 cfu/mL, which is higher than that of commercial standards. The yogurt also exhibited a suitable water-holding capacity, viscosity, 3-week storage time, and favorable sensory test results. Conclusion: This study highlights the potential of naturally enriched GABA yogurt as a competitive commercial yogurt with beneficial health effects.