[Spatial and Temporal Evolution Characteristics of Carbon Emission from Land Use and Influencing Factors in Gansu Province].

Land ecosystems are the largest carbon sink in the world, and land use change is one of the main factors leading to regional carbon emissions. By studying the spatiotemporal evolution characteristics and influencing factors of land use carbon emissions in Gansu Province from 2000 to 2020, this research aimed to provide a scientific basis and reference for promoting low-carbon land use and low-carbon economic development in Gansu Province. Using land use data and the greenhouse gas emission coefficient method, the study analyzed the growth trend of land use carbon emissions at the city-regional scale in Gansu Province, and the spatiotemporal evolution characteristics at the provincial scale, and identified the controlling factors through principal component analysis. The results showed that： ① From 2000 to 2020, land use carbon emissions in Gansu Province showed an overall increasing trend, from 24.289 3 million tons to 57.739 6 million tons. The first stage from 2000 to 2014 was a significant increase period, whereas the second stage from 2014 to 2020 was a stable and slightly decreasing period. Construction land was the main carbon source, and the carbon intensity continued to increase. ② Spatially, there was an "east high, west low" pattern, with carbon emissions in the eastern part of the province significantly higher than those in the western part. ③ Based on emission characteristics, Gansu Province could be divided into five types of carbon emission zones： slow growth, relatively slow growth, moderate growth, relatively fast growth, and rapid growth. ④ The main reasons for the continuous increase in land use carbon emissions in Gansu Province were economic development level, degree of land use, and energy consumption.

Adaptive Wiener process-based remaining useful life prediction method considering multi-source variability.

Existing remaining useful life (RUL) prediction methods considering multi-source variability were not applicable to the situation that the uneven measurement interval distribution and inconsistent measurement frequency of degrading equipment. This type of method also has ignored the variability of adaptive drift in the future degradation process. In view of this, based on adaptive Wiener process, the paper proposes a new nonlinear degradation method of the RUL prediction. Firstly, adopting the adaptive Wiener process, we have constructed the nonlinear degradation model with multi-source variability, which randomness of the parameters in the nonlinear function. Secondly, the real-time estimation of multiple hidden states can be realized by the particle filter algorithm. It has derived the RUL distribution in the sense of first hitting time. Using monitoring data of degrading equipment, the adaptive update of model parameters was implemented by expectation maximization algorithm. Finally, the effectiveness and superiority of the proposed model are validated through numerical simulation and lithium-ion battery experiments. The results show that it can effectively improve the prediction accuracy, which has potential application value.

Unveiling the complexity of rifampicin drug susceptibility testing in Mycobacterium tuberculosis: comparative analysis with next-generation sequencing.

Introduction. The discordance between phenotypic and molecular methods of rifampicin (RIF) drug susceptibility testing (DST) in Mycobacterium tuberculosis poses a significant challenge, potentially resulting in misdiagnosis and inappropriate treatment.Hypothesis/gap statement. A comparison of RIF phenotypic and molecular methods for DST, including whole genome sequencing (WGS), may provide a better understanding of resistance mechanisms.Aim. This study aims to compare RIF DST in M. tuberculosis using two phenotypic and molecular methods including the GeneXpert RIF Assay (GX) and WGS for better understanding.Methodology. The study evaluated two phenotypic liquid medium methods [Lowenstein-Jensen (LJ) and Mycobacterium Growth Indicator Tube (MGIT)], one targeted molecular method (GX), and one WGS method. Moreover, mutational frequency in ponA1 and ponA2 was also screened in the current and previous RIF resistance M. tuberculosis genomic isolates to find their compensatory role.Results. A total of 25 RIF-resistant isolates, including nine from treatment failures and relapse cases with both discordant and concordant DST results on LJ, MGIT and GX, were subjected to WGS. The phenotypic DST results indicated that 11 isolates (44%) were susceptible on LJ and MGIT but resistant on GX. These isolates exhibited multiple mutations in rpoB, including Thr444>Ala, Leu430>Pro, Leu430>Arg, Asp435>Gly, His445>Asn and Asn438>Lys. Conversely, four isolates that were susceptible on GX and MGIT but resistant on LJ were wild type for rpoB in WGS. However, these isolates possessed several novel mutations in the PonA1 gene, including a 10 nt insertion and two nonsynonymous mutations (Ala394>Ser, Pro631>Ser), as well as one nonsynonymous mutation (Pro780>Arg) in PonA2. The discordance rate of RIF DST is higher on MGIT than on LJ and GX when compared to WGS. These discordances in the Delhi/CAS lineages were primarily associated with failure and relapse cases.Conclusion. The WGS of RIF resistance is relatively expensive, but it may be considered for isolates with discordant DST results on MGIT, LJ and GX to ensure accurate diagnosis and appropriate treatment options.

Improving Delphi Process in Acupuncture Decision Making: Overall Descriptions and Quality Assessment of Delphi Reports.

Background: Clinical acupuncture decisions are highly operator-dependent and require physician-patient interactions. The Delphi method allows subjective factors such as expert experience and preference of patients to be taken into account in clinical decision making, which is particularly applicable to acupuncture. Currently, the Delphi method is widely used to support clinical decisions in acupuncture. Therefore, it is necessary to provide high-quality and complete descriptions of the Delphi process when making clinical decisions. This study aims to evaluate the quality of the Delphi process in acupuncture, facilitate its standardization and rigor for further clinical decision making in acupuncture. Methods: Articles sourced from six databases were searched systematically to assess the quality of the Delphi consensus process based on the standards for conducting and reporting Delphi studies (CREDES). Descriptive statistics and analysis were presented according to the percentage of each item. Five-score Likert scale was used to evaluate the reporting quality of four domains as well as each item in CREDES by two independent researchers, combined with ICC-value to assess the consistency. Results: A total of 37 qualified articles were included according to eligibility criteria. As for the low reporting rate, the item "External validation" was reported as the lowest positive rate at 32.43% and the item "Prevention of bias" was 48.65%. The item "Adequacy of conclusions", "Definition and attainment of consensus", and "Discussion of limitations" were reported at a positive ratio of 62.16%, 64.86%, and 67.57% individually. The average scores of the four domains based on CREDES from highest to lowest were, respectively, as follows: planning and design (68.75%), reporting (66.07%), rationale for the choice of the Delphi technique (65.54%), study conduct (45.10%). Conclusion: The reporting quality of the Delphi consensus process in acupuncture is acceptable currently, but the reporting rate on some items is still low. Further standardization, including either clearer checklists or study reports, should be developed and strengthened to guide clinical decisions in acupuncture.

Epinecidin-1 and lactic acid synergistically inhibit Aeromonas hydrophila through membrane disruption.

Epinecidin-1 (Epi-1) is an antimicrobial peptide originated from fish with various pharmacological activities but carries the risk of acquiring resistance with long-term use. In the present study, we use L-lactic acid to enhance the antibacterial activity of synthesized Epi-1 against the aquaculture and food pathogen Aeromonas hydrophila. The results showed that 5.5 mmol/L lactic acid increased the inhibitory and bactericidal activity of 25 µmol/L Epi-1 against two strains of A. hydrophila. The laser confocal images proved that lactic acid pre-treatment improved the attachment efficiency of Epi-1 in A.hydrophila cells. In addition, lactic acid enhanced the damaging effect of Epi-1 on the cell membrane of A. hydrophila, evidenced by releasing more nucleic acids, proteins, and transmembrane pH ingredients decrease and electromotive force dissipation. SEM images showed that compared with the single Epi-1 treatment, the co-treatment of Epi-1 and lactic acid caused more outer membrane vesicles (OMVs) and more severe cell deformation. These findings proved that lactic acid could enhance the efficiency of Epi-1 against A. hydrophila and shed light on new aspects to avoid resistance of pathogens against Epi-1.

Unveiling the Therapeutic Potential of Paclitaxel Combinations Against Breast Carcinoma and Identification of In Vivo Biomarkers.

Breast cancer (BC) is one of the leading causes of high mortality rates in women worldwide. Although advancements have been made in the design of therapeutic strategies and drug discovery, drug resistance remains one of the key challenges. One of the ways to overcome drug resistance is finding potential drug combinations since the efficacy of combined drugs is higher than their individual efficacies if the combination is a synergistic pair. Therefore, the current study uses a BC patient-derived xenograft (PDX) dataset to evaluate the effects of various cancer drugs on breast cancer in vivo models. The drug effects are further validated by four machine learning models, namely Elastic Net, Least Absolute Shrinkage and Selection (LASSO), Support Vector Machine (SVM), Random Forests (RF), as well as exploring the shortlisted drugs in combination with paclitaxel, a baseline drug for enhanced efficacy on tumor volume reduction. Additionally, the study also shortlists the top 50 in vivo biomarkers correlated with the effects of the drugs. The outcomes could be significantly important for the design of an effective anti-breast cancer therapy.

The Role of Indigenous Yeasts in Shaping the Chemical and Sensory Profiles of Wine: Effects of Different Strains and Varieties.

The microbial terroir is an indispensable part of the terroir panorama, and can improve wine quality with special characteristics. In this study, eight autochthonous yeasts (Saccharomyces cerevisiae), selected in Huailai country, China, were trailed in small-scale and pilot fermentations for both white (Riesling and Sémillon) and red (Cabernet Sauvignon and Syrah) wines and evaluated by GC-MS analysis and the rate-all-that-apply (RATA) method. Compared to commercial yeast strains, the indigenous yeasts were able to produce higher concentrations of ethyl esters and fatty acid ethyl esters, and higher alcohol, resulting in higher odor activity values of fruity, floral attributes. Marked varietal effects were observed in the pilot fermentation, but yeast strains exerted a noticeable impact in modulating wine aroma and sensory profile. Overall, indigenous yeast could produce more preferred aroma compounds and sensory characteristics for both white and red wines, demonstrating the potential for improving wine quality and regional characteristics.

Effects of herbal formula on growth performance, apparent digestibility, antioxidant capacity, and rumen microbiome in fattening lambs under heat stress.

Heat stress (HS) causes severe economic losses in sheep industry worldwide. The objective of the present study was to investigate the effects of a herbal formula (HF) supplement on growth, digestibility, antioxidant capacity, and rumen microbes in fattening lambs under HS. The HF composed of four herbs was prepared based on the theory of compatibility of Chinese medicine "Jun-Chen-Zuo-Shi". Two-hundred forty 3-month weaned lambs (initial weight 36.61 ± 0.73 kg) were randomly allocated into four groups, supplemented 0% (Control), 0.5%, 1.0%, and 1.5% HF in diets. All lambs were exposed to HS conditions with 79.7 of average temperature-humidity index throughout an experimental period of 35 days. Growth performance, apparent digestibility, and antioxidant activities, involving antioxidant enzymes and heat shock proteins (HSPs), were measured at the end of trial, as well as microbial communities in bacteria and archaea. Results showed that 0.5% HF increased (P = 0.02) average daily gain by 13.80% and decreased feed-to-gain ratio (P = 0.03) by 14.68%, compared to control. With increasing HF doses, the digestibility of ether extract and acid detergent fiber demonstrated a cubical (P < 0.01) and quadratic (P = 0.03) relation, respectively; moreover, glutathione peroxidase and catalase activities demonstrated a quadratic increase (P < 0.01). Serum levels of HSP60, HSP70, and HSP90 for 0.5% HF were lower than that in control (P < 0.05). On the other hand, total volatile fatty acid, acetic acid, butyric acid, valeric acid, and isovaleric acid levels exhibited quadratic increases (P ≤ 0.01) with HF doses. From rumen microbes, the abundance and diversity of bacterial community were improved by HF supplements. Particularly for 0.5% HF group, the operational taxonomic units were the greatest among all groups. Compared to control, Prevotella abundance for HF supplements from 0.5 to 1.5% increased by 35.57 to 60.15%, and Succiniclasticum abundance demonstrated a quadratic pattern (P = 0.02) with doses. Additionally, Methanosphaera abundance in archaeal community raised by 0.2 to 3.3-folds when lambs were fed the HF additions of 0.5 to 1.5%. In summary, dietary HF supplements would contribute to alleviating HS in lambs, and our results suggest the optimal dose of 0.5% HF supplement in diet.

Integrated structural proteomics and machine learning-guided mapping of a highly protective precision vaccine against mycoplasma pulmonis.

Mycoplasma pulmonis (M. pulmonis) is an emerging respiratory infection commonly linked to prostate cancer, and it is classified under the group of mycoplasmas. Improved management of mycoplasma infections is essential due to the frequent ineffectiveness of current antibiotic treatments in completely eliminating these pathogens from the host. The objective of this study is to design and construct effective and protective vaccines guided by structural proteomics and machine learning algorithms to provide protection against the M. pulmonis infection. Through a thorough examination of the entire proteome of M. pulmonis, four specific targets Membrane protein P80, Lipoprotein, Uncharacterized protein and GGDEF domain-containing protein have been identified as appropriate for designing a vaccine. The proteins underwent mapping of cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) (IFN)-γ ±, and B-cell epitopes using artificial and recurrent neural networks. The design involved the creation of mRNA and peptide-based vaccine, which consisted of 8 CTL epitopes associated by GGS linkers, 7 HTL (IFN-positive) epitopes, and 8 B-cell epitopes joined by GPGPG linkers. The vaccine designed exhibit antigenic behavior, non-allergenic qualities, and exceptional physicochemical attributes. Structural modeling revealed that correct folding is crucial for optimal functioning. The coupling of the MEVC and Toll-like Receptors (TLR)1, TLR2, and TLR6 was examined through molecular docking experiments. This was followed by molecular simulation investigations, which included binding free energy estimations. The results indicated that the dynamics of the interaction were stable, and the binding was strong. In silico cloning and optimization analysis revealed an optimized sequence with a GC content of 49.776 % and a CAI of 0.982. The immunological simulation results showed strong immune responses, with elevated levels of active and plasma B-cells, regulatory T-cells, HTL, and CTL in both IgM+IgG and secondary immune responses. The antigen was completely cleared by the 50th day. This study lays the foundation for creating a potent and secure vaccine candidate to combat the newly identified M. pulmonis infection in people.

Photomechanical responses of coordination polymers regulated by precise organization of the photoactive centers.

Three photoactive Cd(II) coordination polymers (CPs), [Cd (Fsbpe)(DBBA)2]·2DMF (CP1), [Cd(Fepbpe)(DBBA)2]·2DMF (CP2) and [Cd(Fsbpeb)(DBBA)2] (CP3) (DBBA = 3,5-dibromobenzoic acid, DMF = dimethyl formamide) with similar 1D chain motifs exhibited completely different photosalient behaviors (PS) in response to UV light. Mechanical motion was triggered by [2+2] photocycloaddition and regulated by positioning of the photoactive alkene centers relative to the crystal axis. This solid-state reaction was reversed by heating and photomechanical behaviour was repeated over several cycles. A simple photoactuating device was prepared using a CP3-PVA composite.

Tumor Cell-Derived Exosomal Hybrid Nanosystems Loaded with Rhubarbic Acid and Tanshinone IIA for Sepsis Treatment.

Background: Sepsis continues to exert a significant impact on morbidity and mortality in clinical settings, with immunosuppression, multi-organ failure, and disruptions in gut microbiota being key features. Although rheinic acid and tanshinone IIA show promise in mitigating macrophage apoptosis in sepsis treatment, their precise targeting of macrophages remains limited. Additionally, the evaluation of intestinal flora changes following treatment, which plays a significant role in subsequent cytokine storms, has been overlooked. Leveraging the innate inflammation chemotaxis of tumor cell-derived exosomes allows for their rapid recognition and uptake by activated macrophages, facilitating phenotypic changes and harnessing anti-inflammatory effects. Methods: We extracted exosomes from H1299 cells using a precipitation method. Then we developed a tumor cell-derived exosomal hybrid nanosystem loaded with rhubarbic acid and tanshinone IIA (R+T/Lipo/EXO) for sepsis treatment. In vitro studies, we verify the anti-inflammatory effect and the mechanism of inhibiting cell apoptosis of nano drug delivery system. The anti-inflammatory effects, safety, and modulation of intestinal microbiota by the nanoformulations were further validated in the in vivo study. Results: Nanoformulation demonstrated enhanced macrophage internalization, reduced TNF-α expression, inhibited apoptosis, modulated intestinal flora, and alleviated immunosuppression. Conclusion: R+T/Lipo/EXO presents a promising approach using exosomal hybrid nanosystems for treating sepsis.

Clinical efficacy, bone density, and follow-up in implant and orthodontic treatment for inclined adjacent teeth.

BACKGROUND: Tooth defects can cause elongation of occlusal teeth, leading to insufficient repair space. The combination of dental implant restoration and orthodontic treatment of oblique adjacent teeth has a significant therapeutic effect. AIM: To explore clinical efficacy, bone density, and follow-up of implant and orthodontic treatment for patients with inclined adjacent teeth. METHODS: In total, 98 patients with oblique adjacent teeth were randomly assigned to implant restoration combined with orthodontic treatment (group A, n = 49) or to receive implant restoration alone (group B, n = 49). Changes in alveolar ridge bone density and apical bone density were observed before and after treatment in the two groups. Changes in chewing function and language function were compared between the two groups of patients. Follow-up lasted for 12 mo after repair to observe any adverse reactions in the oral cavity. RESULTS: The clinical effective rates of group A and group B were 97.96% and 85.71%, respectively, with group A having a higher clinical effective rate than group B. After treatment, the bone density of the alveolar ridge and apical bone in both groups decreased compared to before treatment, while the chewing and language functions improved. The changes in various indicators in group A were more significant. After treatment, the satisfaction rate of group A (97.96%) was higher than that of group B (79.59%). The incidence of adverse reactions in group A (2.04%) was lower than that in group B (24.49%). CONCLUSION: The amalgamation of implant restoration and orthodontic treatment for adjacent tilted teeth demonstrates notable clinical efficacy, diminishes alveolar bone resorption, and fosters patient functional rehabilitation while exhibiting negligible adverse reactions.

[3 + 2] Annulation of Vinyl Azides with Aldehydes for the Synthesis of 3-Oxazolines via the [CO + CCN] Strategy.

Despite the widespread utilizable value of 3-oxazolines, mild and efficient access to such a class of unique structures still remains, to date, a challenge. Herein, we present a [3 + 2] annulation strategy, guided by the retrosynthetic principle of [CO + CCN], that utilizes vinyl azides as the CCN module and aldehydes as the CO module. This approach enables the efficient construction of the 3-oxazoline framework with remarkable features, including operational simplicity, environmental friendliness, and high efficiency. Notably, it solely requires the addition of inexpensive and readily available N-hydroxyphthalimide (NHPI) and air oxygen to obtain the desired product. It also provides a new way to generate the hydroxyl radical, which is produced by the homolysis of peroxycarboxylic acid. In addition, control experiments, X-ray crystallographic analysis, high-resolution mass spectrometry (HRMS), and density functional theory (DFT) calculations afford evidence for the key intermediates (hydroxyl radical, carboxyl radical, imine radical, hydroxyl substituted amide derivatives), further confirming the path for realization of 3-oxazolines.

DDSBC: A Stacking Ensemble Classifier-Based Approach for Breast Cancer Drug-Pair Cell Synergy Prediction.

Breast cancer (BC) ranks as a leading cause of mortality among women worldwide, with incidence rates continuing to rise. The quest for effective treatments has led to the adoption of drug combination therapy, aiming to enhance drug efficacy. However, identifying synergistic drug combinations remains a daunting challenge due to the myriad of potential drug pairs. Current research leverages machine learning (ML) and deep learning (DL) models for drug-pair synergy prediction and classification. Nevertheless, these models often underperform on specific cancer types, including BC, as they are trained on data spanning various cancers without any specialization. Here, we introduce a stacking ensemble classifier, the drug-drug synergy for breast cancer (DDSBC), tailored explicitly for BC drug-pair cell synergy classification. Unlike existing models that generalize across cancer types, DDSBC is exclusively developed for BC, offering a more focused approach. Our comparative analysis against classical ML methods as well as DL models developed for drug synergy prediction highlights DDSBC's superior performance across test and independent datasets on BC data. Despite certain metrics where other methods narrowly surpass DDSBC by 1-2%, DDSBC consistently emerges as the top-ranked model, showcasing significant differences in scoring metrics and robust performance in ablation studies. DDSBC's performance and practicality position it as a preferred choice or an adjunctive validation tool for identifying synergistic or antagonistic drug pairs in BC, providing valuable insights for treatment strategies.

Correction: Suleman et al. Immunoinformatics and Immunogenetics-Based Design of Immunogenic Peptides Vaccine against the Emerging Tick-Borne Encephalitis Virus (TBEV) and Its Validation through In Silico Cloning and Immune Simulation. Vaccines 2021, 9, 1210.

The authors would like to make the following correction to this published paper [...].

Clinical efficacy of EUS-guided celiac plexus neurolysis versus EUS-guided celiac ganglion irradiation with iodine-125 seeds for pain relief in advanced pancreatic cancer: A long-term retrospective study.

Background and Objective: To compare the efficacy of EUS-guided celiac plexus neurolysis (CPN) and celiac plexus irradiation with iodine-125 (125I) seeds with absolute ethanol for relieving pain in patients with advanced pancreatic cancer. Methods: We retrospectively analyzed data of 81 patients with advanced pancreatic cancer who underwent EUS-CPN or EUS-125I implantation between January 2017 and December 2020. Postoperative pain was assessed using visual analog scale (VAS) scores; self-assessments of quality of life and the median survival time were compared between the 2 groups. Results: EUS-CPN and 125I implantation were performed in 43 and 38 patients, respectively. Postoperative VAS scores were significantly lower than the preoperative levels in both groups. One week after the operation, 26 patients (60.5%) in the EUS-CPN group achieved partial pain relief, whereas no patients in the EUS-125I seed group experienced pain relief. However, after 4 weeks postoperatively, VAS scores had decreased, and the rate of partial pain relief was higher for EUS-125I seeds than for EUS-CPN. Self-assessments of quality of life were similar in both groups during the first 1 month after the procedure. Conclusions: Both EUS-CPN and EUS-125I seeds can safely and effectively relieve pain in patients with advanced pancreatic cancer. Although EUS-125I seeds take additional time to show effects, the extent and duration of pain relief are better compared with CPN, and interestingly, the median survival time was different.

Lower serum LDL-C levels are associated with poor prognosis in severe fever with thrombocytopenia syndrome: a single-center retrospective cohort study.

Background: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease triggered by a novel bunyavirus (SFTSV). Characterized by fever, thrombocytopenia, leukocytopenia, and multiple organ dysfunction manifestations, its primary mode of transmission is through tick bites. Despite the critical role of lipid metabolism in viral infections, the role of lipids in SFTS remains unclear. Methods: This retrospective study analyzed 602 patients with SFTS treated at the Shandong Public Health Clinical Center from January 2021 to December 2023. Based on the endpoint events, patients were classified into survival (S) and death (D) groups. The S group was further classified into non-critical (non-C) and critical (C) groups based on symptoms. All patients were followed up for at least 28 days after admission. Propensity score matching, multivariable logistic regression, survival analysis, time trend analysis, and mediation analysis were conducted to assess the association between LDL-C levels and prognosis in SFTS. Results: The serum LDL-C levels on admission were significantly lower in the D and C groups than in the S and non-C groups. The logistic regression models indicated a potential association between LDL-C levels and a poor prognosis in SFTS. The restricted cubic spline showed a unidirectional trend between LDL-C levels and mortality, with a cutoff value of 1.59 mmol/L. The survival analysis revealed higher and earlier mortality in the low-LDL-C group than in the high-LDL-C group. The trends over 28 days post-admission showed that the serum LDL-C levels gradually increased in SFTS, with a favorable prognosis. Finally, the mediation analysis indicated that low LDL-C levels are associated with mortality through poor hepatic, cardiac, and coagulation functions. Conclusion: Low LDL-C levels are potentially associated with a poor prognosis in SFTS.

CELA-MFP: a contrast-enhanced and label-adaptive framework for multi-functional therapeutic peptides prediction.

Functional peptides play crucial roles in various biological processes and hold significant potential in many fields such as drug discovery and biotechnology. Accurately predicting the functions of peptides is essential for understanding their diverse effects and designing peptide-based therapeutics. Here, we propose CELA-MFP, a deep learning framework that incorporates feature Contrastive Enhancement and Label Adaptation for predicting Multi-Functional therapeutic Peptides. CELA-MFP utilizes a protein language model (pLM) to extract features from peptide sequences, which are then fed into a Transformer decoder for function prediction, effectively modeling correlations between different functions. To enhance the representation of each peptide sequence, contrastive learning is employed during training. Experimental results demonstrate that CELA-MFP outperforms state-of-the-art methods on most evaluation metrics for two widely used datasets, MFBP and MFTP. The interpretability of CELA-MFP is demonstrated by visualizing attention patterns in pLM and Transformer decoder. Finally, a user-friendly online server for predicting multi-functional peptides is established as the implementation of the proposed CELA-MFP and can be freely accessed at http://dreamai.cmii.online/CELA-MFP.

Molecular insights into the catalytic mechanism of a phthalate ester hydrolase.

Phthalate esters (PAEs) are emerging hazardous and toxic chemicals that are extensively used as plasticizers or additives. Diethyl phthalate (DEP) and dimethyl phthalate (DMP), two kinds of PAEs, have been listed as the priority pollutants by many countries. PAE hydrolases are the most effective enzymes in PAE degradation, among which family IV esterases are predominate. However, only a few PAE hydrolases have been characterized, and as far as we know, no crystal structure of any PAE hydrolases of the family IV esterases is available to date. HylD1 is a PAE hydrolase of the family IV esterases, which can degrade DMP and DEP. Here, the recombinant HylD1 was characterized. HylD1 maintained a dimer in solution, and functioned under a relatively wide pH range. The crystal structures of HylD1 and its complex with monoethyl phthalate were solved. Residues involved in substrate binding were identified. The catalytic mechanism of HylD1 mediated by the catalytic triad Ser140-Asp231-His261 was further proposed. The hylD1 gene is widely distributed in different environments, suggesting its important role in PAEs degradation. This study provides a better understanding of PAEs hydrolysis, and lays out favorable bases for the rational design of highly-efficient PAEs degradation enzymes for industrial applications in future.

Marine sponge-derived alkaloid inhibits the PI3K/AKT/mTOR signaling pathway against diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous non-Hodgkin lymphoma that is extremely aggressive and has an intermediate to high malignancy. Some patients still experience treatment failure, relapse, or resistance to rituximab, cyclophosphamide, adriamycin, vincristine, and prednisone (R-CHOP) therapy. Therefore, there is an urgent need for further research on new agents for the treatment of DLBCL. AP-48 is an aaptamine alkaloid analog with potent anti-tumor effects that originates from marine natural products. In this study, we found that AP-48 exhibits dose-dependent cytotoxicity in DLBCL cell lines. Flow cytometry showed that AP-48 induced cell cycle arrest in the G0/G1 phase in SU-DHL-4 and Farage cells and in the S phase in WSU-DLCL-2 cells. AP-48 also accelerated apoptosis via the caspase-3-mediated intrinsic apoptotic pathway. Further experiments demonstrated that AP-48 exerted its anti-DLBCL effects through the PI3K/AKT/mTOR pathway, and that the PI3K agonist YS49 partially alleviated the inhibition of cell proliferation and apoptosis induced by AP-48. Finally, in a tumor xenograft model, AP-48 inhibited tumor growth and promoted apoptosis in tumor tissues, indicating its therapeutic potential in DLBCL.