Perspectives and challenges in developing small molecules targeting purine nucleoside phosphorylase.

As a cytosolic enzyme involved in the purine salvage pathway metabolism, purine nucleoside phosphorylase (PNP) plays an important role in a variety of cellular functions but also in immune system, including cell growth, apoptosis and cancer development and progression. Based on its T-cell targeting profile, PNP is a potential target for the treatment of some malignant T-cell proliferative cancers including lymphoma and leukemia, and some specific immunological diseases. Numerous small-molecule PNP inhibitors have been developed so far. However, only Peldesine, Forodesine and Ulodesine have entered clinical trials and exhibited some potential for the treatment of T-cell leukemia and gout. The most recent direction in PNP inhibitor development has been focused on PNP small-molecule inhibitors with better potency, selectivity, and pharmacokinetic property. In this perspective, considering the structure, biological functions, and disease relevance of PNP, we highlight the recent research progress in PNP small-molecule inhibitor development and discuss prospective strategies for designing additional PNP therapeutic agents.

Bayesian network-based survival prediction model for patients having undergone post-transjugular intrahepatic portosystemic shunt for portal hypertension.

BACKGROUND: Portal hypertension (PHT), primarily induced by cirrhosis, manifests severe symptoms impacting patient survival. Although transjugular intrahepatic portosystemic shunt (TIPS) is a critical intervention for managing PHT, it carries risks like hepatic encephalopathy, thus affecting patient survival prognosis. To our knowledge, existing prognostic models for post-TIPS survival in patients with PHT fail to account for the interplay among and collective impact of various prognostic factors on outcomes. Consequently, the development of an innovative modeling approach is essential to address this limitation. AIM: To develop and validate a Bayesian network (BN)-based survival prediction model for patients with cirrhosis-induced PHT having undergone TIPS. METHODS: The clinical data of 393 patients with cirrhosis-induced PHT who underwent TIPS surgery at the Second Affiliated Hospital of Chongqing Medical University between January 2015 and May 2022 were retrospectively analyzed. Variables were selected using Cox and least absolute shrinkage and selection operator regression methods, and a BN-based model was established and evaluated to predict survival in patients having undergone TIPS surgery for PHT. RESULTS: Variable selection revealed the following as key factors impacting survival: age, ascites, hypertension, indications for TIPS, postoperative portal vein pressure (post-PVP), aspartate aminotransferase, alkaline phosphatase, total bilirubin, prealbumin, the Child-Pugh grade, and the model for end-stage liver disease (MELD) score. Based on the above-mentioned variables, a BN-based 2-year survival prognostic prediction model was constructed, which identified the following factors to be directly linked to the survival time: age, ascites, indications for TIPS, concurrent hypertension, post-PVP, the Child-Pugh grade, and the MELD score. The Bayesian information criterion was 3589.04, and 10-fold cross-validation indicated an average log-likelihood loss of 5.55 with a standard deviation of 0.16. The model's accuracy, precision, recall, and F1 score were 0.90, 0.92, 0.97, and 0.95 respectively, with the area under the receiver operating characteristic curve being 0.72. CONCLUSION: This study successfully developed a BN-based survival prediction model with good predictive capabilities. It offers valuable insights for treatment strategies and prognostic evaluations in patients having undergone TIPS surgery for PHT.

Peptide Transporter 1-Mediated Dipeptide Transport Promotes Hepatocellular Carcinoma Metastasis by Activating MAP4K4/G3BP2 Signaling Axis.

Cancer metastasis is the leading cause of mortality in patients with hepatocellular carcinoma (HCC). To meet the rapid malignant growth and transformation, tumor cells dramatically increase the consumption of nutrients, such as amino acids. Peptide transporter 1 (PEPT1), a key transporter for small peptides, has been found to be an effective and energy-saving intracellular source of amino acids that are required for the growth of tumor cells. Here, the role of PEPT1 in HCC metastasis and its underlying mechanisms is explored. PEPT1 is upregulated in HCC cells and tissues, and high PEPT1 expression is associated with poor prognosis in patients with HCC. PEPT1 overexpression dramatically promoted HCC cell migration, invasion, and lung metastasis, whereas its knockdown abolished these effects both in vitro and in vivo. Mechanistic analysis revealed that high PEPT1 expression increased cellular dipeptides in HCC cells that are responsible for activating the MAP4K4/G3BP2 signaling pathway, ultimately facilitating the phosphorylation of G3BP2 at Thr227 and enhancing HCC metastasis. Taken together, these findings suggest that PEPT1 acts as an oncogene in promoting HCC metastasis through dipeptide-induced MAP4K4/G3BP2 signaling and that the PEPT1/MAP4K4/G3BP2 axis can serve as a promising therapeutic target for metastatic HCC.

Identification of CH2-linked quinolone-aminopyrimidine hybrids as potent anti-MRSA agents: Low resistance potential and lack of cross-resistance with fluoroquinolone antibiotics.

The structural optimization of B14, an antibacterial agent we previously obtained, has led to the discovery of a new class of CH2-linked quinolone-aminopyrimidine hybrids with potent anti-MRSA activities. Surprisingly, the hybrids lacking a C-6 fluoro atom at the quinolone nucleus showed equal or even stronger anti-MRSA activities than their corresponding 6-fluoro counterparts, despite the well-established structure-activity relationships (SARs) indicating that the 6-fluoro substituent enhances the antibacterial activity in conventional fluoroquinolone antibiotics. Moreover, these new hybrids, albeit structurally related to conventional fluoroquinolones, showed no cross-resistance with fluoroquinolone drugs. The most active compound, 15m, exhibited excellent activities with a MIC value of 0.39 µg/mL against both fluoroquinolone-sensitive strain USA500 and -resistant MRSA isolate Mu50. Further resistance development studies indicated MRSA is unlikely to acquire resistance against 15m. Moreover, 15m displayed favorable in vivo half-life and safety profiles. These findings suggest a rationale for further evolution of quinolone antibiotics with a high barrier to resistance.

Single-cell analysis identifies critical regulators of spermatogonial development and differentiation in cattle-yak bulls.

Spermatogenesis is a continuous process in which functional sperm are produced through a series of mitotic and meiotic divisions and morphological changes in germ cells. The aberrant development and fate transitions of spermatogenic cells cause hybrid sterility in mammals. Cattle-yak, a hybrid animal between taurine cattle (Bos taurus) and yak (Bos grunniens), exhibits male-specific sterility due to spermatogenic failure. In the present study, we performed single-cell RNA sequencing analysis to identify differences in testicular cell composition and the developmental trajectory of spermatogenic cells between yak and cattle-yak. The composition and molecular signatures of spermatogonial subtypes were dramatically different between these 2 animals, and the expression of genes associated with stem cell maintenance, cell differentiation and meiotic entry was altered in cattle-yak, indicating the impairment of undifferentiated spermatogonial fate decisions. Cell communication analysis revealed that signaling within different spermatogenic cell subpopulations was weakened, and progenitor spermatogonia were unable or delayed receiving and sending signals for transformation to the next stage in cattle-yak. Simultaneously, the communication between niche cells and germ cells was also abnormal. Collectively, we obtained the expression profiles of transcriptome signatures of different germ cells and testicular somatic cell populations at the single-cell level and identified critical regulators of spermatogonial differentiation and meiosis in yak and sterile cattle-yak. The findings of this study shed light on the genetic mechanisms that lead to hybrid sterility and speciation in bovid species.

Reconciling the Cooperative-Competitive Patterns among Tumor and Immune Cells for Triple-Negative Breast Cancer Treatment Using Multimodule Nanocomplexes.

Targeting the competitive-cooperative relationships among tumor cells and various immune cells can efficiently reverse the immune-dysfunction microenvironment to boost the immunotherapies for the triple-negative breast cancer treatment. Hence, a bacterial outer membrane vesicle-based nanocomplex is designed for specifically targeting malignant cells and immune cells to reconcile the relationships based on metabolic-immune crosstalk. By uniquely utilizing the property of charge-reversal polymers to realize function separation, the nanocomplexes could synergistically regulate tumor cells and immune cells. This approach could reshape the immunosuppressive competition-cooperation pattern into one that is immune-responsive, showcasing significant potential for inducing tumor remission in TNBC models.

Case report: Treatment of psoriasiform dermatitis in patients with malignancy.

Psoriasis and atopic dermatitis (AD) are prevalent inflammatory skin disorders, each stemming from diverse factors, and characterized by recurring episodes. In certain complex cases, the clinical and pathological features exhibit overlapping and atypical characteristics, making accurate clinical diagnosis and targeted treatment a challenge. Psoriasiform dermatitis is the term used to describe such cases. Moreover, when patients have a history of malignancy, the situation becomes even more intricate, resulting in limited treatment options. Biologic therapies have transformed the management of immune-mediated inflammatory diseases, including psoriasis and AD. Meanwhile, the safety of biologics in special populations, especially among patients with a history of malignancy, should be underlined. The selective Janus kinase 1 (JAK1) inhibitor abrocitinib has been approved for the treatment of AD and has showed satisfying efficacy and safety in the treatment of psoriasis in clinical trials. Although unreported, JAK1 inhibitors are thought to have the potential to increase the risk of potential tumors. Apremilast, an oral phosphodiesterase (PDE)-4 inhibitor, is approved for moderate to severe plaque psoriasis. It has been investigated for its efficacy in AD, and is not contraindicated in malignancy. This report presents three cases of psoriasiform dermatitis in patients with a history of malignancy, showcasing significant improvement following treatment with systemic glucocorticoid, abrocitinib, or apremilast.

Structure-Guided Discovery and Preclinical Assessment of Novel (Thiophen-3-yl)aminopyrimidine Derivatives as Potent ERK1/2 Inhibitors.

The RAS-RAF-MEK-ERK signaling cascade is abnormally activated in various tumors, playing a crucial role in mediating tumor progression. As the key component at the terminal stage of this cascade, ERK1/2 emerges as a potential antitumor target and offers a promising therapeutic strategy for tumors harboring BRAF or RAS mutations. Here, we identified 36c with a (thiophen-3-yl)aminopyrimidine scaffold as a potent ERK1/2 inhibitor through structure-guided optimization for hit 18. In preclinical studies, 36c showed powerful ERK1/2 inhibitory activities (ERK1/2 IC50 = 0.11/0.08 nM) and potent antitumor efficacy both in vitro and in vivo against triple-negative breast cancer and colorectal cancer models harboring BRAF and RAS mutations. 36c could directly inhibit ERK1/2, significantly block the phosphorylation expression of their downstream substrates p90RSK and c-Myc, and induce cell apoptosis and incomplete autophagy-related cell death. Taken together, this work provides a promising ERK1/2 lead compound for multiple tumor-treatment drug discovery.

Construction and validation of a hypoxia-related gene signature to predict the prognosis of breast cancer.

BACKGROUND: Among the most common forms of cancer worldwide, breast cancer posed a serious threat to women. Recent research revealed a lack of oxygen, known as hypoxia, was crucial in forming breast cancer. This research aimed to create a robust signature with hypoxia-related genes to predict the prognosis of breast cancer patients. The function of hypoxia genes was further studied through cell line experiments. MATERIALS AND METHODS: In the bioinformatic part, transcriptome and clinical information of breast cancer were obtained from The Cancer Genome Atlas(TCGA). Hypoxia-related genes were downloaded from the Genecards Platform. Differentially expressed hypoxia-related genes (DEHRGs) were identified. The TCGA filtered data was evenly split, ensuring a 1:1 distribution between the training and testing sets. Prognostic-related DEHRGs were identified through Cox regression. The signature was established through the training set. Then, it was validated using the test set and external validation set GSE131769 from Gene Expression Omnibus (GEO). The nomogram was created by incorporating the signature and clinicopathological characteristics. The predictive value of the nomogram was evaluated by C-index and receiver operating characteristiccurve. Immune microenvironment and mutation burden were also examined. In the experiment part, the function of the two most significant hypoxia-related genes were further explored by cell-line experiments. RESULTS: In the bioinformatic part, 141 up-regulated and 157 down-regulated DEHRGs were screened out. A prognostic signature was constructed containing nine hypoxia genes (ALOX15B, CA9, CD24, CHEK1, FOXM1, HOTAIR, KCNJ11, NEDD9, PSME2) in the training set. Low-risk patients exhibited a much more favorable prognosis than higher-risk ones (P < 0.001). The signature was double-validated in the test set and GSE131769 (P = 0.006 and P = 0.001). The nomogram showed excellent predictive value with 1-year OS AUC: 0.788, 3-year OS AUC: 0.783, and 5-year OS AUC: 0.817. Patients in the high-risk group had a higher tumor mutation burden when compared to the low-risk group. In the experiment part, the down-regulation of PSME2 inhibited cell growth ability and clone formation capability of breast cancer cells, while the down-regulation of KCNJ11 did not have any functions. CONCLUSION: Based on 9 DEHRGs, a reliable signature was established through the bioinformatic method. It could accurately predict the prognosis of breast cancer patients. Cell line experiment indicated that PSME2 played a protective role. Summarily, we provided a new insight to predict the prognosis of breast cancer by hypoxia-related genes.

DoseDiff: Distance-aware Diffusion Model for Dose Prediction in Radiotherapy.

Treatment planning, which is a critical component of the radiotherapy workflow, is typically carried out by a medical physicist in a time-consuming trial-and-error manner. Previous studies have proposed knowledge-based or deep-learning-based methods for predicting dose distribution maps to assist medical physicists in improving the efficiency of treatment planning. However, these dose prediction methods usually fail to effectively utilize distance information between surrounding tissues and targets or organs-at-risk (OARs). Moreover, they are poor at maintaining the distribution characteristics of ray paths in the predicted dose distribution maps, resulting in a loss of valuable information. In this paper, we propose a distance-aware diffusion model (DoseDiff) for precise prediction of dose distribution. We define dose prediction as a sequence of denoising steps, wherein the predicted dose distribution map is generated with the conditions of the computed tomography (CT) image and signed distance maps (SDMs). The SDMs are obtained by distance transformation from the masks of targets or OARs, which provide the distance from each pixel in the image to the outline of the targets or OARs. We further propose a multi-encoder and multi-scale fusion network (MMFNet) that incorporates multi-scale and transformer-based fusion modules to enhance information fusion between the CT image and SDMs at the feature level. We evaluate our model on two in-house datasets and a public dataset, respectively. The results demonstrate that our DoseDiff method outperforms state-of-the-art dose prediction methods in terms of both quantitative performance and visual quality.

Analysis of mechanism of core points in acupuncture and moxibustion treatment for epilepsy based on data mining. / åŸºäºŽæ•°æ®æŒ–æŽ˜æŽ¢è®¨é’ˆç¸æ²»ç–—ç™«ç—«æ ¸å¿ƒç©´ä½çš„ä½œç”¨æœºåˆ¶.

OBJECTIVES: To explore the mechanism of core points in acupuncture and moxibustion treatment for epilepsy by using data mining technique, so as to provide a reference for clinical practice and experimental research. METHODS: The data comes from relevant documents collected from CNKI, Wanfang, SinoMed, VIP, PubMed, Embase, Cochrane Library, EBSCO, Web of Science databases. The selected acupoints were analyzed in descriptive statistics, high-frequency acupoints group and core acupoint prescription. Further, potential target mining, "core acupoint prescription-target-epilepsy" network construction, protein-protein interactions (PPI) network establishment and core target extraction, gene ontology (GO) and KEGG gene enrichment analysis of the core acupoint prescription were carried out to predict its anti-epileptic potential mechanism. RESULTS: A total of 122 acupoint prescriptions were included. The core acupoint prescriptions were Baihui (GV20), Hegu (LI4), Neiguan (PC6), Shuigou (GV26) and Taichong (LR3). 277 potential targets were identified, among which 134 were shared with epilepsy. The core targets were extracted by PPI network topology analysis, including signal transducer and activator of transcription 3, tumor necrosis factor (TNF), interleukin (IL)-6, protein kinase B1, c-Jun N-terminal kinase, brain-derived neurotrophic factor, tumor protein 53, vascular endothelial growth factor A, Caspase-3, epidermal growth factor receptor, etc. The main anti-epileptic pathways of the core acupoints were predicted by KEGG enrichment, including lipid and atherosclerosis, neurodegeneration, phosphatidylinositol-3-kinase/protein B kinase signaling pathway, mitogen-activated protein kinase signaling pathway, cyclic adenosine monophosphate signaling pathway, TNF signaling pathway, IL-17 signaling pathway, hypoxia-inducible factor-1 signaling pathway, apoptosis, etc., involving neuronal death, synaptic plasticity, oxidative stress, inflammation and other related biological process. CONCLUSIONS: The core acupoint prescription of acupuncture and moxibustion intervention for epilepsy can act on multiple targets and multiple pathways to exert anti-epileptic effects, which can provide a theoretical basis for further clinical application and mechanism research.

EspP2 Regulates the Adhesion of Glaesserella parasuis via Rap1 Signaling Pathway.

Different levels of EspP2 expression are seen in strains of Glaesserella parasuis with high and low pathogenicity. As a potential virulence factor for G. parasuis, the pathogenic mechanism of EspP2 in infection of host cells is not clear. To begin to elucidate the effect of EspP2 on virulence, we used G. parasuis SC1401 in its wild-type form and SC1401, which was made EspP2-deficient. We demonstrated that EspP2 causes up-regulation of claudin-1 and occludin expression, thereby promoting the adhesion of G. parasuis to host cells; EspP2-deficiency resulted in significantly reduced adhesion of G. parasuis to cells. Transcriptome sequencing analysis of EspP2-treated PK15 cells revealed that the Rap1 signaling pathway is stimulated by EspP2. Blocking this pathway diminished occludin expression and adhesion. These results indicated that EspP2 regulates the adhesion of Glaesserella parasuis via Rap1 signaling pathway.

Appendectomy and risk of prostate cancer in the Health Professionals Follow-up Study.

BACKGROUND: Appendectomy is a common surgical procedure to treat appendicitis. Limited studies examined its association on prostate cancer, with one large cohort study suggesting significant increased risk of overall and advanced prostate cancer, especially among younger men. METHODS: A total of 49,104 men in the Health Professionals Follow-up Study were followed from 1986 to 2016. Cox proportional hazards models were applied to evaluate the association between self-reported history of appendectomy and risk of overall and subtype specific prostate cancer, adjusted for multiple risk factors. RESULTS: During 30 years of follow-up, we documented 7,253 overall prostate cancer including 579 advanced and 1,092 lethal events. Compared to men without appendectomy, those who reported at baseline having had appendectomy were not at higher risk of overall (hazard ratio (HR)=1.01, 95% CI = 0.95 to 1.07), advanced (HR=0.99, 95% CI = 0.81 to 1.23) or lethal (HR=1.04, 95% CI = 0.89 to 1.20) prostate cancer. The association remained null when stratified by age. CONCLUSIONS: We found no evidence of an association between appendectomy and risk of overall and clinically important prostate cancer. IMPACT: We showed that appendectomy was not associated with overall or advanced prostate cancer adjusted for multiple risk factors among a large population of men with 30 years of follow-up.

Efficient degradation of sulfonamides by introducing sulfur to magnetic Prussian blue analog in photo-assisted persulfate oxidation system.

The peroxynitrite photocatalytic degradation system was considered a green, convenient, and efficient water treatment process, but not satisfying against some antibiotics, e.g. sulfonamides (SAs). To improve the photocatalytic degradation efficiency of SAs, sulfur was introduced to a magnetic Fe-MOF (Fe-metal organic framework) Prussian blue analog to achieve a heteroatomic material CuFeO@S, which was applied in heterogeneous visible light photo-assisted catalytic process with persulfate (PS) as an oxidant. The characterization results of CuFeO@S by XRD and XPS confirmed the presence of Fe3O4 (for magnetic separation), Cu+ (for activation of PS) and S2- (for narrowing the energy band and prolonging the lifetime of photo-generated electronics). Through systematic optimization of reaction conditions in CuFeO@S + PS + hv system, efficient degradation of four tested SAs was achieved in 30 min (removal rate of 97-100% for the tested 4 SAs). Moreover, the material could be magnetically recycled and reused for over 7 cycles with a removal rate of >90% for sulfamerazine. Furthermore, the removal rate of sulfamerazine in pond water reached 99% at a mineralization rate of about 34% (decrease in total organic matter), demonstrating its potential in the treatment of antibiotic-containing wastewater.

Capturing ion trapping and detrapping dynamics in electrochromic thin films.

Ion trapping has been found to be responsible for the performance degradation in electrochromic oxide thin films, and a detrapping procedure was proved to be effective to rejuvenate the degraded films. Despite of the studies on ion trapping and detrapping, its dynamics remain largely unknown. Moreover, coloration mechanisms of electrochromic oxides are also far from clear, limiting the development of superior devices. Here, we visualize ion trapping and detrapping dynamics in a model electrochromic material, amorphous WO3. Specifically, formation of orthorhombic Li2WO4 during long-term cycling accounts for the origin of shallow traps. Deep traps are multiple-step-determined, composed of mixed W4+-Li2WO4, amorphous Li2WO4 and W4+-Li2O. The non-decomposable W4+-Li2WO4 couple is the origin of the irreversible traps. Furthermore, we demonstrate that, besides the typical small polaron hopping between W5+ ↔ W6+ sites, bipolaron hopping between W4+ ↔ W6+ sites gives rise to optical absorption in the short-wavelength region. Overall, we provide a general picture of electrochromism based on polaron hopping. Ion trapping and detrapping were demonstrated to also prevail in other cathodic electrochromic oxides. This work not only provides the ion trapping and detrapping dynamics of WO3, but also open avenues to study other cathodic electrochromic oxides and develop superior electrochromic devices with great durability.

The effects of mnemonic variability and spacing on memory over multiple timescales.

The memory benefit that arises from distributing learning over time rather than in consecutive sessions is one of the most robust effects in cognitive psychology. While prior work has mainly focused on repeated exposures to the same information, in the real world, mnemonic content is dynamic, with some pieces of information staying stable while others vary. Thus, open questions remain about the efficacy of the spacing effect in the face of variability in the mnemonic content. Here, in two experiments, we investigated the contributions of mnemonic variability and the timescale of spacing intervals, ranging from seconds to days, to long-term memory. For item memory, both mnemonic variability and spacing intervals were beneficial for memory; however, mnemonic variability was greater at shorter spacing intervals. In contrast, for associative memory, repetition rather than mnemonic variability was beneficial for memory, and spacing benefits only emerged in the absence of mnemonic variability. These results highlight a critical role for mnemonic variability and the timescale of spacing intervals in the spacing effect, bringing this classic memory paradigm into more ecologically valid contexts.

Bioequivalence Study of Tebipenem Pivoxil in Healthy Chinese Adults.

BACKGROUND AND OBJECTIVE: Tebipenem pivoxil (TP) is a carbapenem and is applied against pneumonia, otitis media, and sinusitis. This study compared the pharmacokinetics (PK) and safety of a test (T) preparation and reference (R) preparation of TP in healthy Chinese adults. METHODS: This study was a single-center, randomized, open, single-dose (fasting/postprandial) oral administration, two-agent, two-sequence, two-cycle, crossover bioequivalence trial. A total of 60 participants were enrolled (24 fasting and 36 postprandial). All participants were randomly assigned to the TR sequence and RT sequence. Subsequently, they switched T sequences or R sequences 7 days later. PK blood samples were collected according to the protocol, plasma TP concentration was determined by liquid chromatography-mass spectrometry, main PK parameters were calculated based on a non-compartment model, and adverse events were recorded during the test. RESULTS: In the feeding arm, the geometric mean ratio of maximum concentration (Cmax) was 89.84% (90% confidence interval 84.33-95.70), the geometric mean ratio of area under the plasma concentration-time curve from time 0 to last time of quantifiable concentration (AUC0-t) was 86.80% (83.62-90.10), and the geometric mean ratio of area under the plasma concentration-time curve from time 0 to infinity time of quantifiable concentration (AUC0-∞) was 86.90% (83.73-90.20), which were within the acceptable range of bioequivalence (80-125%). In the fasting arm, the geometric mean ratio of Cmax was 96.07% (89.62-102.99), the geometric mean ratio of AUC0-t was 93.09% (90.47-95.78), and the geometric mean ratio of AUC0-∞ was 93.09% (90.48-95.77), which was within the acceptable range of bioequivalence (80-125%). Hence, the T preparation and R preparation of TP had bioequivalence in the fasting arm and feeding arm of the clinical trial. In addition, all adverse events were mild, and no severe adverse events were noted. CONCLUSION: Preparations T and R of TP were bioequivalent in the fasting and postprandial groups in clinical trials, and TP was safe.

Can xenobiotics support the growth of Mn(II)-oxidizing bacteria (MnOB)? A case of phenol-utilizing bacteria Pseudomonas sp. AN-1.

Biogenic manganese oxides (BioMnOx) produced by Mn(II)-oxidizing bacteria (MnOB) have garnered considerable attention for their exceptional adsorption and oxidation capabilities. However, previous studies have predominantly focused on the role of BioMnOx, neglecting substantial investigation into MnOB themselves. Meanwhile, whether the xenobiotics could support the growth of MnOB as the sole carbon source remains uncertain. In this study, we isolated a strain termed Pseudomonas sp. AN-1, capable of utilizing phenol as the sole carbon source. The degradation of phenol took precedence over the accumulation of BioMnOx. In the presence of 100 mg L-1 phenol and 100 µM Mn(II), phenol was entirely degraded within 20 h, while Mn(II) was completely oxidized within 30 h. However, at the higher phenol concentration (500 mg L-1), phenol degradation reduced to 32% and Mn(II) oxidation did not appear to occur. TOC determination confirmed the ability of strain AN-1 to mineralize phenol. Based on the genomic and proteomics studies, the Mn(II) oxidation and phenol mineralization mechanism of strain AN-1 was further confirmed. Proteome analysis revealed down-regulation of proteins associated with Mn(II) oxidation, including MnxG and McoA, with increasing phenol concentration. Notably, this study observed for the first time that the expression of Mn(II) oxidation proteins is modulated by the concentration of carbon sources. This work provides new insight into the interaction between xenobiotics and MnOB, thus revealing the complexity of biogeochemical cycles of Mn and C.

The receptor binding domain of SARS-CoV-2 Omicron subvariants targets Siglec-9 to decrease its immunogenicity by preventing macrophage phagocytosis.

The development of a vaccine specific to severe acute respiratory syndrome coronavirus 2 Omicron has been hampered due to its low immunogenicity. Here, using reverse mutagenesis, we found that a phenylalanine-to-serine mutation at position 375 (F375S) in the spike protein of Omicron to revert it to the sequence found in Delta and other ancestral strains significantly enhanced the immunogenicity of Omicron vaccines. Sequence FAPFFAF at position 371-377 in Omicron spike had a potent inhibitory effect on macrophage uptake of receptor-binding domain (RBD) nanoparticles or spike-pseudovirus particles containing this sequence. Omicron RBD enhanced binding to Siglec-9 on macrophages to impair phagocytosis and antigen presentation and promote immune evasion, which could be abrogated by the F375S mutation. A bivalent F375S Omicron RBD and Delta-RBD nanoparticle vaccine elicited potent and broad nAbs in mice, rabbits and rhesus macaques. Our research suggested that manipulation of the Siglec-9 pathway could be a promising approach to enhance vaccine response.

GraphormerDTI: A graph transformer-based approach for drug-target interaction prediction.

The application of Artificial Intelligence (AI) to screen drug molecules with potential therapeutic effects has revolutionized the drug discovery process, with significantly lower economic cost and time consumption than the traditional drug discovery pipeline. With the great power of AI, it is possible to rapidly search the vast chemical space for potential drug-target interactions (DTIs) between candidate drug molecules and disease protein targets. However, only a small proportion of molecules have labelled DTIs, consequently limiting the performance of AI-based drug screening. To solve this problem, a machine learning-based approach with great ability to generalize DTI prediction across molecules is desirable. Many existing machine learning approaches for DTI identification failed to exploit the full information with respect to the topological structures of candidate molecules. To develop a better approach for DTI prediction, we propose GraphormerDTI, which employs the powerful Graph Transformer neural network to model molecular structures. GraphormerDTI embeds molecular graphs into vector-format representations through iterative Transformer-based message passing, which encodes molecules' structural characteristics by node centrality encoding, node spatial encoding and edge encoding. With a strong structural inductive bias, the proposed GraphormerDTI approach can effectively infer informative representations for out-of-sample molecules and as such, it is capable of predicting DTIs across molecules with an exceptional performance. GraphormerDTI integrates the Graph Transformer neural network with a 1-dimensional Convolutional Neural Network (1D-CNN) to extract the drugs' and target proteins' representations and leverages an attention mechanism to model the interactions between them. To examine GraphormerDTI's performance for DTI prediction, we conduct experiments on three benchmark datasets, where GraphormerDTI achieves a superior performance than five state-of-the-art baselines for out-of-molecule DTI prediction, including GNN-CPI, GNN-PT, DeepEmbedding-DTI, MolTrans and HyperAttentionDTI, and is on a par with the best baseline for transductive DTI prediction. The source codes and datasets are publicly accessible at https://github.com/mengmeng34/GraphormerDTI.