Antibodies expand the scope of angiotensin receptor pharmacology.

G-protein-coupled receptors (GPCRs) are key regulators of human physiology and are the targets of many small-molecule research compounds and therapeutic drugs. While most of these ligands bind to their target GPCR with high affinity, selectivity is often limited at the receptor, tissue and cellular levels. Antibodies have the potential to address these limitations but their properties as GPCR ligands remain poorly characterized. Here, using protein engineering, pharmacological assays and structural studies, we develop maternally selective heavy-chain-only antibody ('nanobody') antagonists against the angiotensin II type I receptor and uncover the unusual molecular basis of their receptor antagonism. We further show that our nanobodies can simultaneously bind to angiotensin II type I receptor with specific small-molecule antagonists and demonstrate that ligand selectivity can be readily tuned. Our work illustrates that antibody fragments can exhibit rich and evolvable pharmacology, attesting to their potential as next-generation GPCR modulators.

Theta Signal Transfer from Parietal to Prefrontal Cortex Ignites Conscious Awareness of Implicit Knowledge during Sequence Learning.

Unconscious acquisition of sequence structure from experienced events can lead to explicit awareness of the pattern through extended practice. Although the implicit-to-explicit transition has been extensively studied in humans using the serial reaction time (SRT) task, the subtle neural activity supporting this transition remains unclear. Here, we investigated whether frequency-specific neural signal transfer contributes to this transition. A total of 208 participants (107 females) learned a sequence pattern through a multisession SRT task, allowing us to observe the transitions. Session-by-session measures of participants' awareness for sequence knowledge were conducted during the SRT task to identify the session when the transition occurred. By analyzing time course RT data using switchpoint modeling, we identified an increase in learning benefit specifically at the transition session. Electroencephalogram (EEG)/magnetoencephalogram (MEG) recordings revealed increased theta power in parietal (precuneus) regions one session before the transition (pretransition) and a prefrontal (superior frontal gyrus; SFG) one at the transition session. Phase transfer entropy (PTE) analysis confirmed that directional theta transfer from precuneus → SFG occurred at the pretransition session and its strength positively predicted learning improvement at the subsequent transition session. Furthermore, repetitive transcranial magnetic stimulation (TMS) modulated precuneus theta power and altered transfer strength from precuneus to SFG, resulting in changes in both transition rate and learning benefit at that specific point of transition. Our brain-stimulation evidence supports a role for parietal → prefrontal theta signal transfer in igniting conscious awareness of implicitly acquired knowledge.SIGNIFICANCE STATEMENT There exists a pervasive phenomenon wherein individuals unconsciously acquire sequence patterns from their environment, gradually becoming aware of the underlying regularities through repeated practice. While previous studies have established the robustness of this implicit-to-explicit transition in humans, the refined neural mechanisms facilitating conscious access to implicit knowledge remain poorly understood. Here, we demonstrate that prefrontal activity, known to be crucial for conscious awareness, is triggered by neural signal transfer originating from the posterior brain region, specifically the precuneus. By employing brain stimulation techniques, we establish a causal link between neural signal transfer and the occurrence of awareness. Our findings unveil a mechanism by which implicit knowledge becomes consciously accessible in human cognition.

Controllable Electronic Transfer Tailoring d-band Center via Cobalt-Oxygen-Bridged Ru/Fe Dual-sites for Boosted Oxygen Evolution.

Rational tailoring of the electronic structure at the defined active center of reconstructed metal (oxy)hydroxides (MOOH) during oxygen evolution reaction (OER) remains a challenge. With the guidance of density functional theory (DFT), herein a dual-site regulatory strategy is reported to tailor the d-band center of the Co site in CoOOH via the controlled electronic transfer at the Ru─O─Co─O─Fe bonding structure. Through the bridged O2- site, electrons are vastly flowed from the t2g-orbital of the Ru site to the low-spin orbital of the Co site in the Ru-O-Co coordination and further transfer from the strong electron-electron repulsion of the Co site to the Fe site by the Co-O-Fe coordination, which balancing the electronic configuration of Co sites to weaken the over-strong adsorption energy barrier of OH* and O*, respectively. Benefiting from the highly active of the Co site, the constructed (Ru2Fe2Co6)OOH provide an extremely low overpotential of 248 mV and a Tafel slope of 32.5 mV dec-1 at 10 mA cm-2 accompanied by long durability in alkaline OER, far superior over the pristine and Co-O-Fe bridged CoOOH catalysts. This work provides guidance for the rational design and in-depth analysis of the optimized role of metal dual-sites.

Prevalence and genetic diversity of human rhinovirus among patients with acute respiratory infections in China, 2012-2021.

To understand the prevalence of rhinovirus (RV) among acute respiratory infection (ARI) patients, 10-year ARI surveillance in multiple provinces of China were conducted during 2012-2021. Of 15 645 ARI patients, 1180 (7.54%) were confirmed to have RV infection and 820 (69.49%) were children under 5 years of age. RV typing was performed on the 527 VP1 gene sequences, and species A, B, and C accounted for 73.24%, 4.93%, and 21.82%, respectively. Although no significant difference in the proportions of age groups or disease severity was found between RV species, RV-C was more frequently detected in children under 5 years of age, RV-A was more frequently detected in elderly individuals (≥60), and the proportions of pneumonia in RV-A and RV-C patients were higher than those in RV-B patients. The epidemic peak of RV-A was earlier than that of RV-C. A total of 57 types of RV-A, 13 types of RV-B, and 35 types of RV-C were identified in RV-infected patients, and two uncertain RV types were also detected. The findings showed a few differences in epidemiological and clinical features between RV species in ARI patients, and RV-A and RV-C were more prevalent than RV-B.

Engineering and Characterization of a Long-Half-Life Relaxin Receptor RXFP1 Agonist.

Relaxin-2 is a peptide hormone with important roles in human cardiovascular and reproductive biology. Its ability to activate cellular responses such as vasodilation, angiogenesis, and anti-inflammatory and antifibrotic effects has led to significant interest in using relaxin-2 as a therapeutic for heart failure and several fibrotic conditions. However, recombinant relaxin-2 has a very short serum half-life, limiting its clinical applications. Here, we present protein engineering efforts targeting the relaxin-2 hormone in order to increase its serum half-life while maintaining its ability to activate the G protein-coupled receptor RXFP1. To achieve this, we optimized a fusion between relaxin-2 and an antibody Fc fragment, generating a version of the hormone with a circulating half-life of around 3 to 5 days in mice while retaining potent agonist activity at the RXFP1 receptor both in vitro and in vivo.

Salidroside ameliorates acetaminophen-induced acute liver injury through the inhibition of endoplasmic reticulum stress-mediated ferroptosis by activating the AMPK/SIRT1 pathway.

Acetaminophen (APAP) overdose has long been considered a major cause of drug-induced liver injury. Ferroptosis is a type of programmed cell death mediated by iron-dependent lipid peroxidation. Endoplasmic reticulum (ER) stress is a systemic response triggered by the accumulation of unfolded or misfolded proteins in the ER. Ferroptosis and ER stress have been proven to contribute to the progression of APAP-induced acute liver injury (ALI). It was reported that salidroside protects against APAP-induced ALI, but the potential mechanism remain unknown. In this study, male C57BL/6 J mice were intraperitoneally (i.p.) injected APAP (500 mg/kg) to induce an ALI model. Salidroside was i.p. injected at a dose of 100 mg/kg 2 h prior to APAP administration. Mice were sacrificed 12 h after APAP injection and the liver and serum of the mice were obtained for histological and biochemistry analysis. AML12 cells were used in in vitro assays. The results indicated that salidroside mitigated glutathione degradation via inhibiting cation transport regulator homolog 1 (CHAC1) to attenuate ferroptosis, and simultaneously suppressing PERK-eIF2α-ATF4 axis-mediated ER stress, thus alleviating APAP-induced ALI. However, PERK activator CCT020312 and overexpression of ATF4 inhibited the protective function of salidroside on CHAC1-mediated ferroptosis. Besides this, activation of the AMPK/SIRT1 signaling pathway by salidroside was demonstrated to have a protective effect against APAP-induced ALI. Interestingly, selective inhibition of SIRT1 ameliorated the protective effects of salidroside on ER stress and ferroptosis. Overall, salidroside plays a significant part in the mitigation of APAP-induced ALI by activating the AMPK/SIRT1 signaling to inhibit ER stress-mediated ferroptosis in the ATF4-CHAC1 axis.

Prospects of Using Chitosan-Based Biopolymers in the Treatment of Peripheral Nerve Injuries.

Peripheral nerve injuries are common neurological disorders, and the available treatment options, such as conservative management and surgical repair, often yield limited results. However, there is growing interest in the potential of using chitosan-based biopolymers as a novel therapeutic approach to treating these injuries. Chitosan-based biopolymers possess unique characteristics, including biocompatibility, biodegradability, and the ability to stimulate cell proliferation, making them highly suitable for repairing nerve defects and promoting nerve regeneration and functional recovery. Furthermore, these biopolymers can be utilized in drug delivery systems to control the release of therapeutic agents and facilitate the growth of nerve cells. This comprehensive review focuses on the latest advancements in utilizing chitosan-based biopolymers for peripheral nerve regeneration. By harnessing the potential of chitosan-based biopolymers, we can pave the way for innovative treatment strategies that significantly improve the outcomes of peripheral nerve injury repair, offering renewed hope and better prospects for patients in need.

The Porous Structure of Peripheral Nerve Guidance Conduits: Features, Fabrication, and Implications for Peripheral Nerve Regeneration.

Porous structure is an important three-dimensional morphological feature of the peripheral nerve guidance conduit (NGC), which permits the infiltration of cells, nutrients, and molecular signals and the discharge of metabolic waste. Porous structures with precisely customized pore sizes, porosities, and connectivities are being used to construct fully permeable, semi-permeable, and asymmetric peripheral NGCs for the replacement of traditional nerve autografts in the treatment of long-segment peripheral nerve injury. In this review, the features of porous structures and the classification of NGCs based on these characteristics are discussed. Common methods for constructing 3D porous NGCs in current research are described, as well as the pore characteristics and the parameters used to tune the pores. The effects of the porous structure on the physical properties of NGCs, including biodegradation, mechanical performance, and permeability, were analyzed. Pore structure affects the biological behavior of Schwann cells, macrophages, fibroblasts, and vascular endothelial cells during peripheral nerve regeneration. The construction of ideal porous structures is a significant advancement in the regeneration of peripheral nerve tissue engineering materials. The purpose of this review is to generalize, summarize, and analyze methods for the preparation of porous NGCs and their biological functions in promoting peripheral nerve regeneration to guide the development of medical nerve repair materials.

G protein-coupled receptor signaling: transducers and effectors.

G protein-coupled receptors (GPCRs) are of considerable interest due to their importance in a wide range of physiological functions and in a large number of Food and Drug Administration (FDA)-approved drugs as therapeutic entities. With continued study of their function and mechanism of action, there is a greater understanding of how effector molecules interact with a receptor to initiate downstream effector signaling. This review aims to explore the signaling pathways, dynamic structures, and physiological relevance in the cardiovascular system of the three most important GPCR signaling effectors: heterotrimeric G proteins, GPCR kinases (GRKs), and ß-arrestins. We will first summarize their prominent roles in GPCR pharmacology before transitioning into less well-explored areas. As new technologies are developed and applied to studying GPCR structure and their downstream effectors, there is increasing appreciation for the elegance of the regulatory mechanisms that mediate intracellular signaling and function.

Lens culinaris agglutinin inhibits human hepatoma cell migration via mannose and fucose-mediated ERK1/2 and JNK1/2/3 signalling pathway.

BACKGROUND: Hepatocellular carcinoma (HCC) is the main types of primary liver cancer, which shows some abnormal glycosylation, such as the increase of fucose. Lens culinaris agglutinin (LCA), a natural plant lectin that can bind to mannose and fucose, has been reported to be antiproliferative to may tumors. However, the effect of LCA on the vitality and migration ability of human hepatoma cells is not demonstrated. Therefore, the aim of this study is to investigate the effects of LCA on vitality and migration in human hepatoma cells and its potential mechanisms. METHODS AND RESULTS: LCA had no significant effect on viability of human hepatoma cells (HCCLM3, MHCC97L and HepG2) and hepatocytes (L02) by CCK-8 kit, but it could inhibit human hepatoma cells migration significantly without affecting hepatocytes by Transwell method. Sugar inhibition assay was used to verify the possible binding site between LCA and human hepatoma cells. The result showed that Mannose- and fucose- related sites were associated with LCA inhibiting human hepatoma cells migration. Moreover, LCA could affect HCCLM3 migration by activating ERK1/2 and JNK1/2/3 signalling pathways. LCA did not affect MMP-2 and MMP-9 of HCCLM3 through gelatinase zymography. However, the results of immunofluorescence standing showed that LCA could reduce the F-actin formation in HCCLM3 via ERK1/2 and JNK1/2/3 signalling pathways. CONCLUSIONS: LCA might inhibit human hepatoma cell migration by reducing the F-actin formation via the mannose and fucose-mediated ERK1/2 and JNK1/2/3 signalling pathway. This result will deepen people's understanding on plant lectin as a drug in tumor glycobiology.

Relationship between family support, serum lipid knowledge and quality of life in Chinese breast cancer women with adjuvant endocrine therapy.

BACKGROUND: Serum lipid management is an important health management goal for breast cancer patients with endocrine therapy, and serum lipid knowledge is a substantial factor influencing patients' serum lipid management behavior. The aim of this study was to explore the relationship between family support, serum lipid knowledge and quality of life in breast cancer women with endocrine therapy. METHODS: Through convenience sampling, 301 women who had been treated in the First Affiliated Hospital of China Medical University and Liaoning Cancer Hospital were selected to fill in the questionnaire of knowledge-attitude-practice (KAP) on serum lipids, family support questionnaire (FSQ), and the functional assessment of cancer therapy-breast cancer (FACT-B). Pearson correlation coefficient was used to analyze the correlation between the three. Multiple linear regression model was used to analyze the influencing factors of quality of life in breast cancer patients with endocrine therapy. RESULTS: The average score of KAP on serum lipids was 42.62 ± 7.333, the average score of family support was 12.55 ± 2.390, and the average score of quality of life was 97.13 ± 21.347, all above the medium level. Family support of breast cancer women with endocrine therapy was positively correlated with serum lipid knowledge and quality of life. Disease stage, family support, and serum lipid knowledge were the influencing factors of quality of life of breast cancer women with endocrine therapy. CONCLUSION: Good family support is associated with better serum lipid knowledge in breast cancer women with endocrine therapy. Therefore, interventions that aim to improve the level of family support may be one way to improve the knowledge level of serum lipid, prevent cardiovascular and cerebrovascular diseases, and improve the quality of life.

The relationship among psychosocial adaptation, medication adherence and quality of life in breast cancer women with adjuvant endocrine therapy.

BACKGROUND: Patients undergoing endocrine therapy for breast cancer often suffer from poor psychosocial adaptation, low compliance with endocrine therapy and poor quality of life. However, the relationship among the three is not completely clear. The aims of this study were to investigate the status of psychosocial adaptation (PSA), medication adherence and quality of life (QOL) in breast cancer women with adjuvant endocrine therapy (AET), and to analyze the influencing factors of QOL and explore the relationship among them. METHODS: 346 breast cancer women were selected who underwent endocrine therapy after surgery, and data collected by the general information questionnaire, the PSA questionnaire among breast cancer women with AET, Morisky Medication Adherence Scale and The Functional Assessment of Cancer Therapy-Breast (FACT-B). The relationship among the variables was investigated by univariate analysis, multiple stepwise regression analysis and mediating effect analysis. RESULTS: The scores of PSA, medication adherence and QOL were slightly above the medium level. Univariate analysis showed that there were significant differences in QOL among breast cancer women of AET with different types of exercise, medical payment methods, discomfort symptoms (headache, hypomnesis, arthralgia, perturbation), type of discomfort symptoms, medication adherence and PSA; Multi-factor analysis showed that PSA and medication adherence were the influential factors of QOL; mediating effect showed that medication adherence played a partial mediating role in PSA and QOL. CONCLUSION: The QOL of breast cancer women with AET will be directly affected by PSA. Medication compliance has a weak mediating effect in the indirect impact of PSA on the QOL. In the future, clinical nursing work should take targeted measures to improve the PSA level of patients, and effectively improve the compliance of patients with medication, so as to better improve the QOL of breast cancer women.

ß-Arrestin-Biased Allosteric Modulator Potentiates Carvedilol-Stimulated ß Adrenergic Receptor Cardioprotection.

ß 1 adrenergic receptors (ß 1ARs) are central regulators of cardiac function and a drug target for cardiac disease. As a member of the G protein-coupled receptor family, ß 1ARs activate cellular signaling by primarily coupling to Gs proteins to activate adenylyl cyclase, cAMP-dependent pathways, and the multifunctional adaptor-transducer protein ß-arrestin. Carvedilol, a traditional ß-blocker widely used in treating high blood pressure and heart failure by blocking ß adrenergic receptor-mediated G protein activation, can selectively stimulate Gs-independent ß-arrestin signaling of ß adrenergic receptors, a process known as ß-arrestin-biased agonism. Recently, a DNA-encoded small-molecule library screen against agonist-occupied ß 2 adrenergic receptors (ß 2ARs) identified Compound-6 (Cmpd-6) to be a positive allosteric modulator for agonists on ß 2ARs. Intriguingly, it was further discovered that Cmpd-6 is positively cooperative with the ß-arrestin-biased ligand carvedilol at ß 2ARs. Here we describe the surprising finding that at ß 1ARs unlike ß 2ARs, Cmpd-6 is cooperative only with carvedilol and not agonists. Cmpd-6 increases the binding affinity of carvedilol for ß 1ARs and potentiates carvedilol-stimulated, ß-arrestin-dependent ß 1AR signaling, such as epidermal growth factor receptor transactivation and extracellular signal-regulated kinase activation, whereas it does not have an effect on Gs-mediated cAMP generation. In vivo, Cmpd-6 enhances the antiapoptotic, cardioprotective effect of carvedilol in response to myocardial ischemia/reperfusion injury. This antiapoptotic role of carvedilol is dependent on ß-arrestins since it is lost in mice with myocyte-specific deletion of ß-arrestins. Our findings demonstrate that Cmpd-6 is a selective ß-arrestin-biased allosteric modulator of ß 1ARs and highlight its potential clinical utility in enhancing carvedilol-mediated cardioprotection against ischemic injury. SIGNIFICANCE STATEMENT: This study demonstrates the positive cooperativity of Cmpd-6 on ß1ARs as a ß-arrestin-biased positive allosteric modulator. Cmpd-6 selectively enhances the affinity and cellular signaling of carvedilol, a known ß-arrestin-biased ß-blocker for ß1ARs, whereas it has minimal effect on other ligands tested. Importantly, Cmpd-6 enhances the ß-arrestin-dependent in vivo cardioprotective effect of carvedilol during ischemia/reperfusion injury-induced apoptosis. The data support the potential therapeutic application of Cmpd-6 to enhance the clinical benefits of carvedilol in the treatment of cardiac disease.

Modeling and computation of multistep batch testing for infectious diseases.

We propose a mathematical model based on probability theory to optimize COVID-19 testing by a multistep batch testing approach with variable batch sizes. This model and simulation tool dramatically increase the efficiency and efficacy of the tests in a large population at a low cost, particularly when the infection rate is low. The proposed method combines statistical modeling with numerical methods to solve nonlinear equations and obtain optimal batch sizes at each step of tests, with the flexibility to incorporate geographic and demographic information. In theory, this method substantially improves the false positive rate and positive predictive value as well. We also conducted a Monte Carlo simulation to verify this theory. Our simulation results show that our method significantly reduces the false negative rate. More accurate assessment can be made if the dilution effect or other practical factors are taken into consideration. The proposed method will be particularly useful for the early detection of infectious diseases and prevention of future pandemics. The proposed work will have broader impacts on medical testing for contagious diseases in general.

A study on depression of the elderly with different sleep quality in pension institutions in Northeastern China.

BACKGROUND: China owns he largest aged population in the world, and the elderly adults who live in pension institutions are more likely to suffer from mental disorders than other elderly adults. The purpose of this study is to discover the risky factors of depression among nursing home residents with various sleeping quality. METHODS: We conducted a cross-sectional study in Northeastern China from May to September in 2017 using multistage sampling method and 507 elderly people without cognitive impairment in six pension institutions were interviewed. The Pittsburgh Sleep Quality Index (PSQI) and Geriatric Depression Scale (GDS) were adopted to collect the information of sleep quality and depression. We used logistic regression to analyze the factors influencing depression among the elderly adults with poor or good sleep quality. RESULTS: The overall depression rate among elderly adults was 21.7%. The logistic regression analysis revealed that marital status, chronic disease, regular exercise, physical ache, filial piety and chewing ability had significant effects on the depression of the elderly with good sleep quality. Loneliness, self-caring ability, chewing ability and chronic diseases had significant effects on depression of the elderly with poor sleep quality. CONCLUSION: The prevalence of depressive symptoms in the elderly is not high. However, sleeping quality distinguishes root causes on elderly adults depression. Therefore, the risk factors of depression among elderly adults should be analyzed separately.

Development and evaluation of a multimodal marker of major depressive disorder.

This study aimed to identify biomarkers of major depressive disorder (MDD), by relating neuroimage-derived measures to binary (MDD/control), ordinal (severe MDD/mild MDD/control), or continuous (depression severity) outcomes. To address MDD heterogeneity, factors (severity of psychic depression, motivation, anxiety, psychosis, and sleep disturbance) were also used as outcomes. A multisite, multimodal imaging (diffusion MRI [dMRI] and structural MRI [sMRI]) cohort (52 controls and 147 MDD patients) and several modeling techniques-penalized logistic regression, random forest, and support vector machine (SVM)-were used. An additional cohort (25 controls and 83 MDD patients) was used for validation. The optimally performing classifier (SVM) had a 26.0% misclassification rate (binary), 52.2 ± 1.69% accuracy (ordinal) and r = .36 correlation coefficient (p < .001, continuous). Using SVM, R2 values for prediction of any MDD factors were <10%. Binary classification in the external data set resulted in 87.95% sensitivity and 32.00% specificity. Though observed classification rates are too low for clinical utility, four image-based features contributed to accuracy across all models and analyses-two dMRI-based measures (average fractional anisotropy in the right cuneus and left insula) and two sMRI-based measures (asymmetry in the volume of the pars triangularis and the cerebellum) and may serve as a priori regions for future analyses. The poor accuracy of classification and predictive results found here reflects current equivocal findings and sheds light on challenges of using these modalities for MDD biomarker identification. Further, this study suggests a paradigm (e.g., multiple classifier evaluation with external validation) for future studies to avoid nongeneralizable results.

GLP-1/GLP-1RAs: New Options for the Drug Treatment of NAFLD.

Non-alcoholic fatty liver disease (NAFLD) has recently emerged as a global public health concern. Currently, the cornerstone of NAFLD treatment is lifestyle modification and, if necessary, weight loss. However, compliance is a challenge, and this approach alone may not be sufficient to halt and treat the more serious disease development, so medication is urgently needed. Nevertheless, no medicines are approved to treat NAFLD. Glucagon-like peptide-1 (GLP-1) is an enteropeptide hormone that inhibits glucagon synthesis, promotes insulin secretion, and delays gastric emptying. GLP-1 has been found in recent studies to be beneficial for the management of NAFLD, and the marketed GLP-1 agonist drugs have different degrees of effectiveness for NAFLD while lowering blood glucose. In this article, we review GLP-1 and its physiological roles, the pathogenesis of NAFLD, the correlation between NAFLD and GLP-1 signaling, and potential strategies for GLP-1 treatment of NAFLD.

ComCo: Complementary supervised contrastive learning for complementary label learning.

Complementary label learning (CLL) is an important problem that aims to reduce the cost of obtaining large-scale accurate datasets by only allowing each training sample to be equipped with labels the sample does not belong. Despite its promise, CLL remains a challenging task. Previous methods have proposed new loss functions or introduced deep learning-based models to CLL, but they mostly overlook the semantic information that may be implicit in the complementary labels. In this work, we propose a novel method, ComCo, which leverages a contrastive learning framework to assist CLL. Our method includes two key strategies: a positive selection strategy that identifies reliable positive samples and a negative selection strategy that skillfully integrates and leverages the information in the complementary labels to construct a negative set. These strategies bring ComCo closer to supervised contrastive learning. Empirically, ComCo significantly achieves better representation learning and outperforms the baseline models and the current state-of-the-art by up to 14.61% in CLL.

The INSIGHT platform: Enhancing NAD(P)-dependent specificity prediction for co-factor specificity engineering.

Enzyme specificity towards cofactors like NAD(P)H is crucial for applications in bioremediation and eco-friendly chemical synthesis. Despite their role in converting pollutants and creating sustainable products, predicting enzyme specificity faces challenges due to sparse data and inadequate models. To bridge this gap, we developed the cutting-edge INSIGHT platform to enhance the prediction of coenzyme specificity in NAD(P)-dependent enzymes. INSIGHT integrates extensive data from principal bioinformatics resources, concentrating on both NADH and NADPH specificities, and utilizes advanced protein language models to refine the predictions. This integration not only strengthens computational predictions but also meets the practical demands of high-throughput screening and optimization. Experimental validation confirms INSIGHT's effectiveness, boosting our ability to engineer enzymes for efficient, sustainable industrial and environmental processes. This work advances the practical use of computational tools in enzyme research, addressing industrial needs and offering scalable solutions for environmental challenges.

SLInterpreter: An Exploratory and Iterative Human-AI Collaborative System for GNN-based Synthetic Lethal Prediction.

Synthetic Lethal (SL) relationships, though rare among the vast array of gene combinations, hold substantial promise for targeted cancer therapy. Despite advancements in AI model accuracy, there is still a significant need among domain experts for interpretive paths and mechanism explorations that align better with domain-specific knowledge, particularly due to the high costs of experimentation. To address this gap, we propose an iterative Human-AI collaborative framework with two key components: 1) HumanEngaged Knowledge Graph Refinement based on Metapath Strategies, which leverages insights from interpretive paths and domain expertise to refine the knowledge graph through metapath strategies with appropriate granularity. 2) Cross-Granularity SL Interpretation Enhancement and Mechanism Analysis, which aids experts in organizing and comparing predictions and interpretive paths across different granularities, uncovering new SL relationships, enhancing result interpretation, and elucidating potential mechanisms inferred by Graph Neural Network (GNN) models. These components cyclically optimize model predictions and mechanism explorations, enhancing expert involvement and intervention to build trust. Facilitated by SLInterpreter, this framework ensures that newly generated interpretive paths increasingly align with domain knowledge and adhere more closely to real-world biological principles through iterative Human-AI collaboration. We evaluate the framework's efficacy through a case study and expert interviews.