Molecular mechanism of the metal-independent production of hydroxyl radicals by thiourea dioxide and H2O2.

It is well-known that highly reactive hydroxyl radicals (HO•) can be produced by the classic Fenton system and our recently discovered haloquinone/H2O2 system, but rarely from thiol-derivatives. Here, we found, unexpectedly, that HO• can be generated from H2O2 and thiourea dioxide (TUO2), a widely used and environmentally friendly bleaching agent. A carbon-centered radical and sulfite were detected and identified as the transient intermediates, and urea and sulfate as the final products, with the complementary application of electron spin-trapping, oxygen-18 isotope labeling coupled with HPLC/MS analysis. Density functional theory calculations were conducted to further elucidate the detailed pathways for HO• production. Taken together, we proposed that the molecular mechanism for HO• generation by TUO2/H2O2: TUO2 tautomerizes from sulfinic acid into ketone isomer (TUO2-K) through proton transfer, then a nucleophilic addition of H2O2 on the S atom of TUO2-K, forming a S-hydroperoxide intermediate TUO2-OOH, which dissociates homolytically to produce HO•. Our findings represent the first experimental and computational study on an unprecedented new molecular mechanism of HO• production from simple thiol-derived sulfinic acids, which may have broad chemical, environmental, and biomedical significance for future research on the application of the well-known bleaching agent and its analogs.

Enhancing Light Out-coupling in Perovskite Light-Emitting Diodes through Plasmonic Nanostructures.

Perovskite light-emitting diodes (PeLEDs) have emerged as promising candidates for lighting and display technologies owing to their high photoluminescence quantum efficiency and high carrier mobility. However, the performance of planar PeLEDs is limited by the out-coupling efficiency, predominantly governed by photonic losses at device interfaces. Most notably, the plasmonic loss at the metal electrode interfaces can account for up to 60% of the total loss. Here, we investigate the use of plasmonic nanostructures to improve the light out-coupling in PeLEDs. By integrating these nanostructures with PeLEDs, we have demonstrated an effectively reduced plasmonic loss and enhanced light out-coupling. As a result, the nanostructured PeLEDs exhibit an average 1.5-fold increase in external quantum efficiency and an ∼20-fold improvement in device lifetime. This finding offers a generic approach for enhancing light out-coupling, promising great potential to go beyond existing performance limitations.

Species delimitation in Amana (Liliaceae): transcriptomes battle with evolutionary complexity.

Species delimitation has long been a subject of controversy, and there are many alternative concepts and approaches used to define species in plants. The genus Amana (Liliaceae), known as "East Asian tulips" has a number of cryptic species and a huge genome size (1C = 21.48-57.35 pg). It also is intriguing how such a spring ephemeral genus thrives in subtropical areas. However, phylogenetic relationships and species delimitation within Amana are challenging. Here we included all species and 84 populations of Amana, which are collected throughout its distribution range. A variety of methods were used to clarify its species relationships based on a combination of morphological, ecological, genetic, evolutionary and phylogenetic species concepts. This evidence supports the recognition of at least 12 species in Amana. Moreover, we explored the complex evolutionary history within the genus and detected several historical hybridization and introgression events based on phylogenetic trees (transcriptomic and plastid), phylonetworks, admixture and ABBA-BABA analyses. Morphological traits have undergone parallel evolution in the genus. This spring ephemeral genus might have originated from a temperate region, yet finally thrives in subtropical areas, and three hypotheses about its adaptive evolution are proposed for future testing. In addition, we propose a new species, Amana polymorpha, from eastern Zhejiang Province, China. This research also demonstrates that molecular evidence at the genome level (such as transcriptomes) has greatly improved the accuracy and reasonability of species delimitation and taxon classification.

The Osmolality and Hemolysis of High-Concentration Monoclonal Antibody Formulations.

PURPOSES: Highly concentrated monoclonal antibody (mAb) formulations for subcutaneous administration are becoming increasingly preferred within the biopharmaceutical industry for ease of use and improved patient compliance. A common phenomenon observed in the industry is that osmolality detected via freezing-point depression (FPD) in high-concentration mAb formulations is much higher than the theoretical concentrations, yet the occurrence of this phenomenon and its possible safety issues have been rarely reported. METHODS: The current study summarized theoretical osmolality of U.S. Food and Drug Administration approved high-concentration mAb formulations and evaluated effects of high osmolality on safety using hemolysis experiments for the first time. Two mAbs formulated at 150 mg/mL were used as models and configured into two isotonic solutions: a, a theoretically calculated molarity in the isotonic range (H) and b, an osmolality value measured via the FPD in the isotonic range (I). The H and I formulations of each mAb were individually subjected to hemolysis experiments, and the hemolysis rates of the two formulations of the same mAb were compared. Besides, the effect of mAb concentration on osmolality detected by FPD was explored as well. RESULTS: The results indicated that the hemolysis rates were similar between the H and I formulations of mAbs at the same sample addition volume, and the osmolality values increased approximately linearly with the increase in mAb concentration. CONCLUSIONS: High osmolality for high-concentration mAb formulations would not affect product safety and the excipients could be added at relatively high levels to maintain product stability, especially for labile products.

LNAS: a clinically applicable deep-learning system for mediastinal enlarged lymph nodes segmentation and station mapping without regard to the pathogenesis using unenhanced CT images.

BACKGROUND: The accurate identification and evaluation of lymph nodes by CT images is of great significance for disease diagnosis, treatment, and prognosis. PURPOSE: To assess the lymph nodes' segmentation, size, and station by artificial intelligence (AI) for unenhanced chest CT images and evaluate its value in clinical scenarios. MATERIAL AND METHODS: This retrospective study proposed an end-to-end Lymph Nodes Analysis System (LNAS) consisting of three models: the Lymph Node Segmentation model (LNS), the Mediastinal Organ Segmentation model (MOS), and the Lymph Node Station Registration model (LNR). We selected a healthy chest CT image as the template image and annotated 14 lymph node station masks according to the IASLC to build the lymph node station mapping template. The exact contours and stations of the lymph nodes were annotated by two junior radiologists and reviewed by a senior radiologist. Patients aged 18 and above, who had undergone unenhanced chest CT and had at least one suspicious enlarged mediastinal lymph node in imaging reports, were included. Exclusions were patients who had thoracic surgeries in the past 2 weeks or artifacts on CT images affecting lymph node observation by radiologists. The system was trained on 6725 consecutive chest CTs that from Tianjin Medical University General Hospital, among which 6249 patients had suspicious enlarged mediastinal lymph nodes. A total of 519 consecutive chest CTs from Qilu Hospital of Shandong University (Qingdao) were used for external validation. The gold standard for each CT was determined by two radiologists and reviewed by one senior radiologist. RESULTS: The patient-level sensitivity of the LNAS system reached of 93.94% and 92.89% in internal and external test dataset, respectively. And the lesion-level sensitivity (recall) reached 89.48% and 85.97% in internal and external test dataset. For man-machine comparison, AI significantly apparently shortened the average reading time (p < 0.001) and had better lesion-level and patient-level sensitivities. CONCLUSION: AI improved the sensitivity lymph node segmentation by radiologists with an advantage in reading time.

Construction of a Risk Prediction Model for Intraoperative Hypothermia in Patients Undergoing Lower Extremity Joint Replacement.

PURPOSE: To investigate the influencing factors of intraoperative hypothermia (IOH) in patients undergoing total joint arthroplasty (TJA) of the lower extremities, establish a risk prediction model, and test the effect of application. DESIGN: A prospective, observational study was conducted. METHODS: Patients who underwent total knee arthroplasty and total hip arthroplasty from June 2020 to December 2021 were prospectively analyzed. According to the occurrence of IOH, patients were divided into the IOH group (temperature less than 36 °C) and non-IOH group (temperature ≥36 °C). We collected demographic, anesthesia, and surgical data for both groups to identify risk factors for IOH and develop a predictive model. The model's goodness of fit was assessed using the Hosmer-Lemeshow test, and its predictive efficacy was evaluated using the receiver operating characteristic curve. FINDINGS: A total of 258 patients were included in this study, with 79 patients in the IOH group and 179 patients in the non-IOH group. Logistic regression analysis showed that American Society of Anesthesiologists' grade, blood loss, and duration of surgery were independent risk factors for IOH in lower extremity TJA patients. Hosmer-Lemeshow test P = .803, area under receiver operating characteristic curve was 0.846, Youden index was 0.490, sensitivity was 65.4%, specificity was 83.6%. In the external validation cohort, the application accuracy of the model was 83.3%. CONCLUSIONS: The prediction model established in this study is suitable for the risk assessment of IOH in TJA patients with good prediction effect, which can provide a tool for clinical medical staff to identify high-risk populations preoperatively.

Molecular mechanism for the unusual enhancement of the second-step chemiluminescence production from the carcinogenic tetrabromohydroquinone and H2O2.

We have found recently that two-step intrinsic hydroxyl radical (·OH)-dependent chemiluminescence (CL) could be produced by carcinogenic tetrahaloquinone and H2O2. However, the first-step CL was too fast to clearly detect the stepwise generation of ·OH and CL, and to distinguish the exact dividing point between the first-step and second-step CL. Here we found that, extremely clear two-step intrinsic CL could be produced by the relative slow reaction of tetrabromohydroquinone (TBHQ) with H2O2, which was directly dependent on the two-step ·OH generation. Interestingly, the second-step, but not the first-step CL production of TBHQ/H2O2 (CRET donor) was markedly enhanced by fluorescein (a typical xanthene dye, CRET acceptor) through a unique chemiluminescence resonance energy transfer (CRET) process. The novel CRET system of TBHQ/H2O2/fluorescein was successfully applied for the sensitive detection of TBHQ with the detection limit as low as 2.5 µmol/L. These findings will help to develop more sensitive and highly efficient CL or CRET systems and specific CL sensor to detect the carcinogenic haloquinones, which may have broad environmental applications.

High levels of uric acid inhibit BAT thermogenic capacity through regulation of AMPK.

Hyperuricemia (HUA) is strongly associated with the increasing prevalence of obesity, but the underlying mechanism remains elusive. Dysfunction of brown adipose tissue (BAT) could lead to obesity. However, studies on the role of HUA on BAT are lacking. Our retrospective clinical analysis showed that serum uric acid (UA) is significantly associated with BAT in humans. To investigate the role of UA in regulating BAT function, we used UA to treat primary brown adipocytes (BACs) in vitro and established HUA mice. In vitro results showed that HUA suppressed thermogenic gene expression and oxygen consumption rate. Accordingly, HUA mice exhibited lower energy expenditure and body temperature, with larger lipid droplets and lower thermogenic gene expression. These results demonstrate that HUA inhibits BAT thermogenic capacity in vitro and in vivo. To further elucidate the mechanism of UA on adipocytes, mRNA-sequencing analysis was performed and screened for "AMP-activated protein kinase (AMPK) signaling pathway" and "mitochondrial biogenesis." Further tests in vivo and in vitro showed that the phosphorylation of AMPK was suppressed by HUA. Activation of AMPK alleviated the inhibition of AMPK phosphorylation by HUA and increased mitochondrial biogenesis, subsequently restoring the impaired BAT thermogenic capacity in vitro and vivo. Thus, we confirmed that HUA suppresses mitochondrial biogenesis by regulating AMPK, thereby inhibiting BAT thermogenic capacity. Taken together, our study identifies UA as a novel regulator of BAT thermogenic capacity, providing a new strategy to combat obesity.NEW & NOTEWORTHY To investigate the effect and mechanism of UA on BAT thermogenic capacity, we established HUA models in vitro and in vivo, and performed RNA sequencing analysis. Our results revealed that HUA suppresses mitochondrial biogenesis by regulating AMPK, thereby inhibiting BAT thermogenic capacity. Taken together, our study identifies UA as a novel regulator of BAT thermogenic capacity, providing a new strategy to combat obesity.

Hexagon AgNCs/PVP Crystallization Induced Cathode Electrochemiluminescence Enhancement for miRNA221 Biosensing.

Aggredation-induced electrochemiluminescence (AIECL) promises an efficient strategy for synthesize highly luminescent emitter and co-reactant for ECL analysis, however, rational control of electrogenerated emission intensity is still challenging. The low electroconductivity and amorphous molecular configuration are intrinsic bottleneck. This work reveals the impact of polyvinyl pyrrolidone backbone regulated silver nanocrystallines (AgNCs/PVP) on the cathode AIECL properties in near infrared region, by employing the Box-Behnken designed response surface computation model to modulate crystal aggregates. Electron paramagnetic resonance spectroscopy discovered hydrogen radical (HO• ) dominant reductive-oxidative (R-O) ECL mechanism with AgNCs acting as the co-reaction accelerator in graphene oxide/persulfate system (GO/S2 O8 2- ). Both theoretical calculation and experimental measurement testified that the ECL of AgNCs in GO/S2 O8 2- dependent on the concentration of in situ electrochemical oxidized Ag+ . The high efficiency of crystallization-induced enhanced ECL (CIECL) originates from 1) the effective electron transfer of Ag+ accelerated HO• produce to notable promote radioactive transition, and 2) twisted intramolecular charge transfer from the electron-rich donor of PVP to electron-deficient receptor of Ag0 to restrict nonradioactive transition. The AgNCs/PVP with CIECL effect are applied to construct an ultrasensitive platform for miR-221 assay with a lower detection limit of 7.47 × 103  copies mL-1 than typical qPCR method.

CAFs shape myeloid-derived suppressor cells to promote stemness of intrahepatic cholangiocarcinoma through 5-lipoxygenase.

BACKGROUND AND AIMS: We previously demonstrated that cancer-associated fibroblasts (CAFs) promote tumor growth through recruitment of myeloid-derived suppressor cells (MDSCs). 5-lipoxygenase (5-LO) is highly expressed in myeloid cells and is critical for synthesizing leukotriene B4 (LTB4), which is involved in tumor progression by activating its receptor leukotriene B4 receptor type 2 (BLT2). In this study, we investigated whether and how CAFs regulate MDSC function to enhance cancer stemness, the driving force of the cancer aggressiveness and chemotherapy refractoriness, in highly desmoplastic intrahepatic cholangiocarcinoma (ICC). APPROACH AND RESULTS: RNA-sequencing analysis revealed enriched metabolic pathways but decreased inflammatory pathways in cancer MDSCs compared with blood MDSCs from patients with ICC. Co-injection of ICC patient-derived CAFs promoted cancer stemness in an orthotopic ICC model, which was blunted by MDSC depletion. Conditioned media (CM) from CAF-educated MDSCs drastically promoted tumorsphere formation efficiency and stemness marker gene expression in ICC cells. CAF-CM stimulation increased expression and activity of 5-LO in MDSCs, while 5-LO inhibitor impaired the stemness-enhancing capacity of MDSCs in vitro and in vivo. Furthermore, IL-6 and IL-33 primarily expressed by CAFs mediated hyperactivated 5-LO metabolism in MDSCs. We identified the LTB4-BLT2 axis as the critical downstream metabolite signaling of 5-LO in promoting cancer stemness, as treatment with LTB4 was elevated in CAF-educated MDSCs, or blockade of BLT2 (which was preferentially expressed in stem-like ICC cells) significantly reduced stemness-enhancing effects of CAF-educated MDSCs. Finally, BLT2 blockade augmented chemotherapeutic efficacy in ICC patient-derived xenograft models. CONCLUSIONS: Our study reveals a role for CAFs in orchestrating the optimal cancer stemness-enhancing microenvironment by educating MDSCs, and suggests the 5-LO/LTB4-BLT2 axis as promising therapeutic targets for ICC chemoresistance by targeting cancer stemness.

Correlation between AI-based CT organ features and normal lung dose in adjuvant radiotherapy following breast-conserving surgery: a multicenter prospective study.

BACKGROUND: Radiation pneumonitis (RP) is one of the common side effects after adjuvant radiotherapy in breast cancer. Irradiation dose to normal lung was related to RP. We aimed to propose an organ features based on deep learning (DL) model and to evaluate the correlation between normal lung dose and organ features. METHODS: Patients with pathology-confirmed invasive breast cancer treated with adjuvant radiotherapy following breast-conserving surgery in four centers were included. From 2019 to 2020, a total of 230 patients from four nationwide centers in China were screened, of whom 208 were enrolled for DL modeling, and 22 patients from another three centers formed the external testing cohort. The subset of the internal testing cohort (n = 42) formed the internal correlation testing cohort for correlation analysis. The outline of the ipsilateral breast was marked with a lead wire before the scanning. Then, a DL model based on the High-Resolution Net was developed to detect the lead wire marker in each slice of the CT images automatically, and an in-house model was applied to segment the ipsilateral lung region. The mean and standard deviation of the distance error, the average precision, and average recall were used to measure the performance of the lead wire marker detection model. Based on these DL model results, we proposed an organ feature, and the Pearson correlation coefficient was calculated between the proposed organ feature and ipsilateral lung volume receiving 20 Gray (Gy) or more (V20). RESULTS: For the lead wire marker detection model, the mean and standard deviation of the distance error, AP (5 mm) and AR (5 mm) reached 3.415 ± 4.529, 0.860, 0.883, and 4.189 ± 8.390, 0.848, 0.830 in the internal testing cohort and external testing cohort, respectively. The proposed organ feature calculated from the detected marker correlated with ipsilateral lung V20 (Pearson correlation coefficient, 0.542 with p < 0.001 in the internal correlation testing cohort and 0.554 with p = 0.008 in the external testing cohort). CONCLUSIONS: The proposed artificial Intelligence-based CT organ feature was correlated with normal lung dose in adjuvant radiotherapy following breast-conserving surgery in patients with invasive breast cancer. TRIAL REGISTRATION: NCT05609058 (08/11/2022).

A pre-treatment CT-based weighted radiomic approach combined with clinical characteristics to predict durable clinical benefits of immunotherapy in advanced lung cancer.

OBJECTIVES: To develop a pre-treatment CT-based predictive model to anticipate inoperable lung cancer patients' progression-free survival (PFS) to immunotherapy. METHODS: This single-center retrospective study developed and cross-validated a radiomic model in 185 patients and tested it in 48 patients. The binary endpoint is the durable clinical benefit (DCB, PFS ≥ 6 months) and non-DCB (NDCB, PFS < 6 months). Radiomic features were extracted from multiple intrapulmonary lesions and weighted by an attention-based multiple-instance learning model. Aggregated features were then selected through L2-regularized ridge regression. Five machine-learning classifiers were conducted to build predictive models using radiomic and clinical features alone and then together. Lastly, the predictive value of the model with the best performance was validated by Kaplan-Meier survival analysis. RESULTS: The predictive models based on the weighted radiomic approach showed superior performance across all classifiers (AUCs: 0.75-0.82) compared with the largest lesion approach (AUCs: 0.70-0.78) and the average sum approach (AUCs: 0.64-0.80). Among them, the logistic regression model yielded the most balanced performance (AUC = 0.87 [95%CI 0.84-0.89], 0.75 [0.68-0.82], 0.80 [0.68-0.92] in the training, validation, and test cohort respectively). The addition of five clinical characteristics significantly enhanced the performance of radiomic-only model (train: AUC 0.91 [0.89-0.93], p = .042; validation: AUC 0.86 [0.80-0.91], p = .011; test: AUC 0.86 [0.76-0.96], p = .026). Kaplan-Meier analysis of the radiomic-based predictive models showed a clear stratification between classifier-predicted DCB versus NDCB for PFS (HR = 2.40-2.95, p < 0.05). CONCLUSIONS: The adoption of weighted radiomic features from multiple intrapulmonary lesions has the potential to predict long-term PFS benefits for patients who are candidates for PD-1/PD-L1 immunotherapies. KEY POINTS: • Weighted radiomic-based model derived from multiple intrapulmonary lesions on pre-treatment CT images has the potential to predict durable clinical benefits of immunotherapy in lung cancer. • Early line immunotherapy is associated with longer progression-free survival in advanced lung cancer.

A phase III randomized, double-blind, placebo-controlled trial of the denosumab biosimilar QL1206 in postmenopausal Chinese women with osteoporosis and high fracture risk.

The current study evaluated the efficacy and safety of a denosumab biosimilar, QL1206 (60 mg), compared to placebo in postmenopausal Chinese women with osteoporosis and high fracture risk. At 31 study centers in China, a total of 455 postmenopausal women with osteoporosis and high fracture risk were randomly assigned to receive QL1206 (60 mg subcutaneously every 6 months) or placebo. From baseline to the 12-month follow-up, the participants who received QL1206 showed significantly increased bone mineral density (BMD) values (mean difference and 95% CI) in the lumbar spine: 4.780% (3.880%, 5.681%), total hip :3.930% (3.136%, 4.725%), femoral neck 2.733% (1.877%, 3.589%) and trochanter: 4.058% (2.791%, 5.325%) compared with the participants who received the placebo. In addition, QL1206 injection significantly decreased the serum levels of C-terminal crosslinked telopeptides of type 1 collagen (CTX): -77.352% (-87.080%, -66.844%), and N-terminal procollagen of type l collagen (P1NP): -50.867% (-57.184%, -45.217%) compared with the placebo over the period from baseline to 12 months. No new or unexpected adverse events were observed. We concluded that compared with placebo, QL1206 effectively increased the BMD of the lumbar spine, total hip, femoral neck and trochanter in postmenopausal Chinese women with osteoporosis and rapidly decreased bone turnover markers. This study demonstrated that QL1206 has beneficial effects on postmenopausal Chinese women with osteoporosis and high fracture risk.

TLR4 Enhances Cerebral Ischemia/Reperfusion Injury via Regulating NLRP3 Inflammasome and Autophagy.

Ischemic stroke is a kind of central nervous disease characterized by high morbidity, high mortality, and high disability. Inflammation and autophagy play important roles in cerebral ischemia/reperfusion (CI/R) injury. The present study characterizes the effects of TLR4 activation on inflammation and autophagy in CI/R injury. An in vivo CI/R rat injury model and an in vitro hypoxia/reoxygenation (H/R) SH-SY5Y cell model were established. Brain infarction size, neurological function, cell apoptosis, inflammatory mediators' levels, and gene expression were measured. Infarction, neurological dysfunction, and neural cell apoptosis were induced in CI/R rats or in H/R-induced cells. The expression levels of NLRP3, TLR4, LC3, TNF-α, interleukin-1 (IL-1), interleukin-6 (IL-6), and interleukin-18 (IL-18) clearly increased in I/R rats or in H/R-induced cells, while TLR4 knockdown significantly suppressed NLRP3, TLR4, LC3, TNF-α, and interleukin-1/6/18 (IL-1/6/18) in H/R-induced cells, as well as cell apoptosis. These data indicate that TLR4 upregulation induced CI/R injury via stimulating NLRP3 inflammasome and autophagy. Therefore, TLR4, is a potential therapeutic target to improve management of ischemic stroke.

Seeing beyond the tumor: computed tomography image-based radiomic analysis helps identify ovarian clear cell carcinoma subtype in epithelial ovarian cancer.

OBJECTIVE: To develop and validate a model that can preoperatively identify the ovarian clear cell carcinoma (OCCC) subtype in epithelial ovarian cancer (EOC) using CT imaging radiomics and clinical data. MATERIAL AND METHODS: We retrospectively analyzed data from 282 patients with EOC (training set = 225, testing set = 57) who underwent pre-surgery CT examinations. Patients were categorized into OCCC or other EOC subtypes based on postoperative pathology. Seven clinical characteristics (age, cancer antigen [CA]-125, CA-199, endometriosis, venous thromboembolism, hypercalcemia, stage) were collected. Primary tumors were manually delineated on portal venous-phase images, and 1218 radiomic features were extracted. The F-test-based feature selection method and logistic regression algorithm were used to build the radiomic signature, clinical model, and integrated model. To explore the effects of integrated model-assisted diagnosis, five radiologists independently interpreted images in the testing set and reevaluated cases two weeks later with knowledge of the integrated model's output. The diagnostic performances of the predictive models, radiologists, and radiologists aided by the integrated model were evaluated. RESULTS: The integrated model containing the radiomic signature (constructed by four wavelet radiomic features) and three clinical characteristics (CA-125, endometriosis, and hypercalcinemia), showed better diagnostic performance (AUC = 0.863 [0.762-0.964]) than the clinical model (AUC = 0.792 [0.630-0.953], p = 0.295) and the radiomic signature alone (AUC = 0.781 [0.636-0.926], p = 0.185). The diagnostic sensitivities of the radiologists were significantly improved when using the integrated model (p = 0.023-0.041), while the specificities and accuracies were maintained (p = 0.074-1.000). CONCLUSION: Our integrated model shows great potential to facilitate the early identification of the OCCC subtype in EOC, which may enhance subtype-specific therapy and clinical management.

Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range.

The n-octanol-water partition coefficient (logP) is an important physicochemical parameter which describes the behavior of organic compounds. In this work, the apparent n-octanol/water partition coefficients (logD) of basic compounds were determined using ion-suppression reversed-phase liquid chromatography (IS-RPLC) on a silica-based C18 column. The quantitative structure-retention relationship (QSRR) models between logD and logkw (logarithm of retention factor corresponding to 100% aqueous fraction of mobile phase) were established at pH 7.0-10.0. It was found that logD had a poor linear correlation with logkw at pH 7.0 and pH 8.0 when strongly ionized compounds were included in the model compounds. However, the linearity of the QSRR model was significantly improved, especially at pH 7.0, when molecular structure parameters such as electrostatic charge ne and hydrogen bonding parameters A and B were introduced. External validation experiments further confirmed that the multi-parameter models could accurately predict the logD value of basic compounds not only under strong alkaline conditions, but also under weak alkaline and even neutral conditions. The logD values of basic sample compounds were predicted based on the multi-parameter QSRR models. Compared with previous work, the findings of this study extended the pH range for the determination of the logD values of basic compounds, providing an optional mild pH for IS-RPLC experiments.

Parallel multi-swarm cooperative particle swarm optimization for protein-ligand docking and virtual screening.

BACKGROUND: A high-quality docking method tends to yield multifold gains with half pains for the new drug development. Over the past few decades, great efforts have been made for the development of novel docking programs with great efficiency and intriguing accuracy. AutoDock Vina (Vina) is one of these achievements with improved speed and accuracy compared to AutoDock4. Since it was proposed, some of its variants, such as PSOVina and GWOVina, have also been developed. However, for all these docking programs, there is still large room for performance improvement. RESULTS: In this work, we propose a parallel multi-swarm cooperative particle swarm model, in which one master swarm and several slave swarms mutually cooperate and co-evolve. Our experiments show that multi-swarm programs possess better docking robustness than PSOVina. Moreover, the multi-swarm program based on random drift PSO can achieve the best highest accuracy of protein-ligand docking, an outstanding enrichment effect for drug-like activate compounds, and the second best AUC screening accuracy among all the compared docking programs, but with less computation consumption than most of the other docking programs. CONCLUSION: The proposed multi-swarm cooperative model is a novel algorithmic modeling suitable for protein-ligand docking and virtual screening. Owing to the existing coevolution between the master and the slave swarms, this model in parallel generates remarkable docking performance. The source code can be freely downloaded from https://github.com/li-jin-xing/MPSOVina .

Matrix-Directed Mineralization for Bulk Structural Materials.

Mineral-based bulk structural materials (MBSMs) are known for their long history and extensive range of usage. The inherent brittleness of minerals poses a major problem to the performance of MBSMs. To overcome this problem, design principles have been extracted from natural biominerals, in which the extraordinary mechanical performance is achieved via the hierarchical organization of minerals and organics. Nevertheless, precise and efficient fabrication of MBSMs with bioinspired hierarchical structures under mild conditions has long been a big challenge. This Perspective provides a panoramic view of an emerging fabrication strategy, matrix-directed mineralization, which imitates the in vivo growth of some biominerals. The advantages of the strategy are revealed by comparatively analyzing the conventional fabrication techniques of artificial hierarchically structured MBSMs and the biomineral growth processes. By introducing recent advances, we demonstrate that this strategy can be used to fabricate artificial MBSMs with hierarchical structures. Particular attention is paid to the mass transport and the precursors that are involved in the mineralization process. We hope this Perspective can provide some inspiring viewpoints on the importance of biomimetic mineralization in material fabrication and thereby spur the biomimetic fabrication of high-performance MBSMs.

The spatial distribution of immune cell subpopulations in hepatocellular carcinoma.

Infiltrating immune cells in the tumor microenvironment (TME) influence tumor progression and patient prognosis, making them attractive therapeutic targets for immunotherapy research. A deeper understanding of immune cell distributions in the TME in hepatocellular carcinoma (HCC) is needed to identify interactions among different immune cell types that might impact the effectiveness of potential immunotherapies. We performed multiplex immunohistochemistry using a tissue microarray of samples from 302 patients with HCC to elucidate the spatial distributions of immune cell subpopulations (CD3+ , CD4+ , CD8+ , CD66b+ , and CD68+ ) in HCC and normal liver tissues. We analyzed the associations between different immune subpopulations using Pearson's correlation. G(r) functions, K(r) functions and Euclidean distance were applied to characterize the bivariate distribution patterns among the immune cell types. Cox regression and Kaplan-Meier analysis were used to evaluate the associations between tumor infiltration by different immune cells and patient outcomes after curative surgery. We also analyzed the relationship between the spatial distribution of different immune cell subpopulations with HCC patient prognosis. We found that the immune cell spatial distribution in the HCC TME is heterogeneous. Our study provides a theoretical basis for HCC immunotherapy.

Heterostructured α-Fe2 O3 @ZnO@ZIF-8 Core-Shell Nanowires for a Highly Selective MEMS-Based ppb-Level H2 S Gas Sensor System.

Highly selective and sensitive H2 S sensors are in high demand in various fields closely related to human life. However, metal oxide semiconductors (MOSs) suffer from poor selectivity and single MOS@metal organic framework (MOF) core-shell nanocomposites are greatly limited due to the intrinsic low sensitivity of MOF shells. To simultaneously improve both selectivity and sensitivity, heterostructured α-Fe2 O3 @ZnO@ZIF-8 core-shell nanowires (NWs) are meticulously synthesized with the assistance of atomic layer deposition. The ZIF-8 shell with regular pores and special surface functional groups is attractive for excellent selectivity and the heterostructured α-Fe2 O3 @ZnO core with an additional electron depletion layer is promising with enhanced sensitivity compared to a single MOS core. As a result, the heterostructured α-Fe2 O3 @ZnO@ZIF-8 core-shell NWs achieve remarkable H2 S sensing performance with a high response (Rair /Rgas  = 32.2 to 10 ppm H2 S), superior selectivity, fast response/recovery speed (18.0/31.8 s), excellent long-term stability (at least over 3 months), and relatively low limit of detection (down to 200 ppb) at low operating temperature of 200 °C, far beyond α-Fe2 O3 @ZIF-8 or α-Fe2 O3 @ZnO core-shell NWs. Furthermore, a micro-electromechanical system-based H2 S gas sensor system with low power consumption is developed, holding great application potential in smart cities.