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Green and sustainable power sources for next-generation electronics are being developed. A cellulose paper-based triboelectric nanogenerator (TENG) was fabricated to harness mechanical energy and convert it into electricity. This work proposes a novel approach to modify cellulose paper with natural dyes, including chlorophyll from spinach, anthocyanin from red cabbage, and curcumin from turmeric, to enhance the power output of a TENG. All the natural dyes are found to effectively improve the energy conversion performance of a cellulose paper-based TENG due to their photogenerated charges. The highest power density of 3.3 W/m2 is achieved from the cellulose paper-based TENG modified with chlorophyll, which is higher than those modified with anthocyanin and curcumin, respectively. The superior performance is attributed not only to the photosensitizer properties but also the molecular structure of the dye that promotes the electron-donating properties of cellulose. [ABSTRACT FROM AUTHOR]

The development of OLED materials by molecular design is important for high performance organic light emitting diode because tailoring the molecular structures can dramatically tune the properties such as efficiency, color, stability of device. Near‐infrared organic light‐emitting diodes (NIR OLEDs) with heavy metals or TADF materials are regularly reported due to the advantages of their various applications in healthcare services, veil authentication, and night vision displays. In this paper, we are summarized the collection of innovative organic near‐infrared (NIR) emitters which is crucial factor to design specific NIR emitter for NIR OLEDs [ABSTRACT FROM AUTHOR]

• It is shown that the commented paper has severe errors. • The analysis of the diffraction pattern was made without success. • The chemical composition of the studied crystals is unknown. My comments concern the errors in the crystallographic part of the commented paper. Moreover, the true chemical composition of the studied sample is different than BaNaFeWO 6 as proposed by authors. Therefore, the subsequent data on other measurements may have no scientific value. [ABSTRACT FROM AUTHOR]

Teaching chemistry and biology students about biologics design remains challenging despite its increasing importance in pharmaceutical development. Monoclonal antibodies, commonly called mAbs, are the most popular biologics. They have been developed into drugs to treat various diseases in the past decades. Multiple challenges exist for designing proper formulations to stabilize mAbs, such as preventing aggregation and mitigating viscosity. Molecular modeling and simulations can improve pharmaceutical products by examining the interactions between mAbs and other compounds, such as excipients. To introduce students to biopharmaceuticals, eight students at the Stevens Institute of Technology participated in a semester-long course to learn the challenges of pharmaceutical development and different computational skills to study biologics design. The students started with a limited background in this field. Throughout one semester, they were introduced to various literature and software tools for modeling antibodies and studying their interactions with excipients. This paper aims to develop a course structure to be replicated at other universities and institutions to teach biopharmaceutical development to students.

[Display omitted] • Synthesis and characterization of a phenothiazine-linked pyridine acetonitrile compound (PZ-PY) through Knoevenagel condensation reaction. • Confirmation of PZ-PY's molecular structure via single-crystal X-ray diffraction, revealing a monoclinic crystal system with a P2 1 /c space group. • Absorbance and emission spectra of PZ-PY receptor at 431 nm and 608 nm, respectively. • PZ-PY's exceptional ability to recognize and bind cyanide ions, a toxic environmental chemical, with significant photophysical properties. • Confirmation of binding stoichiometry (1:1) through various analytical methods including Job's and HRMS spectroscopy. Determination of a relatively low limit of detection for cyanide ions (8.79 × 10 -8 M). • For practical application, the I3 receptor was investigated through the test strips, solid state, bioimaging (A547 cell line), detection of cyanide in diverse water samples and food samples. A phenothiazine-linked pyridine acetonitrile with a cyanoethylene bond PZ-PY has been synthesized by Knoevenagel condensation reaction and characterized by spectroscopic and analytical techniques. The structure of PZ-PY was confirmed through single-crystal X-ray diffraction studies; revealing its monoclinic crystal system with a P2 1 /c space group. The absorption maximum and emission spectrum of the PZ-PY receptor were observed at 431 and 608 nm respectively. Cyanide anion is one of the most prevalent chemicals in the environment, its toxic nature poses a constant threat to human daily life. The PZ-PY receptor's recognition of cyanide ions is associated with remarkable photophysical properties. The binding stoichiometry of PZ-PY-CN- was confirmed by Job's plot, B-H studies, 1H NMR titration, TD-DFT, and ESI-mass spectroscopy. The relatively low limit of detection was determined to be 8.79 × 10 -8 M in a linear range between 0 and 120 µL. PZ-PY receptor exhibits an aggregation-caused quenching (ACQ) nature with the increase in water fraction; it is stable between pH 2 to 11. Moreover, the practical applicability of PZ-PY was investigated through the test strip, solid-state, bioimaging (A547 cell line), detection of cyanide in diverse water samples (tap water, distilled water, and lake water), and food samples (sprouted potatoes, bitter almonds, and cassava). [ABSTRACT FROM AUTHOR]

In this paper, we will explore the relation between molecular structure and functions displayed by biochemical molecules in complex physiological processes by using tools from the philosophy of science and the philosophy of scientific practice. We will argue that biochemical functions are weakly emergent from molecular structure by using an account of weak. In order to explore this thesis, we will consider the role of vitamin B12 in contributing to the process of erythropoiesis. The structure of the paper is the following: First, we will consider biochemical functions and why they cannot be easily reduced to their chemical realisers. We will suggest weak emergence as an alternative while also accounting for the relevance of the context, in our case, systemic and organisational. The paper will conclude by considering (1) how the usage of tools from the philosophy of science, such as weak emergence, can aid our understanding of the relations between the components of complex phenomena, such as erythropoiesis, and (2) how the philosophy of scientific practice sheds light on the explanatory role of processes that are dynamically stabilised and the different levels of organisation implied. [ABSTRACT FROM AUTHOR]

The document is a contents list for the journal CrystEngComm. It highlights various papers that have been published in the journal, covering topics such as the study of defects in crystals, heterojunctions for enhanced photocatalytic activity, reduction of oxygen concentration in silicon crystal growth, structural diversity of substituted thiacalixarene, synthesis of composite anode materials for Li-ion batteries, synthesis and characterization of alkali-metal isocyanurate, tunable emission properties of supramolecular compounds, analysis of crystal packing interactions, and the role of substituents on the molecular and electronic structures of dinuclear complexes. The journal is published by the Royal Society of Chemistry, a leading chemistry community. [Extracted from the article]

A multi-stimuli responsive fluorophore, named NBDNI, was developed by constructing a 1,8-naphthalimide derivative in which a rotatable electron-donating N,N-dimethylaniline group attached to its 4-position. This molecular structure endowed NBDNI with aggregate-induced emission (AIE) and twisted intramolecular charge transfer (TICT) properties, enabling remarkable fluorescence changes in response to multiple external stimuli: (i) sensitivity to polarity in various solvent systems and polymer matrix; (ii) significant fluorescence response and excellent linearity towards temperature changes in solution; (iii) distinct switch of fluorescence color upon acid and base treatments; (iv) reversible mechanochromism behavior in the solid state. Moreover, the mechanisms underlying the aforementioned stimuli-responsive phenomena have been proposed based on comprehensive systematic measurements. Furthermore, preliminary applications such as fluorescence thermometry and acid/base test paper have been demonstrated. This research will bring about new opportunities for the development of novel stimuli-responsive luminescent materials. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a three-dimensional vector field model is proposed, whose dimensions are the Hansen Solubility Parameters: dispersion parameter (δD), polarity parameter (δP), and hydrogen bonding parameter (δH). The vector space that defines the field has the peculiarity of having a dispersion vector with a magnitude of 2 as its base vector, while the polarity and hydrogen bonding vectors have a magnitude of 1. A substance is characterised as a position vector, and the interaction between two substances is determined by calculating the vector difference of both, known as the interaction vector. The interaction among substances may involve solubility, swelling, cracking, surface tension, interface tension, and any physical phenomena where the intermolecular energies of dispersion, polarity or hydrogen bonding come into play. This paper studies free surface energy (surface and interfacial tension). It has been found that free surface energy is directly proportional to the square of the magnitude of the interaction vector. The proportionality constant, τ, is expressed in length units, has a value of 0.025 nm, and does not depend on the chemical nature of the substance or state of matter (solid, liquid or gas). The constant value τ appears universal and aligns with the thickness of interfaces, thereby supporting Guggenheim's hypothesis. This hypothesis asserts that interfaces possess actual thickness and are not merely mathematical surfaces, as originally postulated by Gibbs. Moreover, it also has been found that the interface thickness, τ, is approximately equal to half of the Bohr radius, a0, which is defined by universal constants. Because the solubility parameters of thousands of substances are known and can be easily determined from their molecular structure, a good approximation of the surface and interfacial tension of any given substance can now be calculated. It has also been found that the contact angles of sessile droplets in three-phased systems can be calculated from the interaction vectors of the implicated substances. [ABSTRACT FROM AUTHOR]

In the heterogeneous reservoirs, CO2 flooding easily leads to CO2 gas channeling, which can seriously affect sweeping efficiency and reduce oil recovery. After thoroughly investigating the advantages and shortcomings of various CO2 plugging technologies, this paper focuses on the feasibility of improving conventional water-alternating gas (WAG) through CO2-responsive gel materials. Based on the different chemical reaction mechanisms between the unique chemical structure and CO2, changes in the material's physical and chemical properties can respond to CO2. The feasibility of utilizing these property changes for CO2-responsive plugging is explored. Various CO2-responsive gels and gel nanoparticles have been extensively researched in different fields, such as energy, medicine, and biology. This paper surveys the molecular structures, chemical compositions, response mechanisms, and changes of these CO2-responsive gels, aiming to draw insights into the carbon dioxide-enhanced oil recovery (CO2-EOR) field. Finally, the key issues and future development direction of CO2-responsive plugging gels were analyzed. [ABSTRACT FROM AUTHOR]

• A new tetraphenylethene midified quinolone derivative TPE-QL was designed and prepared. • TPE-QL exhibited highly twisted conformation, high fluorescence quantum and AIE behaviors. • TPE-QL showed mechanochromic behavior by changing the emitting color from blue-green upon grinding. A simple tetraphenylethene (TPE) modified quinoline derivative TPE-QL was designed and prepared. It possessed donor-acceptor molecular structure and highly twisted conformation, which could be proved by spectral studies and theoretical calculatiuons. Due to the introduction of TPE unit, TPE-QL exhibited typical aggregation-induced emission (AIE) characteristic. Interestinly, TPE-QL also showed obvious fluorescence response to mechanical force by changing the emission wavelength from 440 nm to 485 nm upon grinding. Moreover, reversible mechanochromic behavior was detected after repeated grinding and fuming treatment. This work not only discovered a new AIE-active mechanochromic material, but also provided possibility for its application in the filed of ink-free rewritable papers for security decumentation purposes. [Display omitted] [ABSTRACT FROM AUTHOR]

Simple Summary: Recent advancements in cancer research have proven immunotherapies to be a promising strategy for the treatment of hematological malignancies. The bispecific antibody (BsAb) format was developed to overcome the issues of monoclonal antibody-based therapies. T-cell engagers (TCEs) are BsAbs, which directly activate T-cells and their anti-tumor features, ultimately resulting in the lysis of the targeted tumor cells. In 2014, the FDA approved blinatumomab for treatment of acute lymphoblastic leukemia. As of November 2023, seven clinically approved TCE therapies are on the market. In this paper, we summarized the technical basis of the TCE technology, its application in hematology, and its current issues and prospects. Recent advancements in cancer immunotherapy have made directing the cellular immune response onto cancer cells a promising strategy for the treatment of hematological malignancies. The introduction of monoclonal antibody-based (mAbs) targeted therapy has significantly improved the prognosis for hematological patients. Facing the issues of mAb-based therapies, a novel bispecific antibody (BsAb) format was developed. T-cell engagers (TCEs) are BsAbs, which simultaneously target tumor-associated antigens on tumor cells and CD3 molecules present on T-cells. This mechanism allows for the direct activation of T-cells and their anti-tumor features, ultimately resulting in the lysis of tumor cells. In 2014, the FDA approved blinatumomab, a TCE directed to CD3 and CD19 for treatment of acute lymphoblastic leukemia. Since then, numerous TCEs have been developed, allowing for treating different hematological malignancies such as acute myeloid leukemia, multiple myeloma, and non-Hodgkin lymphoma and Hodgkin lymphoma. As of November 2023, seven clinically approved TCE therapies are on the market. TCE-based therapies still have their limitations; however, improving the properties of TCEs, as well as combining TCE-based therapies with other forms of treatment, give hope to find the cures for currently terminal diseases. In this paper, we summarized the technical basis of the TCE technology, its application in hematology, and its current issues and prospects. [ABSTRACT FROM AUTHOR]

Simple Summary: Metformin is one of the most widely used drugs in the world, since its first use in the second part of the 1950s in France (Aron, 1957) and in the United Kingdom (Rona, 1958), and is on the World Health Organization's List of Essential Medicines. Traditionally, metformin is used in diabetes mellitus, mainly in overweight and obese subjects, but also in other conditions of impaired glucose metabolism, such as insulin resistance. In recent years, in vitro and in vivo data on this molecule as an antiproliferative modulator have suggested a series of clinical trials in several tumors that—at the moment—have not confirmed the expected positive results. The aim of this paper is to offer a double vision of this molecule, with a very light side about the metabolic aspects and a darker side concerning its antineoplastic activity, focusing on molecular and subcellular pathways involved in both fields and discussing the contrast between preliminary cellular data and real clinical outcomes in different neoplasms. The ancient Roman god Ianus was a mysterious divinity with two opposite faces, one looking at the past and the other looking to the future. Likewise, metformin is an "old" drug, with one side looking at the metabolic role and the other looking at the anti-proliferative mechanism; therefore, it represents a typical and ideal bridge between diabetes and cancer. Metformin (1,1-dimethylbiguanidine hydrochloride) is a drug that has long been in use for the treatment of type 2 diabetes mellitus, but recently evidence is growing about its potential use in other metabolic conditions and in proliferative-associated diseases. The aim of this paper is to retrace, from a historical perspective, the knowledge of this molecule, shedding light on the subcellular mechanisms of action involved in metabolism as well as cellular and tissue growth. The intra-tumoral pharmacodynamic effects of metformin and its possible role in the management of different neoplasms are evaluated and debated. The etymology of the name Ianus is probably from the Latin term ianua, which means door. How many new doors will this old drug be able to open? [ABSTRACT FROM AUTHOR]

The Sombor index (SO) is a recently invented vertex-degreebased molecular structure-descriptor. LetM1 be the first Zagreb index. The fact that SO is bounded from below by M1/√2 and from above by M1 is well-known and easy to prove. In this paper, we improve these bounds. [ABSTRACT FROM AUTHOR]

This paper delves into the diverse and significant roles of curcumin, a polyphenolic compound from the Curcuma longa plant, in the context of cancer and inflammatory diseases. Distinguished by its unique molecular structure, curcumin exhibits potent biological activities including anti-inflammatory, antioxidant, and potential anticancer effects. The research comprehensively investigates curcumin's molecular interactions with key proteins involved in cancer progression and the inflammatory response, primarily through molecular docking studies. In cancer, curcumin's effectiveness is determined by examining its interaction with pivotal proteins like CDK2, CK2α, GSK3β, DYRK2, and EGFR, among others. These interactions suggest curcumin's potential role in impeding cancer cell proliferation and survival. Additionally, the paper highlights curcumin's impact on inflammation by examining its influence on proteins such as COX-2, CRP, PDE4, and MD-2, which are central to the inflammatory pathway. In vitro and clinical studies are extensively reviewed, shedding light on curcumin's binding mechanisms, pharmacological impacts, and therapeutic application in various cancers and inflammatory conditions. These studies are pivotal in understanding curcumin's functionality and its potential as a therapeutic agent. Conclusively, this review emphasizes the therapeutic promise of curcumin in treating a wide range of health issues, attributed to its complex chemistry and broad pharmacological properties. The research points towards curcumin's growing importance as a multi-faceted natural compound in the medical and scientific community. [ABSTRACT FROM AUTHOR]

Forte is an open-source library specialized in multireference electronic structure theories for molecular systems and the rapid prototyping of new methods. This paper gives an overview of the capabilities of Forte, its software architecture, and examples of applications enabled by the methods it implements. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a neurodegenerative disease with insidious onset and progressive development. It is clinically characterized by cognitive impairment, memory impairment and behavioral change. Chinese herbal medicine and acupuncture are important components of traditional Chinese medicine (TCM), and are commonly used in clinical treatment of AD. This paper systematically summarizes the research progress of traditional Chinese medicine natural products and acupuncture treatment of AD, which combined with existing clinical and preclinical evidence, based on a comprehensive review of neuroinflammation, and discusses the efficacy and potential mechanisms of traditional Chinese medicine natural products and acupuncture treatment of AD. Resveratrol, curcumin, kaempferol and other Chinese herbal medicine components can significantly inhibit the neuroinflammation of AD in vivo and in vitro, and are candidates for the treatment of AD. Acupuncture can alleviate the memory and cognitive impairment of AD by improving neuroinflammation, synaptic plasticity, nerve cell apoptosis and reducing the production and aggregation of amyloid β protein (Aβ) in the brain. It has the characteristics of early, safe, effective and benign bidirectional adjustment. The purpose of this paper is to provide a basis for improving the clinical strategies of TCM for the treatment of AD. [ABSTRACT FROM AUTHOR]

This document, titled "Design of Dosage Forms with Improved Biopharmaceutical Properties," discusses the importance of developing pharmaceutical products with optimal dosage forms to ensure stability, accurate dosage, desired pharmacological effects, and ease of administration with minimal side effects. The document highlights a special issue of the journal Pharmaceutics that features nine original papers on various innovative methods to improve the biopharmaceutical properties of dosage forms. These papers cover topics such as theranostic agents, polysaccharide nanoparticles, drug-loaded beads, pharmaceutical gels, metal-organic frameworks, micellar systems, and drug nanoformulations. The document emphasizes the potential of these advancements in pharmaceutical science to expand therapeutic options and improve patient outcomes. [Extracted from the article]

This paper reports on the linear colorimetric and electrochromic (EC) characteristics of electrodeposited polyaniline (PANI) films. This paper also investigates the infrared EC properties of acid-doped PANI films. The electrochemical polymerization method was employed to create a porous and thin PANI film layer onto PET-ITO substrates. This layer was capped with WO3 film to create a gel electrolyte sandwich structure that demonstrates the compatibility of PANI films with cathodic WO3 films in full devices. The electrodeposition of the film was fabricated by applying different voltages and time, with the optimal film quality achieved with the 1.7 V voltage and a 20 min deposition period. The surface morphology, optical performance, electrochemical behavior, and molecular structure evolution are comprehensively studied in this work. The linear colorimetric behaviors and the corresponding significant changes in the structure in Raman spectra build direct strong quantitative relations in EC polymers. The well-defined oxidation and reduction peaks observed in the cyclic voltammetry indicate the ion-diffusion dominant process in the electrochromism of PANI. Significant transitions between the benzene and quinone phases in the Raman spectra are found in the bleached and colored states of polymers. This study enhances the understanding of PANI film structure and electrochemical and associated optical properties, providing more insights into the dual-function EC charge storage polymers and other energy-related functional materials. [ABSTRACT FROM AUTHOR]

Covering: 2019 to 2023. Even with the advent of modern and complementary spectroscopy techniques, comprehensive characterization of natural product continues to represent an onerous and time-consuming task, being far away to become rather "routine". Mainly due to their highly complex structures and small amount of isolated sample, in milligram or sub-milligram quantities, structural misassignment of natural products are still a recurrence theme in the modern literature. Since the seminal paper from Nicolau and Snider, in 2005, evaluating the various cases of reassignment of natural products, from the present era, in which NMR parameters calculations play such an important role in the structural elucidation of natural products, helping to uncover and ultimately revise the structure of previously reported compounds, a pertinent question arises: are we still chasing molecules that were never there? In this minireview, we intent to discuss the current state of computational NMR parameter calculations, with a particular focus on their application in the structural determination of natural products. Additionally, we have conducted a comprehensive survey of the literature spanning the years 2019-2023, in order to select and discuss recent noteworthy cases of incorrectly assigned structures that were revised through NMR calculations. Therefore, our main goal is to show what can be done through computational simulations of NMR parameters, currently user-friendly and easily implemented by non-expert users with basic skills in computational chemistry, before venturing into complex and time-consuming total synthesis projects. In conclusion, we anticipate a promising future for NMR parameter calculations, fueled by the ongoing development of user-friendly tools and the integration of artificial intelligence. The emergence of these advancements is poised to broaden the applications of NMR simulations, offering a more accessible and reliable means to address the persistent challenge of structural misassignments in natural product chemistry. [ABSTRACT FROM AUTHOR]

Structure elucidation is a stage of paramount importance in the discovery of novel compounds because molecular structure determines their physical, chemical and biological properties. Computational prediction of spectroscopic data, mainly NMR, has become a widely used tool to help in such tasks due to its increasing easiness and reliability. However, despite the continuous increment in CPU calculation power, classical quantum mechanics simulations still require a lot of effort. Accordingly, simulations of large or conformationally complex molecules are impractical. In this context, a growing number of research groups have explored the capabilities of machine learning (ML) algorithms in computational NMR prediction. In parallel, important advances have been made in the development of machine learninginspired methods to correlate the experimental and calculated NMR data to facilitate the structural elucidation process. Here, we have selected some essential papers to review this research area and propose conclusions and future perspectives for the field. [ABSTRACT FROM AUTHOR]

Copyright of University Chemistry is the property of Peking University, College of Chemistry & Molecular Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: Cell biology continuously shows the need for new fluorescent tags with advanced properties. The object of our current study is a new genetically encoded monomeric red fluorescent biomarker mKate2-K67R/R197H (λex/λem 579/603 mn), designed from commercial biomarker mKate2 by two R197H/K67R mutations. The mKate2 precursor, a far-red fluorescent protein, is nearly 3-fold brighter than the previously designed mKate. Compared with commercial mKate2, the double mutant mKate2-K67R/R197H (alternative names FusionRed2 and Diogenes) exhibits an additional ~1.6-fold increase in fluorescence brightness and represents the next generation of extra-bright red fluorescent probes offering novel possibilities for fluorescent imaging of proteins in living cells and animals. Methods: The paper presents the results of X-ray and molecular dynamics study of new bright biomarker mKate2-K67R/R197H. Results and Discussion: The three dimensional structure of new advanced red fluorescent biomarker mKate2-K67R/R197H has been studied by X-ray method at 1.5Å resolution supported by molecular dynamics (MD) study The principal structural fold of the protein is an 11-stranded β-barrel. The nearest chromophore environment (≤ 4 Å) comprises 18 tightly packed residues. Conclusions: The MD study showed that the brightness of mKate2-K67R/R197H and its mKate2 precursor correlates with the dipole moments of the amino acid environments of the chromophores. The higher the dipole moment, the higher the brightness of biomarker. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Chemical molecular structures are a direct and convenient means of expressing chemical knowledge, playing a vital role in academic communication. In chemistry, hand drawing is a common task for students and researchers. If we can convert hand-drawn chemical molecular structures into machine-readable formats, like SMILES encoding, computers can efficiently process and analyze these structures, significantly enhancing the efficiency of chemical research. Furthermore, with the progress of educational technology, automated grading is gaining popularity. When machines automatically recognize chemical molecular structures and assess the correctness of the drawings, it offers great convenience to teachers. We created ChemReco, a tool designed to identify chemical molecular structures involving three atoms: C, H, and O, providing convenience for chemical researchers. Currently, there are limited studies on hand-drawn chemical molecular structures. Therefore, the primary focus of this paper is constructing datasets. We propose a synthetic image method to rapidly generate images resembling hand-drawn chemical molecular structures, enhancing dataset acquisition efficiency. Regarding model selection, the hand-drawn chemical molecule structural recognition model developed in this article achieves a final recognition accuracy of 96.90%. This model employs the encoder-decoder architecture of EfficientNet + Transformer, demonstrating superior performance compared to other encoder-decoder combinations. [ABSTRACT FROM AUTHOR]

Introduction: Blackheart is one of the most common physiological diseases in potatoes during storage. In the initial stage, black spots only occur in tissues near the potato core and cannot be detected from an outward appearance. If not identified and removed in time, the disease will seriously undermine the quality and sale of the-entire batch of potatoes. There is an urgent need to develop a method for early detection of blackheart in potatoes. Methods: This paper used visible-near infrared (Vis/NIR) spectroscopy to conduct online discriminant analysis on potatoes with varying degrees of blackheart and healthy potatoes to achieve real-time detection. An efficient and lightweight detection model was developed for detecting different degrees of blackheart in potatoes by introducing the depth-wise convolution, pointwise convolution, and efficient channel attention modules into the ResNet model. Two discriminative models, the support vector machine (SVM) and the ResNet model were compared with the modified ResNet model. Results and discussion: The prediction accuracy for blackheart and healthy potatoes test sets reached 0.971 using the original spectrum combined with a modified ResNet model. Moreover, the modified ResNet model significantly reduced the number of parameters to 1434052, achieving a substantial 62.71% reduction in model complexity. Meanwhile, its performance was evidenced by a 4.18% improvement in accuracy. The Grad-CAM++ visualizations provided a qualitative assessment of the model’s focus across different severity grades of blackheart condition, highlighting the importance of different wavelengths in the analysis. In these visualizations, the most significant features were predominantly found in the 650–750 nm range, with a notable peak near 700 nm. This peak was speculated to be associated with the vibrational activities of the C-H bond, specifically the fourth overtone of the C-H functional group, within the molecular structure of the potato components. This research demonstrated that the modified ResNet model combined with Vis/NIR could assist in the detection of different degrees of black in potatoes. [ABSTRACT FROM AUTHOR]

Distance-based topological indices are numerical parameters that are derived from the distances between atoms in a molecular structure, and they provide a quantitative measure of the topology and geometry of a molecule. The distance-based topological indices uses to predict various properties of molecules, including their boiling points, melting points, and solubility. It also predicts the biological activity of molecules, including their pharmacological and toxicological properties. Pentagonal chain molecules are organic compounds that consist of a linear chain of five-membered (pentagons) connected by carbon and bonds. These molecules have unique structural and electronic properties that make them useful in a variety of applications. Motivated by the pentagonal chain molecules, we have considered a pentagonal chain graph and it is denoted by Pn. We have computed some distance based topological indices for Pn. The paper focuses on a pentagonal chain molecules denoted by G, and derives several distance-based topological indices. These indices compromise insights into physicochemical properties, aid in identifying structural characterizations, and enhance understanding of molecular properties. [ABSTRACT FROM AUTHOR]

The diketopyrrolopyrrole (DPP) unit represents one of the building blocks more widely employed in the field of organic electronics; in most of the reported DPP-based small molecules, this unit represents the electron acceptor core symmetrically coupled to donor moieties, and the solubility is guaranteed by functionalizing lactamic nitrogens with long and branched alkyl tails. In this paper, we explored the possibility of modulating the solubility by realizing asymmetric DPP derivatives, where the molecular structure is extended in just one direction. Four novel derivatives have been prepared, characterized by a common dithyenil-DPP fragment and functionalized on one side by a thiophene unit linked to different auxiliary electron acceptor groups. As compared to previously reported symmetric analogs, the novel dyes showed an increased solubility in chloroform and proved to be soluble in THF as well. The novel dyes underwent a thorough optical and electrochemical characterization. Electronic properties were studied at the DFT levels. All the dyes were used as active layers in organic field effect transistors, showing balanced charge transport properties. [ABSTRACT FROM AUTHOR]

Drug-drug interaction (DDI) is the combined effects of multiple drugs taken together, which can either enhance or reduce each other's efficacy. Thus, drug interaction analysis plays an important role in improving treatment effectiveness and patient safety. It has become a new challenge to use computational methods to accelerate drug interaction time and reduce its cost-effectiveness. The existing methods often do not fully explore the relationship between the structural information and the functional information of drug molecules, resulting in low prediction accuracy for drug interactions, poor generalization, and other issues. In this paper, we propose a novel method, which is a deep graph contrastive learning model for drug-drug interaction prediction (DeepGCL for brevity). DeepGCL incorporates a contrastive learning component to enhance the consistency of information between different views (molecular structure and interaction network), which means that the DeepGCL model predicts drug interactions by integrating molecular structure features and interaction network topology features. Experimental results show that DeepGCL achieves better performance than other methods in all datasets. Moreover, we conducted many experiments to analyze the necessity of each component of the model and the robustness of the model, which also showed promising results. The source code of DeepGCL is freely available at https://github.com/jzysj/DeepGCL. [ABSTRACT FROM AUTHOR]

Simple Summary: Though chemotherapy is generally known to be effective in the fight against cancer, its application is associated with a number of side effects, including toxic impacts on the ovaries. The most ovotoxic cytostatic chemotherapeutics are the classical alkylating compounds, particularly cyclophosphamide. Thus, it is of utmost importance to find effective means to protect ovaries against the negative influence of chemotherapeutic agents. This review paper presents the results of the current research work on the hitherto proposed agents potentially protecting the functions and state of ovaries exposed to chemotherapy. A large body of promising results have been reported, but as presented, it is necessary to undertake thorough and comprehensive studies aimed at providing an explicit evaluation of the efficacy of selected ovoprotecting agents and their possible clinical use in the future. Chemotherapy is one of the leading cancer treatments. Unfortunately, its use can contribute to several side effects, including gynotoxic effects in women. Ovarian reserve suppression and estrogen deficiency result in reduced quality of life for cancer patients and are frequently the cause of infertility and early menopause. Classic alkylating cytostatics are among the most toxic chemotherapeutics in this regard. They cause DNA damage in ovarian follicles and the cells they contain, and they can also induce oxidative stress or affect numerous signaling pathways. In vitro tests, animal models, and a few studies among women have investigated the effects of various agents on the protection of the ovarian reserve during classic chemotherapy. In this review article, we focused on the possible beneficial effects of selected hormones (anti-Müllerian hormone, ghrelin, luteinizing hormone, melatonin), agents affecting the activity of apoptotic pathways and modulating gene expression (C1P, S1P, microRNA), and several natural (quercetin, rapamycin, resveratrol) and synthetic compounds (bortezomib, dexrazoxane, goserelin, gonadoliberin analogs, imatinib, metformin, tamoxifen) in preventing gynotoxic effects induced by commonly used cytostatics. The presented line of research appears to provide a promising strategy for protecting and/or improving the ovarian reserve in the studied group of cancer patients. However, well-designed clinical trials are needed to unequivocally assess the effects of these agents on improving hormonal function and fertility in women treated with ovotoxic anticancer drugs. [ABSTRACT FROM AUTHOR]

Simple Summary: The rising incidence of cancer is a major threat to patients and healthcare services worldwide. It is therefore important to search for novel therapies and new drugs. Honokiol, found in the bark of the magnolia tree, has many properties, including anticancer activity. However, its potential use is limited due to its poor solubility in water. The present study aimed to review the available studies using modern delivery systems for honokiol and determine their anticancer efficacy in vitro and in vivo. Cancer is a leading cause of death worldwide, and the effectiveness of treatment is consistently not at a satisfactory level. This review thoroughly examines the present knowledge and perspectives of honokiol (HON) in cancer therapeutics. The paper synthesizes critical insights into the molecular mechanisms underlying the observed anticancer effects, emphasizing both in vitro and in vivo studies. The effects of HON application, primarily in the common types of cancers, are presented. Because the therapeutic potential of HON may be limited by its physicochemical properties, appropriate delivery systems are sought to overcome this problem. This review discusses the effect of different nanotechnology-based delivery systems on the efficiency of HON. The data presented show that HON exhibits anticancer effects and can be successfully administered to the site of action. Honokiol exerts its anticancer activity through several mechanisms. Moreover, some authors used the combinations of classical anticancer drugs with HON. Such an approach is very interesting and worth further investigation. Understanding HON's multiple molecular mechanisms would provide valuable insights into how HON might be developed as an effective therapeutic. Therefore, further research is needed to explore its specific applications and optimize its efficacy in diverse cancer types. [ABSTRACT FROM AUTHOR]

This work introduces the development of path Dirac and hypergraph Dirac operators, along with an exploration of their persistence. These operators excel in distinguishing between harmonic and non-harmonic spectra, offering valuable insights into the subcomplexes within these structures. The paper showcases the functionality of these operators through a series of examples in various contexts. An essential facet of this research involves examining the operators' sensitivity to filtration, emphasizing their capacity to adapt to topological changes. The paper also explores a significant application of persistent path Dirac and persistent hypergraph Dirac in molecular science, specifically in analyzing molecular structures. The study introduces strict preorders derived from molecular structures, which generate graphs and digraphs with intricate path structures. The depth of information within these path complexes reflects the complexity of different preorder classes influenced by molecular structures. This characteristic underscores the effectiveness of these tools in the realm of topological data analysis. [ABSTRACT FROM AUTHOR]

Considering the rapid evolution of lithium silicate-based glass ceramics (LSCs) in dentistry, this review paper aims to present an updated overview of the recently introduced commercial novel LSCs. The clinical and in vitro English-language literature relating to the microstructure, manufacturing, strengthening, properties, surface treatments and clinical performance of LSC materials was obtained through an electronic search. Findings from relevant articles were extracted and summarised for this manuscript. There is considerable evidence supporting the mechanical and aesthetic competency of LSC variants, namely zirconia-reinforced lithium silicates and lithium–aluminium disilicates. Nonetheless, the literature assessing the biocompatibility and cytotoxicity of novel LSCs is scarce. An exploration of the chemical, mechanical and chemo-mechanical intaglio surface treatments—alternative to hydrofluoric acid etching—revealed promising adhesion performance for acid neutralisation and plasma treatment. The subtractive manufacturing methods of partially crystallised and fully crystallised LSC blocks and the additive manufacturing modalities pertaining to the fabrication of LSC dental restorations are addressed, wherein that challenges that could be encountered upon implementing novel additive manufacturing approaches using LSC print materials are highlighted. Furthermore, the short-term clinical performance of zirconia-reinforced lithium silicates and lithium–aluminium disilicates is demonstrated to be comparable to that of lithium disilicate ceramics and reveals promising potential for their long-term clinical performance. [ABSTRACT FROM AUTHOR]

Halide perovskites possess ultra-low thermal conductivity and show high potential for thermoelectric devices. The chemical properties and molecular structure of halide perovskite materials are not completely stable under ambient conditions, which hinders their use in thermoelectric generators. Changes in the properties of bulk halide perovskite thermoelectrics are accompanied by partial phase transitions and surface oxidation processes. In this paper, we conducted a comprehensive study of the transport and structural properties of CsSnI3, which were pristine by vacuum melting followed by spark plasma sintering. The research results on the electrical transport of these materials revealed that exposure to an inert atmosphere does not deteriorate stability and the properties of the materials remain unchanged. However, prolonged exposure to air leads to a significant degradation of the electrical transport properties. Contrary to thin-film samples, the shift to the double perovskite structure from the perovskite one is limited to a specific surface layer. This change significantly influences the electrical transport of the material while maintaining the essential properties of both perovskite types. [ABSTRACT FROM AUTHOR]

Effectively enhancing oil recovery can be achieved by reducing the viscosity of crude oil. Therefore, this paper investigated the viscosity reduction behavior of carbon nanotube viscosity reducers with different molecular structures at the oil–water interface, aiming to guide the synthesis of efficient viscosity reducers based on molecular structure. This study selected carbon nanotubes with different functional groups (NH2-CNT, OH-CNT, and COOH-CNT) for research, and carbon nanotubes with varying carbon chain lengths were synthesized. These were then combined with Tween 80 to form a nanofluid. Scanning electron microscopy analysis revealed an increased dispersibility of carbon nanotubes after introducing carbon chains. Contact angle experiments demonstrated that -COOH exhibited the best hydrophilic effect. The experiments of zeta potential, conductivity, viscosity reduction, and interfacial tension showed that, under the same carbon chain length, the conductivity and viscosity reduction rate sequence for different functional groups was -NH2 < -OH < -COOH. The dispersing and stabilizing ability and interfacial tension reduction sequence for different functional groups was -COOH < -OH < -NH2. With increasing carbon chain length, conductivity and interfacial tension decreased, and the viscosity reduction rate and the dispersing and stabilizing ability increased. Molecular dynamics simulations revealed that, under the same carbon chain length, the diffusion coefficient sequence for different functional groups was -NH2 < -OH < -COOH. The diffusion coefficient gradually decreased as the carbon chain length increased, resulting in better adsorption at the oil–water interface. This study holds significant importance in guiding viscosity reduction in heavy oil to enhance oil recovery. [ABSTRACT FROM AUTHOR]

The geometrical re parameters of trans-azobenzene (E-AB) free molecule were refined by gas electron diffraction (GED) method using available experimental data obtained previously by S. Konaka and coworkers. Structural analysis was carried out by various techniques. First of all, these included the widely used molecular orbital constrained gas electron diffraction method and regularization method. The results of the refinements using different models were also compared—a semirigid model, three variants of one-dimensional dynamic models, and a two-dimensional pseudoconformer model. Several descriptions have been used due to the fact that E-AB has a shallow potential energy surface along the rotation coordinates of phenyl groups. Despite this, it turned out that the semirigid model is suitable for use for E-AB and allows good agreement with experimental data to be achieved. According to the results of GED structural analysis, coupled with the results of DLPNO-CCSD(T0) calculations, E-AB has a planar structure. Based only on GED data, it is impossible to unambiguously determine the rotational angle of the phenyl group due to the facts that (i) with rotation over a wide range of angles, the bonded distances in the molecule change insignificantly and (ii) potential function in a structural analysis within a dynamic model is not determined with the necessary accuracy. This work also examines the sensitivity of the GED method to structural changes caused by trans-cis isomerization. The paper also analyzes the applicability of different variants of density functional theory (DFT) calculations in GED structural analysis using E-AB as an example. There are not enough similar methodological works in the literature. This experimental and methodological information is especially important and relevant for planning and implementing GED experiments and corresponding processing of the results for azobenzene derivatives, in which the conformer and isomeric diversity are even more complicated due to the presence of different substituents. [ABSTRACT FROM AUTHOR]

Indium phosphide (InP) is a binary semiconductor composed of indium and phosphorus. It has a zinc blende crystal structure, which is a type of cubic lattice structure. This lattice is composed of indium and phosphorus atoms arranged in a lattice of cube-shaped cells, with each cell containing four indium atoms and four phosphorus atoms. This lattice structure is the same for all materials with a zinc blende crystal structure and is the most common type of lattice structure in semiconductors. Indium phosphide (InP) has several chemical applications. It is commonly used as a dopant in the production of semiconductors, where it helps control the electrical properties of the material. InP is also utilized in the synthesis various indium-containing compounds, which can have applications in catalysts and chemical reactions. Additionally, InP nanoparticles have been investigated for their potential use in biomedical imaging and drug delivery systems. The topological characterization of 3D molecular structures can be performed via graph theory. In graph theory, the connections between atoms are represented as edges and the atoms themselves are represented as nodes. Furthermore, graph theory can be used to calculate the topological descriptors of the molecule such as the degree-based and reverse degree-based irregularity toplogical indices. These descriptors can be used to compare the topology of different molecules. This paper deals with the modeling and topological characterization of indium phosphide (InP) via degree-based and reverse irregularity indices. The 3D crystal structure of the InP is topologically modeled via partition of the edges, and derived closed form expressions for its irregularity indices. Our obtained results will be surely be helpful in investigating the QSPR/QSAR analysis as well as understanding the deep irregular behavior of the indium phosphide (InP) . [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has significantly affected both the global economy and human health. COVID-19 is a single-stranded RNA virus that spreads through the inhalation of viral droplets. Its genome encodes four structural proteins: the envelop protein, spike protein, membrane protein, and nucleocapsid protein. The virus's capsid is a protein shell that contains a positive RNA strand that allows it to take control of human cell machinery. Currently, the only treatments for COVID-19 are preventative measures and immunization. Some of the anti-COVID and anti-cancer medications used to combat this virus include Camptothecin Polymer, Hyaluronic Acid-curcumin, and Hydroxychloroquine. Graphs are used extensively in chemical investigation to provide a mathematical model of molecules. The selection of graph invariants, formerly known as molecular structure descriptor's, is the mathematical modelling of chemical compounds' physio-chemical, pharmacologic, and toxicological aspects. This paper presents a new technique to compute topological indices for three types of chemical networks for a few anti-COVID and anti-cancer medications. Our findings suggest that these indices show a strong association with the acentric factor and entropy, which make them effective in QSPR and QSAR analysis with high accuracy. [ABSTRACT FROM AUTHOR]

This paper explores recent advancements in the field of circularly polarized luminescence (CPL) exhibited by small and isolated organic molecules. The development and application of small CPL molecule are systematically reviewed through eight different chiral skeleton sections. Investigating the intricate interplay between molecular structure and CPL properties, the paper aims at providing and enlighting novel strategies for CPL‐based applications. [ABSTRACT FROM AUTHOR]

In this paper, a new type of Gemini surfactant was synthesized by esterification reaction of phthalic anhydride and fatty alcohol polyoxyethylene ether to improve the pollution problem and achieve the purpose of reservoir restoration in the near-wellbore area. The target product was characterized by infrared spectroscopy and hydrogen nuclear magnetic resonance spectroscopy. The ability of Gemini surfactant to reduce boundary surface tension, wettability, dispersion, viscosity reduction, oil washing and core damage recovery were studied. Gemini surfactant The critical micelle concentration (cmc) and the corresponding γ-cmc of Gemini surfactant are 26 mg/L and 30.26 μN/m, respectively. Gemini surfactant has a good ability to wash oil, which effectively reduce the interfacial tension of oil and water. At the same time, the benzene ring in the molecular structure of Gemini surfactant dissolve the organic matter in the pollution source, and the core permeability could be restored. [ABSTRACT FROM AUTHOR]

Graphs are used to solve many problems in mathematics and computer sciences. Many structures can be displayed with the help of graphs. For example, a directed graph can be used to show how websites are related to each other. Vague graph (VG) is one of the most important graphs in the fuzzy graph (FG)-theory, which can play a significant role in finding the most suitable places in construction and also finding the shortest path in computer networks. Connectivity indices are one of the most widely used topics in graph theory, which are used in other sciences, including computer science and chemistry. One of the most famous indices in the graph is the Wiener index, which belongs to the description of the molecular structure, which is used to design molecules with desirable properties. Therefore, in this paper, we introduce important topological indices such as Wiener index, Wiener absolute index, Randic index, Zegreb index, Harmonic index, and Average Wiener index on VGs and investigate their properties with several examples. Finally, an application of the Wiener index is given to find the most suitable place to build an university. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer is a leading cause of death worldwide. The costs involved in cancer diagnosis and treatment are extraordinary. Important steps that can be taken that would reduce costs include earlier cancer diagnosis for which significant headway is being made through biomarker identification in bodily fluids and imaging. Other important steps will be to identify treatment approaches that do not 'break the bank' and affect a patient's wellbeing. Herein, we aim to highlight the potential of phytochemicals as a cost-effective approach to aid in the treatment of cancer. We focus on phytochemicals that target ion channels, as molecules that mediate critical communication of a cell with its environment. Ultimately, we posit that phytochemicals targeting ion channels can be employed to aid cancer treatment. Modern chemotherapies offer a broad approach to cancer treatment but eliminate both cancer and non-cancer cells indiscriminately and, thus, are associated with a host of side effects. Advances in precision oncology have brought about new targeted therapeutics, albeit mostly limited to a subset of patients with an actionable mutation. They too come with side effects and, ultimately, 'self-resistance' to the treatment. There is recent interest in the modulation of ion channels, transmembrane proteins that regulate the flow of electrically charged molecules in and out of cells, as an approach to aid treatment of cancer. Phytochemicals have been shown to act on ion channels with high specificity regardless of the tumor's genetic profile. This paper explores the use of phytochemicals in cancer symptom management and treatment. [ABSTRACT FROM AUTHOR]

In order to address the issues of energy depletion, more resources are being searched for in the deep sea. Therefore, research into how the deep-sea environment affects cement-based materials for underwater infrastructure is required. This paper examines the impact of ocean depth (0, 500, 1000, and 1500 m) on the ion interaction processes in concrete nanopores using molecular dynamics simulations. At the portlandite interface, the local structural and kinetic characteristics of ions and water molecules are examined. The findings show that the portlandite surface hydrophilicity is unaffected by increasing depth. The density profile and coordination number of ions alter as depth increases, and the diffusion speed noticeably decreases. The main cause of the ions' reduced diffusion velocity is expected to be the low temperature. This work offers a thorough understanding of the cement hydration products' microstructure in deep sea, which may help explain why cement-based underwater infrastructure deteriorates over time. [ABSTRACT FROM AUTHOR]

The paper examines the global scientific literature on Molecular Docking (MD). MDis a keyapproachusedinbioinformatics to identify and developnovel compounds towards drug discovery. This study uses the bibliometric method to analyze scientific data covered in the Scopus database from 2013 to 2022 using MS Excel, R Studio, andVOS Viewer software. A total of 12173 documents on Molecular Docking were retrieved and considered for the study. The paper provides an in-depth evaluation of the research output of MD. The research found that MuthuS.was a most prolific author in MD scientific research, with 98 publications that received 1481 global citations. The most productivecountries in this field areIndia (4020 publications), followedbyChina (2675 publications), Saudi Arabia (1362 publications) and Egypt (1071 publications). The hot keywords in MD research are molecular modelling, molecular docking simulation, unclassified drug and controlled study, but Molecular Docking is the burning author keyword. The finding also shows that the publications are increasing consistently from 2013 onwards. Most articles have been published in the 'Journal of Molecular Structure'. As it is an emerging and a trending topic, it has scope for further studies. This study will benefit future researchers and practitioners worldwide in understanding the research pattern on MD and identifying the other key areas related to the topic. [ABSTRACT FROM AUTHOR]