Optimal Candidates Research Articles

Stock Portfolio Optimization Using Mean-Variance and Mean Absolute Deviation Model Based On K-Medoids Clustering by Dynamic Time Warping

The tendency of investors to choose investments with maximum return and minimal risk causes the need for diversification in a portfolio to form an optimal portfolio. A lot of research on stock portfolio optimization has been conducted extensively, but not many have tried to apply machine learning concepts such as clustering analysis to accelerate the establishment of a model that can have a positive effect on the time and cost efficiency of portfolio management. However, clustering is only limited to determining the optimal stock candidate, so it is necessary to add another optimization model to calculate the portfolio weight. Based on these problems, this study carried out portfolio optimization using Mean-Variance (MV) and Mean Absolute Deviation (MAD) model based on K-Medoids Clustering by Dynamic Time Warping approach using Monte Carlo-Expected Tail Loss for risk analysis. Based on the analysis results, the MAD portfolio is more optimal than the MV portfolio by the MAD portfolio consists of five stocks, namely BMRI shares with a weight of 0.06243, UNTR shares of 0.08658, BBRI shares of 0.10285, BBCA of 0.53623, and KLBF shares of 0.21191 are the best optimal portfolios. The optimal portfolio of the MAD model has a rate of return of 87.836% in May 2017 - December 2022 with a portfolio performance of 0.03704, while the resulting risk level based on Carlo-Expected Tail Loss is 2.2416%.

Bioinformatics Analysis of Hub Genes Involved in Smoke-Induced Hemifacial Microsomia Pathogenesis.

Tobacco smoke is a recognized teratogen, which increases the risk for hemifacial microsomia (HFM) of the fetus during maternal pregnancy. The present study aimed to explore potential mechanisms and verify hub genes of HFM associated with smoke and tobacco smoke pollution (TSP) via bioinformatics methods. Hemifacial microsomia and smoke and TSP pathogenic genes were obtained. A protein-protein interactional (PPI) network was constructed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and molecular complex detection were performed by Metascape. Finally, we used the cytoHubba plug-in to screen the hub genes. A total of 43 HFM genes and 50 optimal smoke candidate genes were selected. Functional enrichment analysis largely focused on tissue morphogenesis and development. Two modules were identified from the PPI network, and 10 hub genes were screened out. The genes most relevant to smoke-induced HFM pathogenesis included TP53 , ESR1 , ESR2 , and HNRNPL. This study identified some significant hub genes, pathways, and modules of HFM related to smoke by bioinformatics analyses. Our results suggest that the TP53 , ESR1 , ESR2 , and HNRNPL gene subfamilies may have played a major role in HFM induced by smoke and TSP.

High proinsulin:C-peptide ratio identifies individuals with stage 2 type 1 diabetes at high risk for progression to clinical diagnosis and responses to teplizumab treatment.

Tractable precision biomarkers to identify immunotherapy responders are lacking in type 1 diabetes. We hypothesised that proinsulin:C-peptide (PI:C) ratios, a readout of beta cell stress, could provide insight into type 1 diabetes progression and responses to immunotherapy. In this post hoc analysis, proinsulin and C-peptide levels were determined in baseline serum samples from 63 participants with stage 2 type 1 diabetes in the longitudinal TrialNet Teplizumab Prevention Study (n=41 in the teplizumab arm; n=22 in the placebo arm). In addition, previously tested demographic, C-peptide, glucose and proinsulin data were used for the new data analyses. The ratio of intact (unprocessed) proinsulin to C-peptide was analysed and relationships with progression to stage 3 diabetes were investigated. Elevated baseline PI:C was strongly associated with more rapid progression of diabetes in both the placebo and teplizumab treatment groups, but teplizumab abrogated the impact of high pre-treatment PI:C on type 1 diabetes progression. Differential responses of drug treatment in those with high vs low PI:C ratios were independent of treatment effects of teplizumab on the PI:C ratio or on relevant immune cells. High pre-treatment PI:C identified individuals with stage 2 type 1 diabetes who were exhibiting rapid progression to stage 3 disease and who displayed benefit from teplizumab treatment. These data suggest that readouts of active disease, such as PI:C ratio, could serve to identify optimal candidates or timing for type 1 diabetes disease-modifying therapies.

Optimal control of mineral processing plants using constrained model predictive static programming

The model predictive static programming (MPSP) technique, which is extended recently to incorporate applicable state and control constraints, operates on the philosophy of nonlinear model predictive control (NMPC). However, it reduces the problem into a lower-dimensional problem of control variables alone, thereby enhancing computational efficiency significantly. Because of this, problems with larger dimensions and/or increased complexity can be solved using MPSP without changing the computational infrastructure. In this paper, the MPSP technique with applicable constraints is applied to two challenging control problems in the mineral processing industry: (i) a single-stage grinding mill circuit model, and (ii) a four-cell flotation circuit model. The results are compared with a conventional nonlinear MPC approach. Comparison studies show that constrained MPSP executes much faster than constrained MPC with similar/improved performance. Therefore, it can be considered a potential optimal control candidate for mineral processing plants.

Locoregional radiotherapy improves survival outcomes in de novo metastatic nasopharyngeal carcinoma treated with chemoimmunotherapy

We aimed to investigate the efficacy of locoregional radiotherapy (LRRT) in patients with de novo metastatic nasopharyngeal carcinoma (dmNPC) receiving chemotherapy combined with anti-programmed cell death receptor-1 monoclonal antibodies (anti-PD-1 mAbs) as first-line treatment and identify optimal candidates for LRRT. We enrolled patients with dmNPC receiving platinum-based palliative chemotherapy and anti-PD-1 mAbs followed or not followed by LRRT from four centers. The endpoints were progression-free survival (PFS), objective response rate (ORR), and overall survival (OS). We used the inverse probability of treatment weighting (IPTW) to balance the baseline characteristics of the LRRT and non-LRRT groups to minimize selection bias before comparative analyses. Multivariate analyses were carried out using the Cox proportional hazards model. We included 163 patients with dmNPC (median follow-up: 22 months). The median PFS was 20 months, and the ORR was 92.0%; the median OS was not achieved. After IPTW adjustments, patients who received LRRT had a significant survival benefit over those not receiving LRRT (median PFS: 28 versus 15 months, P< 0.001). The Epstein-Barr virus DNA (EBV DNA) level after four to six cycles of anti-PD-1 mAbs [weighted hazard ratio (HR): 2.19, 95% confidence interval (CI) 1.22-3.92, P= 0.008] and LRRT (weighted HR: 0.58, 95% CI 0.34-0.99, P= 0.04) were independent prognostic factors. Patients with undetectable EBV DNA levels after four to six cycles of anti-PD-1 mAbs (early EBV DNA clearance) benefitted from LRRT (HR: 0.41, 95% CI 0.22-0.79, P= 0.008), whereas those with detectable levels did not (HR: 1.30, 95% CI 0.59-2.87, P= 0.51). Palliative chemotherapy combined with anti-PD-1 mAbs followed by LRRT was associated with improved PFS in patients with dmNPC, especially for patients with early EBV DNA clearance.

HIPEC in Ovarian Cancer: When and to Whom?

To evaluate the optimal candidates for hyperthermic intraperitoneal chemotherapy (HIPEC) and cytoreductive surgery (CRS) in ovarian cancer. Descriptive study. Place and Duration of the Study: Health Sciences University, Dr. Abdurrahman YurtasianAnkara Oncology Training and Research Hospital, Ankara, Turkey, between 2013 and 2021. Ovarian cancer patients who underwent HIPEC and CRS for peritoneal involvement were included in this study. Thermosolutions were prepared as a closed system by using HT 2000 hyperthermic perfusion device. Then, cisplatin was applied at 100 mg/m2 at 42-42.5 °C for 60 minutes after CRS. A total of 47 patients were enrolled. The median age was 54 years (27-80) at the time of diagnosis. Forty (85.1%) patients had high grade serous carcinoma and 22 (46.7%) patients had clinical stage 3C disease. The median peritoneal cancer index (PCI) was 13 (3-24) in the whole population. HIPEC was applied as first-line treatment in 25 (51%) patients. Eleven (23.4%) patients had HIPEC in the post-neoadjuvant interval whereas 10 (21.3%) patients had it in platinum sensitive relapse. Median progression free survival (PFS) was 31(95% CI:11-50), 33 (95% CI:1-67), and 18 (95% CI:8-27) months in the primary, post-neoadjuvant interval, and platinum-sensitive relapse HIPEC groups, respectively. The patients with lower PCI (PCI<13) had significantly better OS than others with higher PCI (PCI>13, 145 months versus 42 months, p=0.034). HIPEC with CRS should be considered in selected serous carcinoma patients with peritoneal involvement, especially for the patients with primary ovarian cancer with lower PCI (PCI<13). Ovarian cancer, HIPEC, Peritoneal cancer index.

Construction of an efferocytosis-related long non-coding ribonucleic acid scoring system to predict clinical outcome and immunotherapy response in pancreatic adenocarcinoma

BackgroundEfferocytosis suppresses antitumour immune responses by inducing the release and secretion of cytokines. Long non-coding ribonucleic acids (lncRNAs) have various functions in different forms of programmed cell death and in immune regulation. This study aims to explore the potential role of efferocytosis-related lncRNAs as biomarkers in pancreatic adenocarcinoma (PAAD). MethodsTranscriptome profiles, simple nucleotide variations and clinical data of patients with PAAD were extracted from The Cancer Genome Atlas (TCGA) database. Co-expression algorithms identified efferocytosis-related lncRNAs. The efferocytosis-related lncRNA scoring system (ERLncSys) was established using Cox regression and the Least Absolute Shrinkage and Selection Operator algorithm. Additionally, Kaplan-Meier (K-M) curves, Cox regression, receiver operating characteristic (ROC) curves and clinical parameter stratification analyses were used to evaluate ERlncSys. Moreover, ERlncSys was explored through Gene Set Variation Analysis, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Furthermore, the TIMER platform, ESTIMATE algorithm, single sample Gene Set Enrichment Analysis and immune checkpoint analysis were utilised to explore the predictive power of ERlncSys for the tumour immune microenvironment (TIME). Finally, a consensus clustering algorithm identified distinct molecular profiles among patients with PAAD, aiding in the identification of potential beneficiaries for immunotherapy. ResultsK-M, Cox regression and ROC analyses confirmed the robust prognostic efficacy of ERlncSys. Clinical stratification analysis indicated the broad applicability of ERlncSys in PAAD. Additionally, mmunological analyses indicated that ERlncSys can determine immune cell infiltration status in the TIME. Furthermore, consensus clustering analysis based on ERlncSys divided the TCGA-PAAD cohort into two clusters. Cluster 1 exhibited characteristics consistent with an immune ‘hot tumour’ compared to cluster 2, suggesting cluster 1 is a more suitable population for immune checkpoint inhibitor therapy. ConclusionThe established ErlncSys aids in predicting the prognosis and understanding the TIME landscape of patients with PAAD. In turn, it facilitates the identification of optimal candidates for immunotherapy. This study introduces novel insights into the potential value of efferocytosis-related lncRNAs as biomarkers in PAAD.

The multilevel coordinated optimal control method of a photovoltaic distribution network based on an improved FPA algorithm

The control method of the photovoltaic distribution network has problems of low control accuracy and high line loss of the photovoltaic distribution network. Therefore, this paper proposes a multilevel coordinated optimization control method of a photovoltaic distribution network based on an improved FPA algorithm. First, we analyze the FCM algorithm, use the Euclidean distance to calculate the number of clusters, analyze the basic principle of the flower pollination algorithm, build the coordinated optimization control model of the photovoltaic distribution network, calculate the power flow result of the photovoltaic distribution network by improving the FPA algorithm, determine the global pollination behavior according to the flower pollination algorithm, and use the greedy strategy to obtain the optimal candidate solution. At this time, the obtained solution is the multi-level coordinated optimization control result of the photovoltaic distribution network. The experimental results show that this method can effectively improve the multi-level coordination and optimization control effect of the photovoltaic distribution network and reduce the line loss of the photovoltaic distribution network.

UV Signatures of Magnetar Formation and Their Crucial Role for GW Detection

The emission from shock breakouts (SBOs) represents the earliest electromagnetic (EM) signal emitted by cataclysmic events involving the formation or the merger of neutron stars (NSs). As such, SBOs carry unique information on the structure of their progenitors and on the explosion energy. The characteristic SBO emission is expected in the UV range, and its detection is one of the key targets of the ULTRASAT satellite. Among SBO sources, we focus on a specific class involving the formation of fast-spinning magnetars in the core-collapse of massive stars. Fast-spinning magnetars are expected to produce a specific signature in the early UV supernova light curve, powered by the extra spin energy quickly released by the NS. Moreover, they are considered as optimal candidates for the emission of long-transient gravitational wave (GW) signals, the detection of which requires early EM triggers to boost the sensitivity of dedicated GW search pipelines. We calculate early supernova UV light curves in the presence of a magnetar central engine, as a function of the explosion energy, ejecta mass, and magnetar parameters. We then estimate the ULTRASAT detection horizon (z < 0.15) as a function of the same physical parameters, and the overall expected detection rate, finding that magnetar-powered SBOs may represent up to 1/5 of the total events detected by ULTRASAT. Moreover, at the expected sensitivity of the LIGO/Virgo/Kagra O5 science run, one such event occurring within 5 Mpc will provide an ideal trigger for a GW long-transient search. Future GW detectors like the Einstein Telescope will push the horizon for joint EM-GW detections to 35–40 Mpc.

Optimal candidates for cervical conization before primary radical hysterectomy in early cervical cancer: A Korean multi-center study (1153)

Optimal candidates for cervical conization before primary radical hysterectomy in early cervical cancer: A Korean multi-center study (1153)

A rapid and scalable fabrication of flexible P/C-CNTs anodes for sodium-ion battery

Flexible sodium-ion batteries (SIBs) are a prior energy supply for the future wearable electronic devices. And red phosphorus (P) with high theoretical capacity (2596 mAh/g) is regarded as an optimal candidate for SIB anode. However, the huge volume expansion of red P during the sodiation/desodiation process deteriorates the structural integrity of electrodes, resulting in the rapid capacity fading, which hinders the successful deployment of red P in the flexible SIB anodes. Herein, we propose a rapid and scalable method to fabricate the flexible P-based electrodes, which is similar with the common blade-coating method. The three-dimensional carbon nanotubes (CNTs) matrix from monodispersed CNT solution with robust mechanical strength ensures the structural integrity of the flexible electrode during the long cyclic process. As a result, the flexible P/C-CNTs electrode using as SIB anode delivers a reversible capacity (calculated based on the whole mass of the electrodes, 35 wt% P in electrode) of 442 mA h g−1 at 0.5 A g−1 after 100 cycles, together with 83 % capacity retention. And this work could propel the practical application process of flexible SIB.

Multi-objective design optimization of bioresorbable braided stents

Background and objectivesBioresorbable braided stents, typically made of bioresorbable polymers such as poly-l-lactide (PLLA), have great potential in the treatment of critical limb ischemia, particularly in cases of long-segment occlusions and lesions with high angulation. However, the successful adoption of these devices is limited by their low radial stiffness and reduced elastic modulus of bioresorbable polymers. This study proposes a computational optimization procedure to enhance the mechanical performance of bioresorbable braided stents and consequently improve the treatment of critical limb ischemia. MethodsFinite element analyses were performed to replicate the radial crimping test and investigate the implantation procedure of PLLA braided stents. The stent geometry was characterized by four design parameters: number of wires, wire diameter, initial stent diameter, and braiding angle. Manufacturing constraints were considered to establish the design space. The mechanical performance of the stent was evaluated by defining the radial force, foreshortening, and peak maximum principal stress of the stent as objectives and constraint functions in the optimization problem. An approximate relationship between the objectives, constraint, and the design parameters was defined using design of experiment coupled with surrogate modelling. Surrogate models were then interrogated within the design space, and a multi-objective design optimization was conducted. ResultsThe simulation of radial crimping was successfully validated against experimental data. The radial force was found to be primarily influenced by the number of wires, wire diameter, and braiding angle, with the wire diameter having the most significant impact. Foreshortening was predominantly affected by the braiding angle. The peak maximum principal stress exhibited contrasting behaviour compared to the radial force for all parameters, with the exception of the number of wires. Among the Pareto-optimal design candidates, feasible peak maximum principal stress values were observed, with the braiding angle identified as the differentiating factor among these candidates. ConclusionsThe exploration of the design space enabled both the understanding of the impact of design parameters on the mechanical performance of bioresorbable braided stents and the successful identification of optimal design candidates. The optimization framework contributes to the advancement of innovative bioresorbable braided stents for the effective treatment of critical limb ischemia.

Polymer Chainmail: Steric Hindrance and Charge Compensation of Anion-Doped PEDOT to Boost Stress Deformation of Compressible Supercapacitor.

Conducting polymers with high theoretical capacitance and deformability are among the optimal candidates for compressible supercapacitor electrode materials. However, achieving both mechanical and electrochemical stabilities in a single electrode remains a great challenge. To address this issue, the "Polymer Chainmail" is proposed with reversible deformation capability and enhances stability because of the steric hindrance and charge compensation effect of doped anions. As a proof of concept, four common anions are selected as dopants for Poly(3,4-ethylenedioxythiophene) (PEDOT), and their effects on the adsorption and diffusion of H+ on PEDOT are verified using density functional theory calculations. Owing to the film formation effect, the PF-6 doped PEDOT/Nitrogen-doped carbon foam exhibits good mechanical properties. Furthermore, the composite demonstrates excellent rate performance and stability due to suitable anion doping. This finding provides new insights into the preparation of electrochemically stable conductive polymer-based compressible electrode materials.

Polymer Chainmail: Steric Hindrance and Charge Compensation of Anion‐Doped PEDOT to Boost Stress Deformation of Compressible Supercapacitor

AbstractConducting polymers with high theoretical capacitance and deformability are among the optimal candidates for compressible supercapacitor electrode materials. However, achieving both mechanical and electrochemical stabilities in a single electrode remains a great challenge. To address this issue, the “Polymer Chainmail” is proposed with reversible deformation capability and enhances stability because of the steric hindrance and charge compensation effect of doped anions. As a proof of concept, four common anions are selected as dopants for Poly(3,4‐ethylenedioxythiophene) (PEDOT), and their effects on the adsorption and diffusion of H+ on PEDOT are verified using density functional theory calculations. Owing to the film formation effect, the doped PEDOT/nitrogen‐doped carbon foam exhibits good mechanical properties. Furthermore, the composite demonstrates excellent rate performance and stability due to suitable anion doping. This finding provides new insights into the preparation of electrochemically stable conductive polymer‐based compressible electrode materials.

A stochastic approach to detect fragmentation epoch from a single fragment orbit determination

In the last decades, the growing in-orbit population of resident space objects has become one of the main concerns for space agencies and institutions worldwide. In this context, fragmentations further contribute to increase the number of space debris and, operationally, it is fundamental to identify the event epoch as soon as possible, even when just a single fragment orbital state, resulting from an Initial Orbit Determination (IOD) process, is available.This work illustrates the Fragmentation Epoch Detector (FRED) algorithm, which deals with the problem through a stochastic approach, starting from a single fragment IOD result (expressed through mean state and covariance) and parent ephemeris (assumed as deterministic). The process populates the fragment ephemeris with a multivariate normal distribution and, for each couple sample-parent, the epochs of parent transit through the Minimum Orbital Intersection Distance (MOID) are first computed on a time window and then clustered in time. For each cluster, both the three-dimensional MOID and the three-dimensional relative distance distributions are derived, and their similarity is statistically assessed. Given that, at the actual fragmentation epoch, MOID and relative distance were equal, the cluster featuring the best matching between the two distributions is considered as the optimal candidate, and the related fragmentation epoch is returned from the time of parent transit through the MOID, in terms of mean and standard deviation.FRED algorithm performance is assessed through a numerical analysis. The algorithm robustness decreases when parent and fragment orbits share a similar geometry, and results get deteriorated if the perturbations and, moreover, the IOD errors are included in the process, but the correct fragmentation epoch is always present among candidates. Overall, FRED algorithm turns out to be a valid choice in operational scenarios, and a sensitivity analysis tests the algorithm out of the nominal conditions.

Enhancing Ion Signals and Improving Matrix Selection in Time-of-Flight Secondary Ion Mass Spectrometry with Microvolume Expansion Using Large Argon Clusters.

The molecular environment has an important impact on the ionization mechanism in time-of-flight secondary ion mass spectrometry (ToF-SIMS). In complex samples, desorption/ionization, and thus the detection of a molecular signal, can be hampered by molecular entanglement, ionization-suppressive neighbors, or even an unfavorable sample substrate. Here, a method called microvolume expansion is developed to overcome these negative effects. Large argon clusters are able to transfer biomolecules from a target to a collector in vacuum. In this study, argon gas cluster ion beams (Arn+-GCIB with n centered around 3000 or 5000) are used to expand a microvolume from the sample to a collector, which is a material ideally enhancing the ionization yield. The collector is then analyzed using a liquid metal ion gun. The signal amplification factor corresponding to the expansion of phosphatidylcholine (PC) lipid on collectors partially covered with acidic matrices was evaluated as an initial proof of concept. In one experiment, the PC expansion on a pattern of four drop-casted matrix-assisted laser desorption/ionization matrices led to the selection of α-cyano-4-hydroxycinnamic (CHCA) as the optimal candidate for cationic PC detection. The ion signal is increased by at least three orders of magnitude when PC was expanded using 10 keV Ar3000+ and Ar5000+ on a sublimated layer of CHCA. Finally, the expansion of the gray matter of a mouse on different materials (Si, Au-coated Si, CHCA, and polyethylene) was achieved with varying degrees of success, demonstrating the potential of the method to further analyze complex and fragile biological assemblies.

In‐Plane Nanowire Growth of Topological Crystalline Insulator Pb1 − xSnxTe

AbstractPredicted topological crystalline insulators such as Pb1 − xSnxTe are an interesting candidate for applications in quantum technology, as they can host spin‐polarized surface states. Moreover, in the nanowire geometry, a quasi‐1D system can be realized with potential applications exploiting Majorana fermions. Herein, the selective area growth of Pb1 − xSnxTe islands and nanowires over the full range of x is demonstrated, and their in‐depth growth dynamics and faceting are analyzed. By transmission electron microscopy, the single‐crystalline and defect‐free nature of the grown material and the homogeneous, controllable Pb/Sn ratio in the nanowires is confirmed. With support of phase‐field growth simulations, it is shown that the crystal faceting mainly follows the driving force of surface energy minimization, favoring the lowest energy {200} surfaces. A kinetic enhancement of adatom incorporation on {110} facets is recognized to limit their extension with respect to {200} and {111} facets. After inspecting all possible in‐plane orientations, we identify the 〈110〉 directions as the optimal candidate for the growth of high‐quality and perfectly straight Pb1 − xSnxTe nanowires, enabling the design of complex networks due to their threefold symmetry. This work opens the way to systematic transport investigation of the carrier density in Pb1 − xSnxTe nanowires and can facilitate further optimization of the Pb1 − xSnxTe system.

Optimization of a solar energy system integrating cooling, hot water, and power units in Australian cities: A climate-based analysis and cost-efficiency investigation

This study presents an investigation into the analysis and optimization of a solar energy system that integrates cooling, hot water, and power units. The system employs PV/T (photovoltaic/thermal) modules to generate electricity and provide thermal energy simultaneously. Using the response surface methodology (RSM), the system is subjected to multi-objective optimization to enhance its performance and decrease costs. The first optimization scenario focuses on maximizing net output power and minimizing the cost of the thermoelectric generator (TEG). Six choice factors are identified to improve the system's cost and exergy efficiency. Results indicate an optimal exergy efficiency of 19.704% and a favorable cost rate of 1.774 $/h for the proposed system. Economic analysis reveals that the most expensive subsystems are the proton exchange membrane (PEM) electrolyzer and organic Rankine cycle (ORC). Exergy analysis highlights the PV panels, absorption chiller, PEM electrolyzer, and ORC evaporator as components with significant exergy devastation. To assess the system's viability in Australian cities, it is analyzed across six climate zones. The city of Maitland emerges as the most optimal candidate for system implementation. The study demonstrates that the proposed approach performs best in cities with similar climates to Maitland. Considering the impact of environmental factors such as temperature and sunlight radiation is crucial for determining system costs, net output power, and exergy efficiency on a global scale. Overall, this research contributes to the understanding of solar energy systems by integrating cooling, hot water, and power units. It emphasizes the importance of climate-based analysis and optimization for efficient system performance. The findings provide valuable insights for the design and implementation of solar energy systems, facilitating their widespread adoption and contribution to sustainable energy solutions.

Development and validation of a prognostic score to identify the optimal candidate for preemptive TIPS in patients with cirrhosis and acute variceal bleeding.

Baveno VII workshop recommends the use of preemptive TIPS (p-TIPS) in patients with cirrhosis and acute variceal bleeding (AVB) at high- risk of treatment failure. However, the criteria defining "high-risk" have low clinical accessibility or include subjective variables. We aimed to develop and externally validate a model for better identification of p-TIPS candidates. The derivation cohort included 1554 patients with cirrhosis and AVB who were treated with endoscopy plus drug (n = 1264) or p-TIPS (n = 290) from 12 hospitals in China between 2010 and 2017. We first used competing risk regression to develop a score for predicting 6-week and 1-year mortality in patients treated with endoscopy plus drugs, which included age, albumin, bilirubin, international normalized ratio, white blood cell, creatinine, and sodium. The score was internally validated with the bootstrap method, which showed good discrimination (6wk/1y concordance-index: 0.766/0.740) and calibration, and outperformed other currently available models. In the second stage, the developed score was combined with treatment and their interaction term to predicate the treatment effect of p-TIPS (mortality risk difference between treatment groups) in the whole derivation cohort. The estimated treatment effect of p-TIPS varied substantially among patients. The prediction model had good discriminative ability (6wk/1y c -for-benefit: 0.696/0.665) and was well calibrated. These results were confirmed in the validation dataset of 445 patients with cirrhosis with AVB from 6 hospitals in China between 2017 and 2019 (6-wk/1-y c-for-benefit: 0.675/0.672). We developed and validated a clinical prediction model that can help to identify individuals who will benefit from p-TIPS, which may guide clinical decision-making.

Discovery of potent pyrrolo-pyrimidine and purine HDAC inhibitors for the treatment of advanced prostate cancer

The development of drugs for the treatment of advanced prostate cancer (PCA) remains a challenging task. In this study we have designed, synthesized and tested twenty-nine novel HDAC inhibitors based on three different zinc binding groups (trifluoromethyloxadiazole, hydroxamic acid, and 2-mercaptoacetamide). These warheads were conveniently tethered to variously substituted phenyl linkers and decorated with differently substituted pyrrolo-pyrimidine and purine cap groups. Remarkably, most of the compounds showed nanomolar inhibitory activity against HDAC6. To provide structural insights into the Structure-Activity Relationships (SAR) of the investigated compounds, docking of representative inhibitors and molecular dynamics of HDAC6-inhibitor complexes were performed. Compounds of the trifluoromethyloxadiazole and hydroxamic acid series exhibited promising anti-proliferative activities, HDAC6 targeting in PCA cells, and in vitro tumor selectivity. Representative compounds of the two series were tested for solubility, cell permeability and metabolic stability, demonstrating favorable in vitro drug-like properties. The more interesting compounds were subjected to migration assays, which revealed that compound 13 and, to a lesser extent, compound 15 inhibited the invasive behaviour of androgen-sensitive and –insensitive advanced prostate cancer cells. Compound 13 was profiled against all HDACs and found to inhibit all members of class II HDACs (except for HDAC10) and to be selective with respect to class I and class IV HDACs. Overall, compound 13 combines potent inhibitory activity and class II selectivity with favorable drug-like properties, an excellent anti-proliferative activity and marked anti-migration properties on PCA cells, making it an excellent lead candidate for further optimization.