Prediction of drug-target binding affinity based on multi-scale feature fusion.

Accurate prediction of drug-target binding affinity (DTA) plays a pivotal role in drug discovery and repositioning. Although deep learning methods are widely used in DTA prediction, two significant challenges persist: (i) how to effectively represent the complex structural information of proteins and drugs; (ii) how to precisely model the mutual interactions between protein binding sites and key drug substructures. To address these challenges, we propose a MSFFDTA (Multi-scale feature fusion for predicting drug target affinity) model, in which multi-scale encoders effectively capture multi-level structural information of drugs and proteins are designed. And then a Selective Cross Attention (SCA) mechanism is developed to filter out the trivial interactions between drug-protein substructure pairs and retain the important ones, which will make the proposed model better focusing on these key interactions and offering insights into their underlying mechanism. Experimental results on two benchmark datasets demonstrate that MSFFDTA is superior to several state-of-the-art methods across almost all comparison metrics. Finally, we provide the ablation and case studies with visualizations to verify the effectiveness and the interpretability of MSFFDTA. The source code is freely available at https://github.com/whitehat32/MSFF-DTA/.

Extraction and Imputation of Eastern Cooperative Oncology Group Performance Status From Unstructured Oncology Notes Using Language Models.

PURPOSE: Eastern Cooperative Oncology Group (ECOG) performance status (PS) is a key clinical variable for cancer treatment and research, but it is usually only recorded in unstructured form in the electronic health record. We investigated whether natural language processing (NLP) models can impute ECOG PS using unstructured note text. MATERIALS AND METHODS: Medical oncology notes were identified from all patients with cancer at our center from 1997 to 2023 and divided at the patient level into training (approximately 80%), tuning/validation (approximately 10%), and test (approximately 10%) sets. Regular expressions were used to extract explicitly documented PS. Extracted PS labels were used to train NLP models to impute ECOG PS (0-1 v 2-4) from the remainder of the notes (with regular expression-extracted PS documentation removed). We assessed associations between imputed PS and overall survival (OS). RESULTS: ECOG PS was extracted using regular expressions from 495,862 notes, corresponding to 79,698 patients. A Transformer-based Longformer model imputed PS with high discrimination (test set area under the receiver operating characteristic curve 0.95, area under the precision-recall curve 0.73). Imputed poor PS was associated with worse OS, including among notes with no explicit documentation of PS detected (OS hazard ratio, 11.9; 95% CI, 11.1 to 12.8). CONCLUSION: NLP models can be used to impute performance status from unstructured oncologist notes at scale. This may aid the annotation of oncology data sets for clinical outcomes research and cancer care delivery.

Mineral acid-triggered multicolor room-temperature phosphorescence nanoprobes for time-resolved bioimaging.

We present a facile strategy to achieve color-tunability room-temperature phosphorescence (RTP) nanoprobes by doping mineral acids (i.e., boric acid and phosphoric acid) in an organic silicon scaffold through a cross-linking process. Such RTP nanoprobes exhibit inherent tunable phosphorescence (from 420-650 nm) with long lifetime (emission lasting for ∼5-15 s, RTP lifetime: ∼0.53-2.11 s) and high quantum yields (∼13.1-43.0%). Therefore, the as-prepared nanoprobes enable multiple imaging in live cells with a high signal-to-background ratio value of ∼52.

Plasma Kidney Injury Molecule-1 for Preoperative Prediction of Renal Cell Carcinoma Versus Benign Renal Masses, and Association With Clinical Outcomes.

PURPOSE: Both clear cell and papillary renal cell carcinomas (RCCs) overexpress kidney injury molecule-1 (KIM-1). We investigated whether plasma KIM-1 (pKIM-1) may be a useful risk stratification tool among patients with suspicious renal masses. METHODS: Prenephrectomy pKIM-1 was measured in two independent cohorts of patients with renal masses. Cohort 1, from the prospective K2 trial, included 162 patients found to have clear cell RCC (cases) and 162 patients with benign renal masses (controls). Cohort 2 included 247 patients with small (cT1a) renal masses from an academic biorepository, of whom 184 had RCC. We assessed the relationship between pKIM-1, surgical pathology, and clinical outcomes. RESULTS: In Cohort 1, pKIM-1 distinguished RCC versus benign masses with area under the receiver operating curve (AUC-ROC, 0.81 [95% CI, 0.76 to 0.86]). In Cohort 2 (cT1a only), pKIM-1 distinguished RCC versus benign masses (AUC-ROC, 0.74 [95% CI, 0.67 to 0.80]) and the addition of pKIM-1 to an established nomogram for predicting malignancy improved the model AUC-ROC (0.65 [95% CI, 0.57 to 0.74] v 0.78 [95% CI, 0.72 to 0.85]). A pKIM-1 cutpoint identified using Cohort 2 demonstrated sensitivity of 92.5% and specificity of 60% for identifying RCC in Cohort 1. In long-term follow-up of RCC cases (Cohort 1), higher prenephrectomy pKIM-1 was associated with worse metastasis-free survival (multivariable MFS hazard ratio [HR] 1.29 per unit increase in log pKIM-1, 95% CI, 1.10 to 1.53) and overall survival (multivariable OS HR 1.31 per unit increase in log pKIM-1, 95% CI, 1.10 to 1.54). In long-term follow-up of Cohort 2, no metastatic events occurred, consistent with the favorable prognosis of resected cT1a RCC. CONCLUSION: Among patients with renal masses, pKIM-1 is associated with malignant pathology, worse MFS, and risk of death. pKIM-1 may be useful for selecting patients with renal masses for intervention versus surveillance.

CXCL9 Overexpression Predicts Better HCC Response to Anti-PD-1 Therapy and Promotes N1 Polarization of Neutrophils.

Background: Anti-programmed death-1 (PD1) antibodies have changed the treatment landscape for hepatocellular carcinoma (HCC) and exhibit promising treatment efficacy. However, the majority of HCCs still do not respond to anti-PD-1 therapy. Methods: We analyzed the expression of CXCL9 in blood samples from patients who received anti-PD-1 therapy and evaluated its correlation with clinicopathological characteristics and treatment outcomes. Based on the results of Cox regression analysis, a nomogram was established for predicting HCC response to anti-PD-1 therapy. qRT‒PCR and multiple immunofluorescence assays were utilized to analyze the proportions of N1-type neutrophils in vitro and in tumor samples, respectively. Results: The nomogram showed good predictive efficacy in the training and validation cohorts and may be useful for guiding clinical treatment of HCC patients. We also found that HCC cell-derived CXCL9 promoted N1 polarization of neutrophils in vitro and that AMG487, a specific CXCR3 inhibitor, significantly blocked this process. Moreover, multiple immunofluorescence (mIF) showed that patients with higher serum CXCL9 levels had greater infiltration of the N1 phenotype of tumor-associated neutrophils (TANs). Conclusion: Our study highlights the critical role of CXCL9 as an effective biomarker of immunotherapy efficacy and in promoting the polarization of N1-type neutrophils; thus, targeting the CXCL9-CXCR3 axis could represent a novel pharmaceutical strategy to enhance immunotherapy for HCC.

Sandwich-type electrochemical immunosensing of CA125 by using nanoribbon-like Ti3C2Tx MXenes and toluidine blue/UIO-66-NH2.

CA125 (carbohydrate antigen 125) is an important biomarker of ovarian cancer, so developing effective method for its detection is of great significance. In the present work, a novel sandwich-like electrochemical immunosensor (STEM) of CA125 was constructed by preparing nanoribbon-like Ti3C2Tx MXenes (Ti3C2TxNR) to immobilize primary antibody (PAb) of CA125 and UIO-66-NH2 MOFs structure to immobilize second antibody (SAb) and electroactive toluidine blue (Tb) probe. In this designed STEM assay, the as-prepared Ti3C2TxNR nanohybrid offers the advantages in large surface area and conductivity as carrier, and UIO-66-NH2 provided an ideal platform to accommodate SAb and a large number of Tb molecules as signal amplifier. In the presence of CA125, the peak currents of Tb from the formed STEM structure increase with the increase of CA125 level. After optimizing the related control conditions, a wide linear range (0.2-150.0 U mL-1) and a very low detection limit (0.05 U mL-1) of CA125 were achieved. It's thus expected the developed STEM strategy has important applications for the detection of CA125.

Extracellular vesicles derived from plasmodium-infected red blood cells alleviate cerebral malaria in plasmodium berghei ANKA-infected C57BL/6J mice.

RTS,S is the first malaria vaccine recommended for implementation among young children at risk. However, vaccine efficacy is modest and short-lived. To mitigate the risk of cerebral malaria (CM) among children under the age of 5, it is imperative to develop new vaccines. EVs are potential vaccine candidates as they obtain the ability of brain-targeted delivery and transfer plasmodium antigens and immunomodulators during infections. This study extracted EVs from BALB/c mice infected with Plasmodium yoelii 17XNL (P.y17XNL). C57BL/6J mice were intravenously immunized with EVs (EV-I.V. + CM group) or subcutaneously vaccinated with the combination of EVs and CpG ODN-1826 (EV + CPG ODN-S.C. + CM group) on days 0 and 20, followed by infection with Plasmodium berghei ANKA (P.bANKA) on day 20 post-second immunization. We monitored Parasitemia and survival rate. The integrity of the Blood-brain barrier (BBB) was examined using Evans blue staining.The levels of cytokines and adhesion molecules were evaluated using Luminex, RT-qPCR, and WB. Brain pathology was evaluated by hematoxylin and eosin and immunohistochemical staining. The serum levels of IgG, IgG1, and IgG2a were analyzed by enzyme-linked immunosorbent assay. Compared with those in the P.bANKA-infected group, parasitemia increased slowly, death was delayed (day 10 post-infection), and the survival rate reached 75 %-83.3 % in the EV-I.V. + ECM and EV + CPG ODN-S.C. + ECM groups. Meanwhile, compared with the EV + CPG ODN-S.C. + ECM group, although parasitemia was almost the same, the survival rate increased in the EV-I.V. + ECM group.Additionally, EVs immunization markedly downregulated inflammatory responses in the spleen and brain and ameliorated brain pathological changes, including BBB disruption and infected red blood cell (iRBC) sequestration. Furthermore, the EVs immunization group exhibited enhanced antibody responses (upregulation of IgG1 and IgG2a production) compared to the normal control group. EV immunization exerted protective effects, improving the integrity of the BBB, downregulating inflammation response of brain tissue, result in reduces the incidence of CM. The protective effects were determined by immunological pathways and brain targets elicited by EVs. Intravenous immunization exhibited better performance than subcutaneous immunization, which perhaps correlated with EVs, which can naturally cross BBB to play a better role in brain protection.

Supermolecular Confined Silicon Phosphorescence Nanoprobes for Time-Resolved Hypoxic Imaging Analysis.

Room temperature phosphorescence (RTP) nanoprobes play crucial roles in hypoxia imaging due to their high signal-to-background ratio (SBR) in the time domain. However, synthesizing RTP probes in aqueous media with a small size and high quantum yield remains challenging for intracellular hypoxic imaging up to present. Herein, aqueous RTP nanoprobes consisting of naphthalene anhydride derivatives, cucurbit[7]uril (CB[7]), and organosilicon are reported via supermolecular confined methods. Benefiting from the noncovalent confinement of CB[7] and hydrolysis reactions of organosilicon, such small-sized RTP nanoprobes (5-10 nm) exhibit inherent tunable phosphorescence (from 400 to 680 nm) with microsecond second lifetimes (up to ∼158.7 µs) and high quantum yield (up to ∼30%). The as-prepared RTP nanoprobes illustrate excellent intracellular hypoxia responsibility in a broad range from ∼0.1 to 21% oxygen concentrations. Compared to traditional fluorescence mode, the SBR value (∼108.69) of microsecond-range time-resolved in vitro imaging is up to 2.26 times greater in severe hypoxia (<0.1% O2), offering opportunities for precision imaging analysis in a hypoxic environment.

Repolarization of Immunosuppressive Macrophages by Targeting SLAMF7-Regulated CCL2 Signaling Sensitizes Hepatocellular Carcinoma to Immunotherapy.

Immune checkpoint inhibitors have limited efficacy in hepatocellular carcinoma (HCC). Macrophages are the most abundant immune cells in HCC, suggesting that a better understanding of the intrinsic processes by which tumor cells regulate macrophages could help identify strategies to improve response to immunotherapy. As signaling lymphocytic activation molecule (SLAM) family members regulate various immune functions, we investigated the role of specific SLAM receptors in the immunobiology of HCC. Comparison of the transcriptomic landscapes of immunotherapy-responsive and nonresponsive patients with advanced HCC identified SLAMF7 upregulation in immunotherapy-responsive HCC, and patients with HCC who responded to immunotherapy also displayed higher serum levels of SLAMF7. Loss of Slamf7 in liver-specific knockout mice led to increased hepatocarcinogenesis and metastasis, elevated immunosuppressive macrophage infiltration, and upregulated PD-1 expression in CD8+ T cells. HCC cell-intrinsic SLAMF7 suppressed MAPK/ATF2-mediated CCL2 expression to regulate macrophage migration and polarization in vitro. Mechanistically, SLAMF7 associated with SH2 domain-containing adaptor protein B (SHB) through its cytoplasmic 304 tyrosine site to facilitate the recruitment of SHIP1 to SLAMF7 and inhibit the ubiquitination of TRAF6, thereby attenuating MAPK pathway activation and CCL2 transcription. Pharmacological antagonism of the CCL2/CCR2 axis potentiated the therapeutic effect of anti-PD-1 antibody in orthotopic HCC mouse models with low SLAMF7 expression. In conclusion, this study highlights SLAMF7 as a regulator of macrophage function and a potential predictive biomarker of immunotherapy response in HCC. Strategies targeting CCL2 signaling to induce macrophage repolarization in HCC with low SLAMF7 might enhance the efficacy of immunotherapy. SIGNIFICANCE: CCL2 upregulation caused by SLAMF7 deficiency in hepatocellular carcinoma cells induces immunosuppressive macrophage polarization and confers resistance to immune checkpoint blockade, providing potential biomarkers and targets to improve immunotherapy response in patients.

Multi-colour room-temperature phosphorescence from fused-ring compounds for dynamic anti-counterfeiting applications.

We present a facile strategy to achieve purely organic multi-colour room-temperature phosphorescence (RTP) films by doping typical fused-ring compounds into a poly(vinyl alcohol) matrix. Such RTP films demonstrate inherent RTP emission ranging from green to red with a long lifetime and high quantum yield (QY) (lifetime: ∼0.56 ms, QY: ∼35.4%). We further exploit such high-performance RTP films for dynamic information encryption.

Derivation and external validation of a simple risk score for predicting severe acute kidney injury after intravenous cisplatin: cohort study.

OBJECTIVE: To develop and externally validate a prediction model for severe cisplatin associated acute kidney injury (CP-AKI). DESIGN: Multicenter cohort study. SETTING: Six geographically diverse major academic cancer centers across the US. PARTICIPANTS: Adults (≥18 years) receiving their first dose of intravenous cisplatin, 2006-22. MAIN OUTCOME MEASURES: The primary outcome was CP-AKI, defined as a twofold or greater increase in serum creatinine or kidney replacement therapy within 14 days of a first dose of intravenous cisplatin. Independent predictors of CP-AKI were identified using a multivariable logistic regression model, which was developed in a derivation cohort and tested in an external validation cohort. For the primary model, continuous variables were examined using restricted cubic splines. A simple risk model was also generated by converting the odds ratios from the primary model into risk points. Finally, a multivariable Cox model was used to examine the association between severity of CP-AKI and 90 day survival. RESULTS: A total of 24 717 adults were included, with 11 766 in the derivation cohort (median age 59 (interquartile range (IQR) 50-67)) and 12 951 in the validation cohort (median age 60 (IQR 50-67)). The incidence of CP-AKI was 5.2% (608/11 766) in the derivation cohort and 3.3% (421/12 951) in the validation cohort. Each of the following factors were independently associated with CP-AKI in the derivation cohort: age, hypertension, diabetes mellitus, serum creatinine level, hemoglobin level, white blood cell count, platelet count, serum albumin level, serum magnesium level, and cisplatin dose. A simple risk score consisting of nine covariates was shown to predict a higher risk of CP-AKI in a monotonic fashion in both the derivation cohort and the validation cohort. Compared with patients in the lowest risk category, those in the highest risk category showed a 24.00-fold (95% confidence interval (CI) 13.49-fold to 42.78-fold) higher odds of CP-AKI in the derivation cohort and a 17.87-fold (10.56-fold to 29.60-fold) higher odds in the validation cohort. The primary model had a C statistic of 0.75 and showed better discrimination for CP-AKI than previously published models, the C statistics for which ranged from 0.60 to 0.68 (DeLong P<0.001 for each comparison). Greater severity of CP-AKI was monotonically associated with shorter 90 day survival (adjusted hazard ratio 4.63 (95% CI 3.56 to 6.02) for stage 3 CP-AKI versus no CP-AKI). CONCLUSION: This study found that a simple risk score based on readily available variables from patients receiving intravenous cisplatin could predict the risk of severe CP-AKI, the occurrence of which is strongly associated with death.

Chemokine CCL21 determines immunotherapy response in hepatocellular carcinoma by affecting neutrophil polarization.

BACKGROUND: The efficacy of immune checkpoint inhibitors (ICIs) in hepatocellular carcinoma (HCC) is poor and great heterogeneity among individuals. Chemokines are highly correlated with tumor immune response. Here, we aimed to identify an effective chemokine for predicting the efficacy of immunotherapy in HCC. METHODS: Chemokine C-C motif ligand 21 (CCL21) was screened by transcriptomic analysis in tumor tissues from HCC patients with different responses to ICIs. The least absolute shrinkage and selection operator (LASSO) regression analysis was conducted to construct a predictive nomogram. Neutrophils in vitro and HCC subcutaneous tumor model in vivo were applied to explore the role of CCL21 on the tumor microenvironment (TME) of HCC. RESULTS: Transcriptome analysis showed that CCL21 level was much higher in HCC patients with response to immunotherapy. The predictive nomogram was constructed and validated as a classifier. CCL21 could inhibit N2 neutrophil polarization by suppressing the activation of nuclear factor kappa B (NF-κB) pathway. In addition, CCL21 enhanced the therapeutic efficacy of ICIs. CONCLUSION: CCL21 may serve as a predictive biomarker for immunotherapy response in HCC patients. High levels of CCL21 in TME inhibit immunosuppressive polarization of neutrophils. CCL21 in combination with ICIs may offer a novel therapeutic strategy for HCC.

Diagnostic and Prognostic Ability of Contrast-Enhanced Unltrasound and Biomarkers in Hepatocellular Carcinoma Subtypes.

OBJECTIVE: To investigate the diagnostic and prognostic value of contrast-enhanced ultrasound (CEUS) and clinical indicators of the vessels encapsulating tumor clusters (VETC) pattern and macrotrabecular-massive subtype in hepatocellular carcinoma (MTM-HCC). METHODS: This retrospective study included patients who underwent preoperative CEUS and hepatectomy for HCC between August 2018 and August 2021. Multivariable logistic regression was performed to select independent correlated factors of VETC-HCC and MTM-HCC to develop nomogram models. The association between model outcomes and early postoperative HCC recurrence was assessed using Kaplan-Meier curve and Cox regression analysis. RESULTS: The training cohort included 182 patients (54.3 ± 11.3 years, 168 males) and the validation cohort included 91 patients (54.8 ± 10.6 years, 81 males). Multivariate logistic regression analysis revealed that α-fetoprotein (AFP) levels (odds ratio [OR]: 2.26, 95% confidence interval [CI]: 1.49-3.42, p < 0.001), intratumoral nonenhancement (OR: 2.40, 95% CI: 1.02-5.64, p = 0.044), and the perfusion pattern in the CEUS arterial phase (OR: 2.27, 95% CI: 1.05-4.91, p = 0.038) were independent predictors of VETC-HCC. Besides, the former two were also independently associated with MTM-HCC (AFP level: OR: 2.36, 95% CI: 1.36-4.09, p = 0.002; intratumoral nonenhancement: OR: 3.72, 95% CI: 1.02-13.56, p = 0.046). Nomogram models were constructed based on the aforementioned indicators. Kaplan-Meier curve analysis indicated that predicted VETC-HCC or MTM-HCC exhibited higher rates of early recurrence (log-rank p < 0.001 and p = 0.002, respectively). Cox regression analysis showed that a high risk of VETC-HCC was independently correlated with early recurrence (p = 0.011). CONCLUSION: CEUS combined with AFP levels can predict VETC-HCC/MTM-HCC and prognosis preoperatively.

Association of genetic polymorphisms with COVID-19 infection and outcomes: An updated meta-analysis based on 62 studies.

Background: The relationship between genetic polymorphisms and coronavirus disease 2019 (COVID-19) remains to be inconsistent. This meta-analysis aimed to provide an updated evaluation of the role of genetic polymorphisms in the infection, severity and mortality of COVID-19 based on all available published studies. Methods: A systematic search was performed using six databases: PubMed, Embase, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure (CNKI) and Wanfang. Summary odds ratios (ORs) and corresponding 95 % confidence intervals (CIs) were used to calculate the genotypic comparison. All statistical analyses were conducted in Stata 12.0. Results: A total of 62 studies with 19600 cases and 28899 controls was included in this meta-analysis. For COVID-19 infection, ACE Ins/Del polymorphism might be related with significantly decreased risk of COVID-19 infection under dominant, homozygote and allelic models. Meanwhile, the IFITM3 rs12252 and TMPRSS2 rs12329760 polymorphisms were significantly associated with the increased risk of COVID-19 infection under one or more models. Regarding COVID-19 severity, ACE2 rs2074192, ACE2 rs2106809, IFITM3 rs12252 and VDR rs1544410 polymorphisms might be related with significantly increased risk of COVID-19 severity in one or more models. Moreover, the analysis of TMPRSS2 rs2070788 indicated that a variant A allele decreased the risk of COVID-19 severity in recessive model. For COVID-19 mortality, the variant C allele of IFITM3 rs12252 polymorphism might be related with significantly increased risk of COVID-19 mortality under all genetic models. Conclusions: This meta-analysis indicated that he infection, severity or mortality of COVID-19 were related to the above genetic polymorphisms, which might provide an important theoretical basis for understanding the clinical feature of COVID-19 disease.

Development and Comparison of Prediction Models Based on Sonovue- and Sonazoid-Enhanced Ultrasound for Pathologic Grade and Microvascular Invasion in Hepatocellular Carcinoma.

OBJECTIVE: This study was aimed at developing and comparing prediction models based on Sonovue and Sonazoid contrast-enhanced ultrasound (CEUS) in predicting pathologic grade and microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Also investigated was whether Kupffer phase images have additional predictive value for the above pathologic features. METHODS: Ninety patients diagnosed with primary HCC who had undergone curative hepatectomy were prospectively enrolled. All patients underwent conventional ultrasound (CUS), Sonovue-CEUS and Sonazoid-CEUS examinations pre-operatively. Clinical, radiologic and pathologic features including pathologic grade, MVI and CD68 expression were collected. We developed prediction models comprising clinical, CUS and CEUS (Sonovue and Sonazoid, respectively) features for pathologic grade and MVI with both the logistic regression and machine learning (ML) methods. RESULTS: Forty-one patients (45.6%) had poorly differentiated HCC (p-HCC) and 37 (41.1%) were MVI positive. For pathologic grade, the logistic model based on Sonazoid-CEUS had significantly better performance than that based on Sonovue-CEUS (area under the curve [AUC], 0.929 vs. 0.848, p = 0.035), whereas for MVI, these two models had similar accuracy (AUC, 0.810 vs. 0.786, p = 0.068). Meanwhile, we found that well-differentiated HCC tended to have a higher enhancement ratio in 6-12 min during the Kupffer phase of Sonazoid-CEUS, as well as higher CD68 expression compared with p-HCC. In addition, all of these models can effectively predict the risk of recurrence (p < 0.05). CONCLUSION: Sonovue-CEUS and Sonazoid-CEUS were comparably excellent in predicting MVI, while Sonazoid-CEUS was superior to Sonovue-CEUS in predicting pathologic grade because of the Kupffer phase. The enhancement ratio in the Kupffer phase has additional predictive value for pathologic grade prediction.

Novel phenoxy-((phenylethynyl) selanyl) propan-2-ol derivatives as potential anticancer agents.

Selenocompounds protect against damage to healthy cells and induce the death of tumor cells by apoptosis; for this reason, they are attractive compounds for cancer research. In the present study, two series of novel phenoxy-((phenylethynyl) selanyl) propan-2-ol derivatives were synthesized, and their anti-proliferation activities were evaluated. Of the 23 compounds synthesized, most showed potent anti-proliferative activity against human cancer cell lines. Specifically, compounds 3h, 3g, and 3h-2, which had a 2- or 4-position halogen substituent on 1-((phenylethynyl)selanyl)-3-phenoxypropan-2-ol, exhibited the best anti-proliferative activity against tumor cells. Flow cytometry demonstrated that 3h, 3g, and 3h-2 induced G2/M phase arrest and apoptosis in A549 cells. Cellular studies demonstrated that the induction of apoptosis by 3h correlated with changes in the expression of cell cycle-related proteins and apoptosis-related proteins. Xenograft tumor experiments in nude mice revealed that compound 3h has antitumor effects in vivo and no evident toxic effects in nude mice. In addition, compound 3h alleviated cisplatin-induced liver and kidney damage. These findings uncover the applicability of compound 3h as a novel lead compound for cancer treatment.

Phosphorescence Enzyme-Mimics for Time-Resolved Sensitive Diagnostics and Environment-Adaptive Specific Catalytic Therapeutics.

Enzyme mimics (EMs) with intrinsic catalysis activity have attracted enormous interest in biomedicine. However, there is a lack of environmentally adaptive EMs for sensitive diagnosis and specific catalytic therapeutics in simultaneous manners. Herein, the coordination modulation strategy is designed to synthesize silicon-based phosphorescence enzyme-mimics (SiPEMs). Specifically, the atomic-level engineered Co-N4 structure in SiPEMs enables the environment-adaptive peroxidase, oxidase, and catalase-like activities. More intriguingly, the internal Si-O networks are able to stabilize the triplet state, exhibiting long-lived phosphorescence with lifetime of 124.5 ms, suitable for millisecond-range time-resolved imaging of tumor cells and tissue in mice (with high signal-to-background ratio values of ∼60.2 for in vitro and ∼611 for in vivo). Meanwhile, the SiPEMs act as an oxidative stress amplifier, allowing the production of ·OH via cascade reactions triggered by the tumor microenvironment (∼136-fold enhancement in peroxidase catalytic efficiency); while the enzyme-mimics can scavenge the accumulation of reactive oxygen species to alleviate the oxidative damage in normal cells, they are therefore suitable for environment-adaptive catalytic treatment of cancer in specific manners. We innovate a systematic strategy to develop high-performance enzymemics, constructing a promising breakthrough for replacing traditional enzymes in cancer treatment applications.

Micromotor-Enabled Active Hydrogen and Tobramycin Delivery for Synergistic Sepsis Therapy.

Sepsis is a highly heterogeneous syndrome normally characterized by bacterial infection and dysregulated systemic inflammatory response that leads to multiple organ failure and death. Single anti-inflammation or anti-infection treatment exhibits limited survival benefit for severe cases. Here a biodegradable tobramycin-loaded magnesium micromotor (Mg-Tob motor) is successfully developed as a potential hydrogen generator and active antibiotic deliverer for synergistic therapy of sepsis. The peritoneal fluid of septic mouse provides an applicable space for Mg-water reaction. Hydrogen generated sustainably and controllably from the motor interface propels the motion to achieve active drug delivery along with attenuating hyperinflammation. The developed Mg-Tob motor demonstrates efficient protection from anti-inflammatory and antibacterial activity both in vitro and in vivo. Importantly, it prevents multiple organ failure and significantly improves the survival rate up to 87.5% in a high-grade sepsis model with no survival, whereas only about half of mice survive with the individual therapies. This micromotor displays the superior therapeutic effect of synergistic hydrogen-chemical therapy against sepsis, thus holding great promise to be an innovative and translational drug delivery system to treat sepsis or other inflammation-related diseases in the near future.

Physiological and biochemical responses of soft coral Sarcophyton trocheliophorum to doxycycline hydrochloride exposure.

In light of the rapid expansion of the marine aquaculture industry, there has been widespread and irregular usage of aquatic drugs to combat biological diseases, which significantly impact the neighboring aquatic ecosystems. This study delves into the impact of the antibiotic aquatic drug known as doxycycline hydrochloride (DOX) on offshore soft corals, providing valuable data for the responsible use and management of aquatic drugs. In this investigation, we subjected Sarcophyton trocheliophorum to acute exposure to varying concentrations of DOX (0, 1, 5, and 10 mg L-1). We meticulously assessed critical parameters and observed alterations in protein levels, superoxide dismutase (SOD) activity, catalase (CAT) activity, lipid peroxidation (LPO), malondialdehyde (MDA) levels, Acid phosphatase (ACP) activity, alkaline phosphatase (AKP) activity, glutathione (GSH) concentration, glutathione S-transferase (GST) activity, glutathione Peroxidase (GSH-Px) activity, zooxanthellae density, and chlorophyll content. Our findings reveal that in the presence of DOX-induced environmental stress, there is a significant increase in LPO, MDA, chlorophyll, carotenoid levels, and the activities of ACP, GST, and GSH-Px in soft corals. Simultaneously, there is a noteworthy decrease in zooxanthellae density. Additionally, the protein concentration and SOD activity in soft corals experience substantial reduction when exposed to 5 mg L-1 DOX. Notably, CAT activity varies significantly in environments with 1 and 10 mg L-1 DOX. Moreover, these conditions exhibit a discernible influence on AKP activity, GSH content, and chlorophyll levels. These findings suggest that DOX exposure carries the potential for toxicity in aquaculture settings, affecting protein synthesis in soft corals and influencing oxidative stress, lipid peroxidation, immunity, and detoxification processes within these organisms. There is also a risk of compromising the coral defense system, potentially leading to coral bleaching. Furthermore, this study underscores the significant impact on photosynthesis, growth, and the metabolic dynamics of the coral-zooxanthellae symbiotic system. Consequently, our research offers vital insights into the mortality and bleaching effects of aquatic drugs on marine corals, offering a foundation for the prudent use and management of such substances.

Detection of Entangled States Supported by Reinforcement Learning.

Discrimination of entangled states is an important element of quantum-enhanced metrology. This typically requires low-noise detection technology. Such a challenge can be circumvented by introducing nonlinear readout process. Traditionally, this is realized by reversing the very dynamics that generates the entangled state, which requires a full control over the system evolution. In this Letter, we present nonlinear readout of highly entangled states by employing reinforcement learning to manipulate the spin-mixing dynamics in a spin-1 atomic condensate. The reinforcement learning found results in driving the system toward an unstable fixed point, whereby the (to be sensed) phase perturbation is amplified by the subsequent spin-mixing dynamics. Working with a condensate of 10 900 ^{87}Rb atoms, we achieve a metrological gain of 6.97_{-1.38}^{+1.30} dB beyond the classical precision limit. Our work will open up new possibilities in unlocking the full potential of entanglement caused quantum enhancement in experiments.