TRIM21 induces selective autophagic degradation of c-Myc and sensitizes regorafenib therapy in colorectal cancer.

Kirsten rat sarcoma virus (KRAS) mutation is associated with malignant tumor transformation and drug resistance. However, the development of clinically effective targeted therapies for KRAS-mutant cancer has proven to be a formidable challenge. Here, we report that tripartite motif-containing protein 21 (TRIM21) functions as a target of extracellular signal-regulated kinase 2 (ERK2) in KRAS-mutant colorectal cancer (CRC), contributing to regorafenib therapy resistance. Mechanistically, TRIM21 directly interacts with and ubiquitinates v-myc avian myelocytomatosis viral oncogene homolog (c-Myc) at lysine 148 (K148) via K63-linkage, enabling c-Myc to be targeted to the autophagy machinery for degradation, ultimately resulting in the downregulation of enolase 2 expression and inhibition of glycolysis. However, mutant KRAS (KRAS/MT)-driven mitogen-activated protein kinase (MAPK) signaling leads to the phosphorylation of TRIM21 (p-TRIM21) at Threonine 396 (T396) by ERK2, disrupting the interaction between TRIM21 and c-Myc and thereby preventing c-Myc from targeting autophagy for degradation. This enhances glycolysis and contributes to regorafenib resistance. Clinically, high p-TRIM21 (T396) is associated with an unfavorable prognosis. Targeting TRIM21 to disrupt KRAS/MT-driven phosphorylation using the antidepressant vilazodone shows potential for enhancing the efficacy of regorafenib in treating KRAS-mutant CRC in preclinical models. These findings are instrumental for KRAS-mutant CRC treatment aiming at activating TRIM21-mediated selective autophagic degradation of c-Myc.

The role of pattern recognition receptors in the innate immune system of Chinese mitten crab (Eriocheir sinensis).

Eriocheir sinensis (Chinese mitten crab) is one of the main economic species in China, which has evolved an extremely sophisticated innate immune system to fend off disease invasions. However, bacterial and viral infections have caused significant financial losses for the E. sinensis aquaculture in recent years. Making well-informed judgments for the control microbial infections would require a thorough understanding and clarification of the intricate innate immune system of E. sinensis. Innate immunity is essential for the host's defense against invasive pathogens. Pattern recognition receptors (PRRs) initially recognize pathogen-associated molecular patterns (PAMPs) and trigger an innate immune response, causing the generation of inflammatory cytokine and promoting the clearance and control of pathogens. In E. sinensis, Toll/Toll-like receptors, lipopolysaccharide and ß-1,3-glucan binding proteins, C-type lectins, galactoside-binding lectins, L-type lectins, scavenger receptors, and down syndrome cell adhesion molecules have been identified to be PRRs that are involved in the recognition of bacteria, fungi, and viruses. In this review, we give a comprehensive overview of the literature regarding PRRs' roles in the immunological defenses of E. sinensis, with the aim of providing clues to the mechanisms of innate immunity.

Δ-Machine Learning to Elevate DFT-Based Potentials and a Force Field to the CCSD(T) Level Illustrated for Ethanol.

Progress in machine learning has facilitated the development of potentials that offer both the accuracy of first-principles techniques and vast increases in the speed of evaluation. Recently, Δ-machine learning has been used to elevate the quality of a potential energy surface (PES) based on low-level, e.g., density functional theory (DFT) energies and gradients to close to the gold-standard coupled cluster level of accuracy. We have demonstrated the success of this approach for molecules, ranging in size from H3O+ to 15-atom acetyl-acetone and tropolone. These were all done using the B3LYP functional. Here, we investigate the generality of this approach for the PBE, M06, M06-2X, and PBE0 + MBD functionals, using ethanol as the example molecule. Linear regression with permutationally invariant polynomials is used to fit both low-level and correction PESs. These PESs are employed for standard RMSE analysis for training and test data sets, and then general fidelity tests such as energetics of stationary points, normal-mode frequencies, and torsional potentials are examined. We achieve similar improvements in all cases. Interestingly, we obtained significant improvement over DFT gradients where coupled cluster gradients were not used to correct the low-level PES. Finally, we present some results for correcting a recent molecular mechanics force field for ethanol and comment on the possible generality of this approach.

DFT-Based Permutationally Invariant Polynomial Potentials Capture the Twists and Turns of C14H30.

Hydrocarbons are ubiquitous as fuels, solvents, lubricants, and as the principal components of plastics and fibers, yet our ability to predict their dynamical properties is limited to force-field mechanics. Here, we report two machine-learned potential energy surfaces (PESs) for the linear 44-atom hydrocarbon C14H30 using an extensive data set of roughly 250,000 density functional theory (DFT) (B3LYP) energies for a large variety of configurations, obtained using MM3 direct-dynamics calculations at 500, 1000, and 2500 K. The surfaces, based on Permutationally Invariant Polynomials (PIPs) and using both a many-body expansion approach and a fragmented-basis approach, produce precise fits for energies and forces and also produce excellent out-of-sample agreement with direct DFT calculations for torsional and dihedral angle potentials. Going beyond precision, the PESs are used in molecular dynamics calculations that demonstrate the robustness of the PESs for a large range of conformations. The many-body PIPs PES, although more compute intensive than the fragmented-basis one, is directly transferable for other linear hydrocarbons.

Dose-response relationship between body mass index and hypertension: A cross-sectional study from Eastern China.

Background: A high body mass index (BMI) increases the risk of hypertension. However, little is known about the dose-dependent association between BMI and hypertension. Therefore, this study investigated the prevalence of hypertension in 7568 subjects from the Jiangsu Province, Eastern China, and analyzed the dose-response relationship between BMI and hypertension risk. Methods: The eligible subjects completed a structured questionnaire and clinical biochemical indicators were measured according to standardized protocols. Multivariate logistic regression models were used to evaluate the association between BMI and hypertension. Restricted cubic spline (RCS) analysis was used to analyze the dose-response relationship between BMI and hypertension risk. Moreover, sensitivity analysis was performed to verify the robustness of our findings. Results: The prevalence of hypertension was 35.3 % in the total population. BMI was significantly associated with systolic and diastolic blood pressure. The fully-adjusted odds ratio (OR) with 95 % confidence interval (CI) for hypertension was 1.17 (1.15, 1.19) for every 1 kg/m2 increase in BMI. Furthermore, the OR (95 % CI) for hypertension in the highest BMI group (Obesity) was 4.14 (3.45, 4.96) after adjusting for covariates compared with the normal group. Multivariable adjusted RCS analysis showed a positive and linear dose-response relationship between BMI and hypertension risk both in male and female populations (all P for non-linearity > 0.05). Conclusion: Our study demonstrated a positive and linear dose-response relationship between BMI and the risk of hypertension. The results of this study provide evidence for BMI-related clinical interventions to reduce the risk of hypertension.

Diagnostic Value of Artificial Intelligence in Minimal Breast Lesions Based on Real-Time Dynamic Ultrasound Imaging.

Purpose: : To explore the diagnostic value of artificial intelligence (AI)-based on real-time dynamic ultrasound imaging system for minimal breast lesions. Patients and Methods: Minimal breast lesions with a maximum diameter of ≤10mm were selected in this prospective study. The ultrasound equipment and AI system were activated Simultaneously. The ultrasound imaging video is connected to the server of AI system to achieve simultaneous output of AI and ultrasound scanning. Dynamic observation of breast lesions was conducted via ultrasound. And these lesions were evaluated and graded according to the Breast Imaging Reporting and Data System (BI-RADS) classification system through deep learning (DL) algorithms in AI. Surgical pathology was taken as the gold standard, and ROC curves were drawn to determine the area under the curve (AUC) and the optimal threshold values of BI-RADS. The diagnostic efficacy was compared with the use of a BI-RADS category >3 as the threshold for clinically intervening in diagnosing minimal breast cancers. Results: 291 minimal breast lesions were enrolled in the study, of which 228 were benign (78.35%) and 63 were malignant (21.65%). The AUC of the ROC curve was 0.833, with the best threshold value >4A. When using >BI-RADS 3 and >BI-RADS 4A as threshold values, the sensitivity and negative predictive value for minimal breast cancers were higher for >BI-RADS 3 than >BI-RADS 4A (100% vs 65.08%, 100% vs 89.91%, P values <0.001). However, the corresponding specificity, positive predictive value, and accuracy were lower than those for >BI-RADS 4A (42.11% vs 85.96%, 32.31% vs 56.16%, and 54.64% vs 81.44%, P values <0.001). Conclusion: The AI-based real-time dynamic ultrasound imaging system shows good capacity in diagnosing minimal breast lesions, which is helpful for early diagnosis and treatment of breast cancer, and improves the prognosis of patients. However, it still results in some missed diagnoses and misdiagnoses of minimal breast cancers.

Calculations of Dissociation Dynamics of CH3OH on a Global Potential Energy Surface Reveal the Mechanism for the Formation of HCOH; Roaming Plays a Role.

The experimental observation of hydroxymethylene, HCOH, following excitation of methanol at 193 nm, was reported recently (Hockey, E. K.; McLane, N.; Martí, C.; Duckett, L.; Osborn, D. L.; Dodson, L. G. Direct Observation of Gas-Phase Hydroxymethylene: Photoionization and Kinetics Resulting from Methanol Photodissociation. J. Am. Chem. Soc. 2024, 146, 14416-14421, 10.1021/jacs.4c03090). This stimulated us to investigate a dynamic mechanism for its formation using a global potential energy surface for the ground electronic state (S0) of methanol. We show via quasi-classical trajectory calculations that hydroxymethylene is indeed formed under the reasonable assumption that the initially excited state undergoes rapid internal conversion to S0. From the trajectories, fractional yields of the six major product channels are determined as a function of excitation energy, and the rate of production of each is determined from the fractions and rate of methanol disappearance. Roaming is observed in trajectories leading to the OH and CH3 products as well as in those leading to CH2OH + H and non-reactive trajectories. A "frustrated" roaming accounts for roughly 20% of the HCOH production.

Evaluation of adapted parent training for challenging behaviour in pre-school children with moderate to severe intellectual developmental disabilities: A randomised controlled trial.

OBJECTIVES: There is limited evidence on the effectiveness of parenting interventions to improve disruptive behaviour in children with intellectual developmental disabilities. This clinical trial evaluated whether an adapted group parenting intervention for preschool children with intellectual developmental disabilities who display challenging behaviour is superior to treatment as usual in England. STUDY DESIGN: 261 children aged 30-59 months with moderate to severe intellectual developmental disabilities and challenging behaviour were randomised to either the intervention (Stepping Stones Triple P) and treatment as usual or treatment as usual alone. The primary outcome was the parent-rated Child Behaviour Checklist at 52 weeks after randomisation. A health economic evaluation was also completed. RESULTS: We found no significant difference between arms on the primary outcome (mean difference -4.23; 95% CI: -9.99 to 1.53; p = 0.147). However, a subgroup analysis suggests the intervention was effective for participants randomised before the COVID-19 pandemic (mean difference -7.12; 95% CI: -13.44 to -0.81; p = 0.046). Furthermore, a complier average causal effects analysis (mean difference -11.53; 95% CI: -26.97 to 3.91; p = 0.143) suggests the intervention requires participants to receive a sufficient intervention dose. The intervention generated statistically significant cost savings (-£1,057.88; 95% CI -£3,218.6 to -£46.67) but the mean point estimate in Quality Adjusted Life Years was similar in both groups. CONCLUSION: This study did not find an effect of the intervention on reducing challenging behaviour, but this may have been influenced by problems with engagement. The intervention could be considered by services as an early intervention if families are supported to attend, especially given its low cost.

Asymmetric Adaption in Social Learning: Understanding the Dilemma of Competition and Cooperation.

The constant challenge in social interactions involves making informed decisions in the face of competitive and cooperative dilemmas. The decision-making process can be influenced by various factors present in the social context. According to the behavior-pattern-categorization framework of information acquisition, potential biases may develop at all stages of decision-making as information about social context is progressively entered and integrated. In this study, employing the Chicken Game, we investigated the influence of varying information levels within the behavior-pattern-categorization framework (i.e., competitiveness of behavior choice, uncertainty of behavior pattern, and sociality of category) on decision-making in the dilemma of competition and cooperation. Combined with reinforcement learning models, our findings from three experiments showed that participants exhibited basic complementary behavior, becoming less competitive against highly competitive opponents and vice versa. Notably, individuals exhibited varying adaptation rates to different levels of opponent competitiveness and fluctuations. Specifically, participants adapted slower to highly competitive opponents and faster to cooperative opponents. This asymmetric adaptation in social learning is related to the rate at which various levels of information are updated. The current study disentangles the different levels of information acquisition and highlights the asymmetric processing that can occur during the updating of information within each level.

Highly sensitive and selective electrochemical biosensor using odorant-binding protein to detect aldehydes.

Recently, various biosensors based on odorant-binding proteins (OBPs) were developed for the detection of odorants and pheromones. However, important data gaps exist regarding the sensitive and selective detection of aldehydes with various carbon numbers. In this work, an OBP2a-based electrochemical impedance spectroscopy (EIS) biosensor was developed by immobilizing OBP2a on a gold interdigital electrode, and was characterized by EIS and atomic force microscopy. EIS responses showed the OBP2a-based biosensor was highly sensitive to citronellal, lily aldehyde, octanal, and decanal (detection limit of 10-11 mol/L), and was selective towards aldehydes compared with interfering odorants such as small-molecule alcohols and fatty acids (selectivity coefficients lower than 0.15). Moreover, the OBP2a-based biosensor exhibited high repeatability (relative standard deviation: 1.6%-9.1 %, n = 3 for each odorant), stability (NIC declined by 3.6 % on 6th day), and recovery (91.2%-96.6 % on three real samples). More specifically, the sensitivity of the biosensor to aldehydes was positively correlated to the molecular weight and the heterocyclic molecule structure of the odorants. These results proved the availability and the potential usage of the OBP2a-based EIS biosensor for the rapid and sensitive detection of aldehydes in aspects such as medical diagnostics, food and favor analysis, and environmental monitoring.

An evaluation of sample size requirements for developing risk prediction models with binary outcomes.

BACKGROUND: Risk prediction models are routinely used to assist in clinical decision making. A small sample size for model development can compromise model performance when the model is applied to new patients. For binary outcomes, the calibration slope (CS) and the mean absolute prediction error (MAPE) are two key measures on which sample size calculations for the development of risk models have been based. CS quantifies the degree of model overfitting while MAPE assesses the accuracy of individual predictions. METHODS: Recently, two formulae were proposed to calculate the sample size required, given anticipated features of the development data such as the outcome prevalence and c-statistic, to ensure that the expectation of the CS and MAPE (over repeated samples) in models fitted using MLE will meet prespecified target values. In this article, we use a simulation study to evaluate the performance of these formulae. RESULTS: We found that both formulae work reasonably well when the anticipated model strength is not too high (c-statistic < 0.8), regardless of the outcome prevalence. However, for higher model strengths the CS formula underestimates the sample size substantially. For example, for c-statistic = 0.85 and 0.9, the sample size needed to be increased by at least 50% and 100%, respectively, to meet the target expected CS. On the other hand, the MAPE formula tends to overestimate the sample size for high model strengths. These conclusions were more pronounced for higher prevalence than for lower prevalence. Similar results were drawn when the outcome was time to event with censoring. Given these findings, we propose a simulation-based approach, implemented in the new R package 'samplesizedev', to correctly estimate the sample size even for high model strengths. The software can also calculate the variability in CS and MAPE, thus allowing for assessment of model stability. CONCLUSIONS: The calibration and MAPE formulae suggest sample sizes that are generally appropriate for use when the model strength is not too high. However, they tend to be biased for higher model strengths, which are not uncommon in clinical risk prediction studies. On those occasions, our proposed adjustments to the sample size calculations will be relevant.

Characterization of DmToll and DmToll7 homologue in Litopenaeus vannamei based on structure analysis.

Toll-like receptors (TLRs) are a family of pattern recognition receptors (PRRs) that recognize invading pathogens and activate downstream signaling pathways. The number of 10 Tolls is found in Litopenaeus vannamei but have not yet been identified as the corresponding Toll homologue of model animal. In this study, we predicted the three-dimensional (3D) structures of 10 LvTolls (LvToll1-10) with AlphaFold2 program. The per-residue local distance difference test (pLDDT) scores of LvTolls showed the predicted structure of LvTolls had high accuracy (pLDDT>70). By structural analysis, 3D structures of LvToll2 and LvToll3 had high similarity with Drosophila melanogaster Toll and Toll7, respectively. 3D structure of LvToll7 and LvToll10 were not similar to that of other LvTolls. Moreover, we also predicted that LvSpätzle4 had high structural similarity to DmSpätzle. There were 9 potential hydrogen bonds in LvToll2-LvSpätzle4 complex. Importantly, co-immunoprecipitation assay showed that LvToll2 could bind with LvSpätzle4. Collectively, this study provides new insight for researching invertebrate immunity by identifying the protein of model animal homologue.

Association between oxidative balance score and heart failure in the older adults: Results from the NHANES 2005-2018.

BACKGROUND: Heart failure (HF) imposes a substantial burden on older adults, and healthy diets and lifestyles may bring with benefits. However, quantifiable studies on the dietary and lifestyle risk factors for HF are scant. The Oxidative Balance Score (OBS) reflects the oxidative stress status of dietary components and lifestyle factors, but its relationship with HF risk is unclear. OBJECTIVE: We aims to explore the association between OBS and the prevalence of HF. METHODS: Using data from the National Health and Nutrition Examination Survey (NHANES) 2005-2018, the association between OBS and the HF prevalence was analyzed by weighted logistic regression and restricted cubic splines (RCS). Subgroup and sensitivity analyses assessed the stability of the results. RESULTS: The prevalence of HF in the cohort of 6238 older adults was 5.55 %. Compared to the lowest quintile, the adjusted ORs for HF in the highest quintile of OBS and lifestyle OBS were 0.57 (95 % CI: 0.33,0.97) and 0.21 (95 %CI: 0.09,0.50), respectively. The association between OBS and HF prevalence remained stable across different models and subgroups. RCS revealed a potential inflection point. Sensitivity analysis validated the negative association between OBS and HF prevalence, and the correlation analysis between OBS and serum γ-glutamyltransferase (γ-GGT) confirmed the reliability of the study design. CONCLUSION: The OBS is negatively associated with HF prevalence in older adults, and may help prevent HF in this population.

Ubiquitin Ligase RBX2/SAG Regulates Mitochondrial Ubiquitination and Mitophagy.

BACKGROUND: Clearance of damaged mitochondria via mitophagy is crucial for cellular homeostasis. Apart from Parkin, little is known about additional Ub (ubiquitin) ligases that mediate mitochondrial ubiquitination and turnover, particularly in highly metabolically active organs such as the heart. METHODS: In this study, we have combined in silico analysis and biochemical assay to identify CRL (cullin-RING ligase) 5 as a mitochondrial Ub ligase. We generated cardiomyocytes and mice lacking RBX2 (RING-box protein 2; also known as SAG [sensitive to apoptosis gene]), a catalytic subunit of CRL5, to understand the effects of RBX2 depletion on mitochondrial ubiquitination, mitophagy, and cardiac function. We also performed proteomics analysis and RNA-sequencing analysis to define the impact of loss of RBX2 on the proteome and transcriptome. RESULTS: RBX2 and CUL (cullin) 5, 2 core components of CRL5, localize to mitochondria. Depletion of RBX2 inhibited mitochondrial ubiquitination and turnover, impaired mitochondrial membrane potential and respiration, increased cardiomyocyte cell death, and has a global impact on the mitochondrial proteome. In vivo, deletion of the Rbx2 gene in adult mouse hearts suppressed mitophagic activity, provoked accumulation of damaged mitochondria in the myocardium, and disrupted myocardial metabolism, leading to the rapid development of dilated cardiomyopathy and heart failure. Similarly, ablation of RBX2 in the developing heart resulted in dilated cardiomyopathy and heart failure. The action of RBX2 in mitochondria is not dependent on Parkin, and Parkin gene deletion had no impact on the onset and progression of cardiomyopathy in RBX2-deficient hearts. Furthermore, RBX2 controls the stability of PINK1 (PTEN-induced kinase 1) in mitochondria. CONCLUSIONS: These findings identify RBX2-CRL5 as a mitochondrial Ub ligase that regulates mitophagy and cardiac homeostasis in a Parkin-independent, PINK1-dependent manner.

Common neural dysfunction of economic decision-making across psychiatric conditions.

Adaptive decision-making, which is often impaired in various psychiatric conditions, is essential for well-being. Recent evidence has indicated that decision-making capacity in multiple tasks could be accounted for by latent dimensions, enlightening the question of whether there is a common disruption of brain networks in economic decision-making across psychiatric conditions. Here, we addressed the issue by combining activation/lesion network mapping analyses with a transdiagnostic brain imaging meta-analysis. Our findings indicate that there were transdiagnostic alterations in the thalamus and ventral striatum during the decision or outcome stage of decision-making. The identified regions represent key nodes in a large-scale network, which is composed of multiple heterogeneous brain regions and plays a causal role in motivational functioning. The findings suggest that disturbances in the network associated with emotion- and reward-related processing play a key role in dysfunctions of decision-making observed in various psychiatric conditions. This study provides the first meta-analytic evidence of common neural alterations linked to deficits in economic decision-making.

Identification and characterization of a TLR4 homologue in Eriocheir sinensis based on structure analysis.

Toll-like receptor 4 (TLR4) plays an essential role in the activation of innate immunity by recognizing diverse pathogenic components of bacteria. Six Tolls were found in Eriocheir sinensis but have not yet been identified as mammalian TLR4 homolog. For this purpose, we predicted three-dimensional (3D) structures of EsTolls (EsToll1-6) with AlphaFold2. 3D structure of LRRs and TIR most had high accuracy (pLDDT >70). By structure analysis, 3D structures of EsToll6 had a high overlap with HsTLR4. Moreover, we also predicted potential 11 hydrogen bonds and 3 salt bridges in the 3D structure of EsToll6-EsML1 complex. 18 hydrogen bonds and 7 salt bridges were predicted in EsToll6-EsML2 complex. Co-immunoprecipitation assay showed that EsToll6 could interact with EsML1 and EsML2, respectively. Importantly, TAK242 (a mammalian TLR4-specific inhibitor) could inhibit the generation of ROS stimulated by lipopolysaccharides (LPS) in EsToll6-EsML2-overexpression Hela cells. Collectively, these results implied that EsToll6 was a mammalian TLR4 homolog and provided a new insight for researching mammalian homologs in invertebrates.

Alteration Trend and Overlap Analysis of Positive Features in Different-Sized Benign and Malignant Thyroid Nodules: Based on Chinese Thyroid Imaging Reporting and Data System.

Purpose: This study aimed to investigate the alteration trends and overlaps of positive features in benign and malignant thyroid nodules of different sizes based on the Chinese Thyroid Imaging Reporting and Data System (C-TIRADS). Patients and Methods: 1337 patients with 1558 thyroid nodules were retrospectively recruited from November 2021 to December 2023. These nodules were divided into three groups according to maximum diameter: A (≤10 mm), B (10-20 mm), and C (≥20 mm). C-TIRADS positive features were compared between benign and malignant thyroid nodules of different sizes. In addition, the trends of positive features with changes in nodule size among malignant thyroid nodules were analyzed. Results: The incidence of positive features in malignant thyroid nodules was higher than that in benign. As benign nodules grow, the incidence of all positive features showed a linear decreasing trend (Z values were 72.103, 101.081, 17.344, 33.909, and 129.304, P values < 0.001). With the size of malignant thyroid nodules increased, vertical orientation, solid, marked hypoechogenicity, and ill-defined/irregular margins/extrathyroidal extension showed a linear decreasing trend (Z = 148.854, 135.378, 8.590, and 69.239, respectively; P values < 0.05), while suspicious microcalcifications showed a linear increasing trend (Z = 34.699, P<0.001). In terms of overlapping characteristics, group A had a significantly higher overlapping rate than the other two groups, and the overlapping rate of solid indicators remained the highest among all three groups (P < 0.05). Conclusion: Differences in positive features were observed between thyroid nodules of different sizes. Except for suspicious microcalcifications, the incidence of other four positive features decreased with increasing nodule size. In addition, a negative correlation was observed between the overlap rate and nodule size. These results may provide a basis for sonographers to upgrade or downgrade thyroid nodules based on their own experience.

Assessing Permutationally Invariant Polynomial and Symmetric Gradient Domain Machine Learning Potential Energy Surfaces for H3O2.

The singly hydrated hydroxide anion OH-(H2O) is of central importance to a detailed molecular understanding of water; therefore, there is strong motivation to develop a highly accurate potential to describe this anion. While this is a small molecule, it is necessary to have an extensive data set of energies and, if possible, forces to span several important stationary points. Here, we assess two machine-learned potentials, one using the symmetric gradient domain machine learning (sGDML) method and one based on permutationally invariant polynomials (PIPs). These are successors to a PIP potential energy surface (PES) reported in 2004. We describe the details of both fitting methods and then compare the two PESs with respect to precision, properties, and speed of evaluation. While the precision of the potentials is similar, the PIP PES is much faster to evaluate for energies and energies plus gradient than the sGDML one. Diffusion Monte Carlo calculations of the ground vibrational state, using both potentials, produce similar large anharmonic downshift of the zero-point energy compared to the harmonic approximation of the PIP and sGDML potentials. The computational time for these calculations using the sGDML PES is roughly 300 times greater than using the PIP one.

DB-1310, an ADC comprised of a novel anti-HER3 antibody conjugated to a DNA topoisomerase I inhibitor, is highly effective for the treatment of HER3-positive solid tumors.

BACKGROUND: HER3 (ErbB3), a member of the human epidermal growth factor receptor family, is frequently overexpressed in various cancers. Multiple HER3-targeting antibodies and antibody-drug conjugates (ADCs) were developed for the solid tumor treatment, however none of HER3-targeting agent has been approved for tumor therapy yet. We developed DB-1310, a HER3 ADC composed of a novel humanized anti-HER3 monoclonal antibody covalently linked to a proprietary DNA topoisomerase I inhibitor payload (P1021), and evaluate the efficacy and safety of DB-1310 in preclinical models. METHODS: The binding of DB-1310 to Her3 and other HER families were measured by ELISA and SPR. The competition of binding epitope for DB-1310 and patritumab was tested by FACS. The sensitivity of breast, lung, prostate and colon cancer cell lines to DB-1310 was evaluated by in vitro cell killing assay. In vivo growth inhibition study evaluated the sensitivity of DB-1310 to Her3 + breast, lung, colon and prostate cancer xenograft models. The safety profile was also measured in cynomolgus monkey. RESULTS: DB-1310 binds HER3 via a novel epitope with high affinity and internalization capacity. In vitro, DB-1310 exhibited cytotoxicity in numerous HER3 + breast, lung, prostate and colon cancer cell lines. In vivo studies in HER3 + HCC1569 breast cancer, NCI-H441 lung cancer and Colo205 colon cancer xenograft models showed DB-1310 to have dose-dependent tumoricidal activity. Tumor suppression was also observed in HER3 + non-small cell lung cancer (NSCLC) and prostate cancer patient-derived xenograft (PDX) models. Moreover, DB-1310 showed stronger tumor growth-inhibitory activity than patritumab deruxtecan (HER3-DXd), which is another HER3 ADC in clinical development at the same dose. The tumor-suppressive activity of DB-1310 synergized with that of EGFR tyrosine kinase inhibitor, osimertinib, and exerted efficacy also in osimertinib-resistant PDX model. The preclinical assessment of safety in cynomolgus monkeys further revealed DB-1310 to have a good safety profile with a highest non severely toxic dose (HNSTD) of 45 mg/kg. CONCLUSIONS: These finding demonstrated that DB-1310 exerted potent antitumor activities against HER3 + tumors in in vitro and in vivo models, and showed acceptable safety profiles in nonclinical species. Therefore, DB-1310 may be effective for the clinical treatment of HER3 + solid tumors.

Recent Progress on Conversion of Lignocellulosic Biomass by MOF-Immobilized Enzyme.

The enzyme catalysis conversion of lignocellulosic biomass into valuable chemicals and fuels showed a bright outlook for replacing fossil resources. However, the high cost and easy deactivation of free enzymes restrict the conversion process. Immobilization of enzymes in metal-organic frameworks (MOFs) is one of the most promising strategies due to MOF materials' tunable building units, multiple pore structures, and excellent biocompatibility. Also, MOFs are ideal support materials and could enhance the stability and reusability of enzymes. In this paper, recent progress on the conversion of cellulose, hemicellulose, and lignin by MOF-immobilized enzymes is extensively reviewed. This paper focuses on the immobilized enzyme performances and enzymatic mechanism. Finally, the challenges of the conversion of lignocellulosic biomass by MOF-immobilized enzyme are discussed.