Structural Features Research Articles

An Expedition on Synthetic Methodology of FDA-approved Anticancer Drugs (2018-2021).

New drugs being established in the market every year produce specified structures for selective biological targeting. With medicinal insights into molecular recognition, these begot molecules open new rooms for designing potential new drug molecules. In this review, we report the compilation and analysis of a total of 56 drugs including 33 organic small molecules (Mobocertinib, Infigratinib, Sotorasib, Trilaciclib, Umbralisib, Tepotinib, Relugolix, Pralsetinib, Decitabine, Ripretinib, Selpercatinib, Capmatinib, Pemigatinib, Tucatinib, Selumetinib, Tazemetostat, Avapritinib, Zanubrutinib, Entrectinib, Pexidartinib, Darolutamide, Selinexor, Alpelisib, Erdafitinib, Gilteritinib, Larotrectinib, Glasdegib, Lorlatinib, Talazoparib, Dacomitinib, Duvelisib, Ivosidenib, Apalutamide), 6 metal complexes (Edotreotide Gallium Ga-68, fluoroestradiol F-18, Cu 64 dotatate, Gallium 68 PSMA-11, Piflufolastat F-18, 177Lu (lutetium)), 16 macromolecules as monoclonal antibody conjugates (Brentuximabvedotin, Amivantamab-vmjw, Loncastuximabtesirine, Dostarlimab, Margetuximab, Naxitamab, Belantamabmafodotin, Tafasitamab, Inebilizumab, SacituzumabGovitecan, Isatuximab, Trastuzumab, Enfortumabvedotin, Polatuzumab, Cemiplimab, Mogamulizumab) and 1 peptide enzyme (Erwiniachrysanthemi-derived asparaginase) approved by the U.S. FDA between 2018 to 2021. These drugs act as anticancer agents against various cancer types, especially non-small cell lung, lymphoma, breast, prostate, multiple myeloma, neuroendocrine tumor, cervical, bladder, cholangiocarcinoma, myeloid leukemia, gastrointestinal, neuroblastoma, thyroid, epithelioid and cutaneous squamous cell carcinoma. The review comprises the key structural features, approval times, target selectivity, mechanisms of action, therapeutic indication, formulations, and possible synthetic approaches of these approved drugs. These crucial details will benefit the scientific community for futuristic new developments in this arena.

Multi-View Subspace Clustering via Structured Multi-Pathway Network.

Recently, deep multi-view clustering (MVC) has attracted increasing attention in multi-view learning owing to its promising performance. However, most existing deep multi-view methods use single-pathway neural networks to extract features of each view, which cannot explore comprehensive complementary information and multilevel features. To tackle this problem, we propose a deep structured multi-pathway network (SMpNet) for multi-view subspace clustering task in this brief. The proposed SMpNet leverages structured multi-pathway convolutional neural networks to explicitly learn the subspace representations of each view in a layer-wise way. By this means, both low-level and high-level structured features are integrated through a common connection matrix to explore the comprehensive complementary structure among multiple views. Moreover, we impose a low-rank constraint on the connection matrix to decrease the impact of noise and further highlight the consensus information of all the views. Experimental results on five public datasets show the effectiveness of the proposed SMpNet compared with several state-of-the-art deep MVC methods.

One-pot synthesis of cysteine-rich peptide via ‘2,2’-dithiobispyridine’ mediated sulfur exchange reaction

The cyclization of polypeptides confers enhanced stability, specificity, binding affinity, and cell permeability, making it a common feature in the backbone structure of natural products. Disulfide bonds are widely found in active peptides and play a crucial role in maintaining their secondary structure. In this study, we present a sulfur exchange reaction-based method for constructing disulfide bonds using 2,2′-dithiobis(5-nitropyridine) as a mediator. This method exhibits excellent substrate adaptability and compatibility with conventional functional groups. It also demonstrates rapid reaction efficiency, allowing successful disulfide bond formation under various pH conditions. Moreover, the products and additives can be easily separated, showing the potential of this method for screening disulfide bond-rich peptides in future research.

Alkoxycarbonyl Groups in Metalloesters Showing Oxocarbenium‐like Structure and Alkylating Reactivity

AbstractIn contrast to the well‐documented acylating reactivity, the alkylating reactivity of the alkoxycarbonyl group, as signified by its oxocarbenium‐like resonance structure, remains almost unexplored. Herein, the first series of Co/Ni dinuclear metalloesters exhibiting the novel oxocarbenium‐like alkoxycarbonyl groups were synthesized and characterized. In these deformed alkoxycarbonyl groups, the Ccarbonyl−Oalkoxyl bonds were contracted to 1.177(11)~1.191(9) Å with the elongations of the Ccarbonyl=Ocarbonyl bonds to 1.368(13)~1.441(9) Å. Meanwhile, the O−Calkyl bonds were also elongated to 1.522(11) ~1.607(15) Å, and were by far the longest O−Calkyl bonds reported for alkoxycarbonyl groups. As triggered by the long O−Calkyl distances, the alkylating reactivity of the oxocarbenium‐like methoxycarbonyl group towards a series of C/N/O‐nucleophiles via the rare BAL2 mechanism at ambient conditions was examined. Furthermore, the homo‐etherifications of alcohols mediated by the Co/Ni dinuclear metalloesters were investigated. The yields followed the trend ethanol≫n‐propanol≫n‐butanol ≈n‐pentanol, that closely related to the structure features of the alkoxycarbonyl groups in corresponding metalloesters: while the ethoxycarbonyl group showed the reactive oxocarbenium‐like framework, the n‐propoxycarbonyl group displayed the dioxocarbenium‐like skeleton with a shorter O−Calkyl bond; In comparison, the classical frameworks with unactivated alkyl moieties were observed for n‐butoxycarbonyl and n‐pentoxycarbonyl groups.

Alkoxycarbonyl Groups in Metalloesters Showing Oxocarbenium-like Structure and Alkylating Reactivity.

In contrast to the well-documented acylating reactivity, the alkylating reactivity of the alkoxycarbonyl group, as signified by its oxocarbenium-like resonance structure, remains almost unexplored. Herein, the first series of Co/Ni dinuclear metalloesters exhibiting the novel oxocarbenium-like alkoxycarbonyl groups were synthesized and characterized. In these deformed alkoxycarbonyl groups, the Ccarbonyl-Oalkoxyl bonds were contracted to 1.177(11)~1.191(9) Å with the elongations of the Ccarbonyl=Ocarbonyl bonds to 1.368(13)~1.441(9) Å. Meanwhile, the O-Calkyl bonds were also elongated to 1.522(11) ~1.607(15) Å, and were by far the longest O-Calkyl bonds reported for alkoxycarbonyl groups. As triggered by the long O-Calkyl distances, the alkylating reactivity of the oxocarbenium-like methoxycarbonyl group towards a series of C/N/O-nucleophiles via the rare BAL2 mechanism at ambient conditions was examined. Furthermore, the homo-etherifications of alcohols mediated by the Co/Ni dinuclear metalloesters were investigated. The yields followed the trend ethanol≫n-propanol≫n-butanol ≈n-pentanol, that closely related to the structure features of the alkoxycarbonyl groups in corresponding metalloesters: while the ethoxycarbonyl group showed the reactive oxocarbenium-like framework, the n-propoxycarbonyl group displayed the dioxocarbenium-like skeleton with a shorter O-Calkyl bond; In comparison, the classical frameworks with unactivated alkyl moieties were observed for n-butoxycarbonyl and n-pentoxycarbonyl groups.

Gd(HB-DO3A)]: Equilibrium, Dissociation Kinetic and Structural Differences in a Simple Homolog of [Gd(HP-DO3A)] (Prohance®).

[Gd(HP-DO3A)] (gadoteridol) as an active compound of ProHance® is a widely employed contrast agent in clinical MRI scans in the last 30 years. Recent concerns about the long-term retention of gadolinium-based contrast agents (GBCAs) led to a deeper investigation of the structural features underlying the integrity of the paramagnetic metal complex. Several human and nonclinical studies have noted marked differences among the macrocyclic GBCAs, with the least retention of Gd traces and most rapid elimination consistently being reported for [Gd(HP-DO3A)]. It was deemed of interest to assess how minor structural/electronic changes associated to the ligand structure may affect basic properties of the metal complex with several [Gd(HP-DO3A)] analogues synthesized and characterized in the last years. We recently reported that the closest homolog of [Gd(HP-DO3A)], i. e.: [Gd(HB-DO3A)], in which a (±)-2-hydroxy-1-propyl pendant arm is replaced by a (±)-2-hydroxy-1-butyl moiety, showed a significantly different retention behaviour in the model interaction with collagen, despite the apparently very minor structural difference. In this paper we report a comprehensive study of the structural, thermodynamic, kinetic and relaxation properties of [Gd(HB-DO3A)], compared to the parent [Gd(HP-DO3A)] and to other closely related macrocyclic GBCAs to assess whether very minor structural changes can modulate the physico-chemical properties of Gd3+ complexes.

МАТЕМАТИЧНЕ МОДЕЛЮВАННЯ ПЕРЕХІДНИХ ПРОЦЕСІВ В ІЄРАРХІЧНИХ СТРУКТУРАХ ДЕРЖАВНОГО УПРАВЛІННЯ З НЕЛІНІЙНИМИ ХАРАКТЕРИСТИКАМИ

The last decades are characterized by a large number of studies of state and public figures, which can be called an era of deep (fundamental) and rapid changes. Society is experiencing qualitative changes and serious challenges, therefore there is a kind of paradox when the imperatives of a new era force the development of a theoretical basis in the semantic field of common sense, which is associated with permanence and qualitative changes in political, economic and social life [1, 2, 3] . In state administration and local self-government bodies, relations between people, rapid unpredictable changes in the situation in the country and in regions (political, economic, social, etc.) are non-linear management systems. Moreover, any physical system when examined in more detail is always nonlinear. The effectiveness of managing a nonlinear system, taking into account disturbing factors, depends on the accuracy of forecasting the dynamics of changes in individual elements of such a system. This is a multifaceted problem [15]. A characteristic feature of non-linear hierarchical structures (NIS) in the public service (state administration - DU and local self-government - MS) is a continuous and discrete change in the processes of development of events, which distinguishes them from other internal and external influences, such as those that cause the transformation of linear communication into non-linear, which ultimately leads to new changes. This is the first thing. Second, subject-object relationships can have uncoordinated actions caused by real-world circumstances. Such uncoordinated actions can occur even more in transitional processes of society (for example, the speed of their flow) due to the inertia of individual elements or the social system itself as a whole. As a result of these phenomena, the linear relationship between discrete changes is broken and the previous hierarchical structure changes, which leads to non-linear information relationships in the state administration (SU) and local self-government bodies (MS). For example, G. Pocheptsov and other scientists associate this nonlinearity with chaos, the growing complexity of social processes, globalization, with a threat to state security, with the manifestation of unpredictability and instability [1-5]. Strict requirements are imposed on the management process in the new state of DU and MS: - resilience of the management system; - the system should be described as continuous-discrete (its dynamics); - the management process must ensure the necessary accuracy of matching the indicators of the new state of the system with the previous one. A number of problems appear in newly formed non-linear hierarchical structures (NIS) in DU and MS: - lack of a priori information about processes with non-linear connections; - inaccuracy of structural identification; - inaccuracy in the choice of criteria for assessing the situation; - restructuring processes; - wrong choice of states of nature; - incorrect determination of the importance of the selected criteria according to the scale of importance; - incorrectly chosen dependence of alternatives on the criterion; - insufficient degree of awareness of the complexity of the situation. Solving the above problems requires experimental research. If the process of stabilization of the NIS in the DU is considered as an object of regulation, then it is enough to establish the dependence of this stability on the control action and the main disturbance, and all other actions are considered as disturbances on the object of study. Such a description will reflect the main dynamic characteristics of such a process and will be sufficient for the synthesis and development of an optimal regulation system with the aim of achieving stable (stable) processes in such systems (including DU and MS). In the future, we will approach the DU as a non-linear hierarchical system (NHS) and depict the NIS as a multidimensional continuous system, in which the state of nature is the regulated quantity, and the input is the action of managers in the DU and MS (management decisions made by them - PUR) regarding regulation , coordination and perturbations acting on the system.

Phenomenologies of loneliness: alone without you, alone without an us

Loneliness is not simply characterised by a lack of other people in one’s environment or lifeworld, but by a lack of specific forms of relationship, connection or belonging. In this paper I connect the conversation about different types of loneliness with debates happening in the philosophy of intersubjectivity, specifically the phenomenology of intersubjectivity. Philosophers of intersubjectivity tend to characterise experiences of direct encounter as having a second-personal ‘I-thou’ quality. By contrast, experiences of belonging tend to be characterised by first-person plural ‘we’ structures. In this paper I will compare and contrast some of the different phenomenological qualities that come with the absence or poverty of these two types of intersubjective structure respectively. These different types of loneliness are characterised by different phenomenological properties, but also by (the absence of) specific interpersonal and social structures. I argue that the absence of these different interpersonal structures respectively gives rise to loneliness as the experience of being unseen and loneliness as the experience of not-being-at-home. This is significant for loneliness studies, as understanding and combating loneliness is consequently likely to take variegated rather than homogeneous forms. This is particularly significant for a psychosocial approach to loneliness which seeks to understand, hold together and integrate both the structural features of loneliness (in this case the relevant interpersonal and social structures) and the lived experience of individuals and groups (in this case the phenomenology of loneliness).

SAH-NET: Structure-Aware Hierarchical Network for Clustered Microcalcification Classification in Digital Breast Tomosynthesis.

Benign and malignant classification of clustered microcalcifications (MCs) in digital breast tomosynthesis (DBT) is an essential task in computer-aided diagnosis. However, due to the anisotropic resolution of DBT, three-dimensional (3-D) convolutional neural network (CNN)-based methods cannot extract hierarchical features efficiently. Moreover, the sparse distribution of MC points in the cluster makes it difficult for the CNN to extract discriminative structural information for classification. To comprehensively address these challenges, we propose a novel structure-aware hierarchical network (SAH-Net) for benign and malignant classification of clustered MC in a DBT volume. Specifically, the two-dimensional (2-D) group convolution is used to extract intraslice features. The one-to-one correspondence between group convolutions and slices ensures the independence of hierarchical feature extraction. Then, a partial deformable Transformer-based 3-D structural feature learning module is proposed to capture the long-range dependency between MC points in the cluster. We evaluate the proposed method on an in-house dataset with 495 clustered MCs collected from 462 DBT images. Experimental results confirm the validity of our proposed modules. The results also show that the proposed SAH-Net outperforms several other representative methods on this topic, and achieves the best classification result, with an area under the receiver operation curve (AUC) of 86.87%. The implementation of the proposed model is available at https://github.com/sunhaotian130911/SAHNet.

Hard Carbon Derived From Different Precursors for Sodium Storage.

Due to the almost unlimited resource and acceptable performance, Sodium-ion batteries (SIBs) have been regarded as a promising alternative for lithium-ion batteries (LIBs) for grid-scale energy storage. As the key material of SIBs, hard carbon (HC) plays a decisive role in determining the batteries' performance. Nevertheless, the micro-structure of HCs is quite complex and the random organization of turbostratically stacked graphene layers, closed pores, and defects make the structure-performance relationship insufficiently revealed. On the other hand, the impending large-scale deployment of SIBs leads to producing HCs with low-cost and abundant precursors actively pursued. In this work, the recent progress of preparing HCs from different precursors including biomass, polymers, and fossil fuels is summarized with close attention to the influences of precursors on the structural evolution of HCs. After a brief introduction of the structural features of HCs, the recent understanding of the structure-performance relationship of HCs for sodium storage is summarized. Then, the main focus is concentrated on the progress of producing HCs from distinct precursors. After that, the pros and cons of HCs derived from different precursors are comprehensively compared to conclude the selection rules of precursors. Finally, the further directions of HCs are deeply discussed to end this review.

De novo GRIN variants in M3 helix associated with neurological disorders control channel gating of NMDA receptor

N-methyl-d-aspartate receptors (NMDARs) are members of the glutamate receptor family and participate in excitatory postsynaptic transmission throughout the central nervous system. Genetic variants in GRIN genes encoding NMDAR subunits are associated with a spectrum of neurological disorders. The M3 transmembrane helices of the NMDAR couple directly to the agonist-binding domains and form a helical bundle crossing in the closed receptors that occludes the pore. The M3 functions as a transduction element whose conformational change couples ligand binding to opening of an ion conducting pore. In this study, we report the functional consequences of 48 de novo missense variants in GRIN1, GRIN2A, and GRIN2B that alter residues in the M3 transmembrane helix. These de novo variants were identified in children with neurological and neuropsychiatric disorders including epilepsy, developmental delay, intellectual disability, hypotonia and attention deficit hyperactivity disorder. All 48 variants in M3 for which comprehensive testing was completed produce a gain-of-function (28/48) compared to loss-of-function (9/48); 11 variants had an indeterminant phenotype. This supports the idea that a key structural feature of the M3 gate exists to stabilize the closed state so that agonist binding can drive channel opening. Given that most M3 variants enhance channel gating, we assessed the potency of FDA-approved NMDAR channel blockers on these variant receptors. These data provide new insight into the structure–function relationship of the NMDAR gate, and suggest that variants within the M3 transmembrane helix produce a gain-of-function.

Studies on foamed concrete micropores and their effects on stress distribution and heat conduction

Further research on the pore structure of foamed concrete contribute to expand the application of energy-efficient buildings. In this paper, the micropore structure features of foamed concrete were characterized by nuclear magnetic resonance. It is found that the pore size of foamed concrete ranged from 1 nm to 74.84 μm. In order to understand the effect of micropores on the performance of foamed concrete, the models with (Model I) and without micropores (Model II) were established. Besides, the heat conduction and stress distribution of foamed concrete were simulated numerically. Meanwhile, the thermal conductivity and compressive strength were tested as the reference for numerical simulations. The results show that the heat conduction flux and temperature gradient of Model I were increased by 12%–13% and the thermal conductivity was increased by 2.63% compared to Model II. Thermal conductivity of Model I was closer to the experimental results. The stress of Model I was increased by 1.32%–54.66% compared to that of Model II. This indicates that the micropores can significantly increase the stress concentration in the foamed concrete.

Substantial composition and technological treatment of potassium rocks of the Upper Pechora salt basin

The material composition of potassium and potassium-magnesium salts of the Upper Pechora salt-bearing basin was studied, their lithological variability was established over the area of productive strata, depending on the tectonic features of the foundation. The main mining and geological conditions that complicate the possibility of their extraction and the environmental conditions for organizing mining and processing production of mineral salts were established. The basic physical and technological properties of sylvinite and carnallite rocks mined by the mine method were studied for their enrichment by halurgical and flotation methods. The objectives of the work were: determining the material composition, studying textural and structural features and assessing the technological processing of potassium rocks in the Upper Pechora salt-bearing basin. When solving the problems, the following methods were used: a study of the textural and structural features of sylvinites using the petrographic method; the chemical composition of samples and solutions was analyzed by AES spectrometry; the mineral composition of the water-insoluble residue is determined by X-ray quantitative phase analysis.

G-K BertDTA: A graph representation learning and semantic embedding-based framework for drug-target affinity prediction

Developing new drugs is costly, time-consuming, and risky. Drug-target affinity (DTA), indicating the binding capability between drugs and target proteins, is a crucial indicator for drug development. Accurately predicting interaction strength between new drug-target pairs by analyzing previous experiments aids in screening potential drug molecules, repurposing them, and developing safe and effective medicines. Existing computational models for DTA prediction rely on strings or single-graph neural networks, lacking consideration of protein structure and molecular semantic information, leading to limited accuracy. Our experiments demonstrate that string-based methods may overlook protein conformations, causing a high root mean square error (RMSE) of 3.584 in affinity due to a lack of spatial context. Single graph networks also underperform on topology features, with a 6% lower confidence interval (CI) for activity classification. Absent semantic information also limits generalization across diverse compounds, resulting in 18% increment in RMSE and 5% in misclassifications within quantifications study, restricting potential drug discovery. To address these limitations, we propose G-K BertDTA, a novel framework for accurate DTA prediction incorporating protein features, molecular semantic features, and molecular structural information. In this proposed model, we represent drugs as graphs, with a GIN employed to learn the molecular topological information. For the extraction of protein structural features, we utilize a DenseNet architecture. A knowledge-based BERT semantic model is incorporated to obtain rich pre-trained semantic embeddings, thereby enhancing the feature information. We extensively evaluated our proposed approach on the publicly available benchmark datasets (i.e., KIBA and Davis), and experimental results demonstrate the promising performance of our method, which consistently outperforms previous state-of-the-art approaches. Code is available at https://github.com/AmbitYuki/G-K-BertDTA.

Application of co-crystallization method for the production of ammonium perchlorate/ammonium nitrate oxidizer for solid rocket propellants

Efforts in the quest for greener alternatives to ammonium perchlorate (AP) as a solid rocket propellant oxidizer have intensified due to the associated health and environmental concerns. AP exceptional performance in propulsion is accompagnied by its environmental concerns, necessitating the exploration of greener alternatives. Ammonium nitrate (AN) has emerged as a promising substitute, offering cleaner combustion products and cost-effectiveness. AN-based propellants face challenges such as hygroscopicity and structural instability. This study aims to reconcile the latter challenges by employing a co-crystallization process that embodies a synergistic association of AP and AN, culminating in a novel molecule that harmonizes their distinct advantages and mitigates their individual shortcomings. Optimizing the solvent/antisolvent co-crystallization process through a variation of the antisolvent temperature Ta and antisolvent-to-solvent ratio Ra/s allows to assess their impact on the co-crystallization process of AP and AN and to attain the desired and optimal co-crystal formation conditions. Various characterization techniques were applied to gain deep insights into the co-crystal formation mechanism, its thermal behavior, morphological and structural features together with its thermal decomposition kinetics. Maintaining a low Ta and a high Ra/s (Ta = 15 °C, Ra/s = 11) yielded the design of AP/AN that demonstrates typical indications of the cocrystal formation. The AP/AN cocrystal formation elevated the decomposition temperature by about 18 °C compared to the physical mixture. Furthermore, the combination of AP and AN demonstrates a non-negligible decrease in the HTD temperature compared to that of pure AP by about 110 °C. The kinetic study demonstrated a 50 kJ/mol increase in the activation energy of the AP/AN cocrystal compared to that of the physical mixture. The present research addresses the critical gap in the literature by investigating the co-crystallization of AP and AN that not only improves the safety and environmental impact of solid propellants but also enhances their overall performance and stability.

Oxalate-mediated synthesis of hybrid nickel cobalt-based nanostructures for boosting water and urea electrooxidation efficiency

The utilization of urea during electrolysis presents an appealing option for anodic oxidation, offering environmental benefits by converting waste into energy. The present work focuses on synthesizing mixed transition metal oxide (MMO) nanostructures composed of nickel rich nickel cobaltite electrode materials. Interesting, cobalt rich nickel cobaltite have been widely studied; however, the nickel-rich nickel cobaltite remains relatively unexplored. For stabilization of nickel rich nickel cobaltite, we have designed a process for synthesizing three-dimensional (3D) Ni-Co oxalate as a precursor via the coprecipitation method using diammonium oxalate monohydrate as a precipitating agent. The as obtained precursor was further subjected to thermal decomposition which results in the formation of Ni2CoO4. Microstructural analysis of Ni-Co oxalate indicates that oxalate-assisted synthesis leads to anisotropic ultrafine nanoparticle growth, forming hierarchically arranged 3D microflowers. Interestingly, the use of NaOH as a precipitating agent induces a significant change in the morphology of Ni2CoO4, (nanoparticles). Furthermore, the effect of morphology changes over the electrochemical performance was investigated. Ni2CoO4 microflower demonstrates an overpotential of 330 mV@25 mA/cm2 for O2 and −190 mV@10 mA/cm2 for H2 production during water oxidation in 1 M KOH, exhibiting excellent stability for up to 24 h. During urea oxidation, the potential required by Ni2CoO4 microflowers was 1.31 V@10 mA/cm2. Ni2CoO4 nanoparticles' performance is significantly poor during water and urea oxidation compared to the microflower counterpart. Therefore, this work provides detailed insights into designing MMOs with high porosity, increased exposed active sites, and unique structural features that enhance electrocatalytic activity.

Polysubstitution Induced Centrosymmetric-to-Noncentrosymmetric Structural Transformation and Nonlinear-Optical Behavior: The Case of Na0.45Ag0.55Ga3Se5.

Obtaining compounds with large nonlinear-optical (NLO) coefficients and wide band gaps is challenging due to their competitive requirements for chemical bonds. Herein, the first member with mixed cations on the A site in the A-M3-Q5 or A-Ag-M6-Q10 (A = alkali metal; M = Ga, In; Q = S, Se, Te) family, viz. Na0.45Ag0.55Ga3Se5 (NAGSe), was obtained by a solid-state reaction. Its structure features [GaSe4] tetrahedra built three-dimensional {[Ga3Se5]-}∞ network, with Na and Na/Ag cations located at the octahedral cavities. Noncentrosymmetric (R32) NAGSe can also be transformed from centrosymmetric RbGa3S5 (P21/c) via multiple-site cosubstitution. NAGSe exhibits the highest NLO response (1.9 × AGS) in the A-Ag-M-Q family. Crystal structure analysis and theoretical calculations suggest that the NLO response is mainly contributed by the regularly arranged [GaSe4] units. This work enriches the exploration of the undeveloped A-M3-Q5 or A-Ag-M6-Q10 family as potential infrared NLO materials.

Structure and agency in resistance to schooling: Class, race, and the reproduction of unequal outcomes

For low-income and marginalized racialized minority youth, declining prospects of mobility can undermine favorable attitudes toward schooling if adolescents anticipate limited utility in schooling. We find that adolescents' awareness of race and class inequality affects a complex set of attitudes toward schooling, and that these attitudes contribute to outcomes varying by race/ethnicity and class. We capitalize on a unique longitudinal dataset with a random stratified sample of 1428 Black and White high school graduates from a large school system. Using surveys and administrative data, we show how structural factors and student characteristics shape educational attitudes; and then how these attitudes, school structural features, student, family, and neighborhood factors predict educational outcomes. We find the common ground between Willis' resistance theory emphasizing class and Ogbu’s cultural-ecological model focusing on race. Results provide greater conceptual clarity for core constructs associated with both theories of resistance.

Tailoring thin film composite membranes for clean water production: A study on structural variations and predictive insights using machine learning

This study focuses on the fabrication of three thin film composite membranes by interfacial polymerization on polyacrylonitrile support. The objective is to explore the influence of different monomers on structural and functional features of resultant membranes for treating saline water and removing micropollutants. A new linear aliphatic amine 4A–2E was used as an aqueous monomer for the first time. Trimesoyl chloride, isophthaloyl chloride, and terephthaloyl chloride were used as organic phase crosslinkers. The resulting membranes exhibited distinctive structural features such as varied roughness and hydrophilicity, which correlated with their functional performance. The membrane roughness for 4A–2E-TPC@PAN/PET reached the highest value of Ra = 56 nm among the fabricated membranes. Moreover, permeate flux of 32, 56, and 49 L m−2 h−1 at 25 bar was measured for 4A–2E-TPC@PAN/PET, 4A–2E-IPC@PAN/PET, and 4A–2E-TMC@PAN/PET, respectively. Notably, 4A–2E-TPC@PAN/PET membrane exhibited 98% rejection of MgCl2 among the tested divalent salts. Furthermore, the membrane displayed high rejections of micropollutants, with 85% rejection for Amitriptyline. Upon chlorine exposure, the 4A–2E-TPC@PAN/PET membrane proved more resistant than both 4A–2E-IPC@PAN/PET and 4A–2E-TMC@PAN/PET membranes. Machine learning predictive insight was developed using Matérn Gaussian Process Regression model to simulate flux before and after chlorination of membranes. The results in both training and testing proved reliable predictive insight with 99% accuracy in terms of Nash Sutcliffe Efficiency. Hence, current work highlights the use of a linear amine 4A–2E and TPC crosslinker to fabricate a dense polyamide membrane and the application of ML algorithms to desalination data makes it possible to predict the membrane performance.

DRFNet: a deep radiomic fusion network for nAMD/PCV differentiation in OCT images.

Objective.Neovascular age-related macular degeneration (nAMD) and polypoidal choroidal vasculopathy (PCV) present many similar clinical features. However, there are significant differences in the progression of nAMD and PCV. and it is crucial to make accurate diagnosis for treatment. In this paper, we propose a structure-radiomic fusion network (DRFNet) to differentiate PCV and nAMD in optical coherence tomography (OCT) images.Approach.The subnetwork (RIMNet) is designed to automatically segment the lesion of nAMD and PCV. Another subnetwork (StrEncoder) is designed to extract deep structural features of the segmented lesion. The subnetwork (RadEncoder) is designed to extract radiomic features from the segmented lesions based on radiomics. 305 eyes (155 with nAMD and 150 with PCV) are included and manually annotated CNV region in this study. The proposed method was trained and evaluated by 4-fold cross validation using the collected data and was compared with the advanced differentiation methods.Main results.The proposed method achieved high classification performace of nAMD/PCV differentiation in OCT images, which was an improvement of 4.68 compared with other best method.Significance. The presented structure-radiomic fusion network (DRFNet) has great performance of diagnosing nAMD and PCV and high clinical value by using OCT instead of indocyanine green angiography.