Small molecule inhibitor DDQ-treated hippocampal neuronal cells show improved neurite outgrowth and synaptic branching

The process of neurite outgrowth and branching is a crucial aspect of neuronal development and regeneration.Axons and dendrites,sometimes referred to as neurites,are extensions of a neuron's cellular body that are used to start networks.Here we explored the effects of diethyl(3,4-dihydroxyphenethylamino)(quinolin-4-yl)methylphosphonate(DDQ)on neurite developmental features in HT22 neuronal cells.In this work,we examined the protective effects of DDQ on neuronal processes and synaptic outgrowth in differentiated HT22cells expressing mutant Tau(mTau)cDNA.To investigate DDQ chara cteristics,cell viability,biochemical,molecular,western blotting,and immunocytochemistry were used.Neurite outgrowth is evaluated through the segmentation and measurement of neural processes.These neural processes can be seen and measured with a fluorescence microscope by manually tracing and measuring the length of the neurite growth.These neuronal processes can be observed and quantified with a fluorescent microscope by manually tracing and measuring the length of the neuronal HT22.DDQ-treated mTau-HT22 cells(HT22 cells transfected with cDNA mutant Tau)were seen to display increased levels of synaptophysin,MAP-2,andβ-tubulin.Additionally,we confirmed and noted reduced levels of both total and p-Tau,as well as elevated levels of microtubule-associated protein 2,β-tubulin,synaptophysin,vesicular acetylcholine transporter,and the mitochondrial biogenesis protein-pe roxisome prolife rator-activated receptor-gamma coactivator-1α.In mTa u-expressed HT22 neurons,we observed DDQ enhanced the neurite characteristics and improved neurite development through increased synaptic outgrowth.Our findings conclude that mTa u-HT22(Alzheimer's disease)cells treated with DDQ have functional neurite developmental chara cteristics.The key finding is that,in mTa u-HT22 cells,DDQ preserves neuronal structure and may even enhance nerve development function with mTa u inhibition.

Cold cesium molecules produced directly in a magneto-optical trap

We report on the observation of ultracold ground electric-state cesium molecules produced directly in a magneto-optical trap with a good signal-to-noise ratio. These molecules arise from the photoassociation of magneto-optical trap lasers and they are detected by resonantly enhanced multiphoton ionization technology. The production rate of ultracold cesium molecules is up to 4× 10^4 s-1. We measure the characteristic time of the ground electric-state cesium molecules generated in the experiment and investigate the Cs2＋ molecular ion intensity as a function of the trapping laser intensity and the ionization pulse laser energy. We conclude that the production of cold cesium molecules may be enhanced by using appropriate experimental parameters, which is useful for future experiments involving the production and trapping of ultracold ground electric-state molecules.

Kinetics of Hydrogen Molecules in MAGNUM-PSI

Results from simulations of plasma and neutrals under conditions predictively characterizing the detached plasma regime in the linear machine MAGNUM-PSI are presented. The relaxation of the vibrationally excited hydrogen molecules is investigated in order to establish a relation between their relaxation and dwell times, and the role of the varions mechanisms of the molecular vibrational kinetics. Tile results obtained show that the individual vibrational states have to be inclllded in the transport code for neutrals as distinct species, since the relaxation time of tile vibrational states is sufficiently longer than the typical dwell time of hydrogen molecules in the detached plasma region. The parameters of plasma and neutrals are affected by the transport of the vibrationally excited hydrogen lnolecnles. Furthermore. the rate of molecular reconlbination is overestimated by a factor of - 5 provided that the transport of ilydrogen molecules only in their ground vibrational state is considered. The role of the various processes of vibrational kinetics is studied. The vibrational excitation through singlet electronic states ires a strong influence on the molecular densities for levels with vibrational quantum numbers v≥ 5. Vibration-vibration （V-V） collisions between vibrationally excited hydrogen molecules and vibration-translation （V-T） collisions between vibrationally excited hydrogen molecules and ground state molecules and atoms are of nlinor importance in MAGNUM-PSI.

Electromagnetically Induced Transparency Using a Artificial Molecule in Circuit Quantum Electrodynamics

Electromagnetically induced transparency (EIT) having wide applications in quantum optics and nonlinear optics is explored ordinarily in various atomic systems. In this paper we present a theoretical study of EIT using supercon- ducting circuit with a V-type artificial molecule constructed by two Josephson charge qubits coupled each other through a large capacitor. In our theoretical model we make a steady state approximation and obtain the analytical expressions of the complex susceptibility for the artificial system via the density matrix formalism. The complex susceptibility has additional dependence on the qubit parameters and hence can be tuned to a certain extent.

Inverse Molecule Design with Invertible Neural Networks as Generative Models

Using neural networks for supervised learning means learning a function that maps input x to output y. However, in many applications, the inverse learning is also wanted, i.e., inferring y from x, which requires invertibility of the learning. Since the dimension of input is usually much higher than that of the output, there is information loss in the forward learning from input to output. Thus, creating invertible neural networks is a difficult task. However, recent development of invertible learning techniques such as normalizing flows has made invertible neural networks a reality. In this work, we applied flow-based invertible neural networks as generative models to inverse molecule design. In this context, the forward learning is to predict chemical properties given a molecule, and the inverse learning is to infer the molecules given the chemical properties. Trained on 100 and 1000 molecules, respectively, from a benchmark dataset QM9, our model identified novel molecules that had chemical property values well exceeding the limits of the training molecules as well as the limits of the whole QM9 of 133,885 molecules, moreover our generative model could easily sample many molecules (x values) from any one chemical property value (y value). Compared with the previous method in the literature that could only optimize one molecule for one chemical property value at a time, our model could be trained once and then be sampled any multiple times and for any chemical property values without the need of retraining. This advantage comes from treating inverse molecule design as an inverse regression problem. In summary, our main contributions were two: 1) our model could generalize well from the training data and was very data efficient, 2) our model could learn bidirectional correspondence between molecules and their chemical properties, thereby offering the ability to sample any number of molecules from any y values. In conclusion, our findings revealed the efficiency and effectiveness of using invertible neural networks as generative models in inverse molecule design.

Critical Solvation Structures Arrested Active Molecules for Reversible Zn Electrochemistry

Aqueous Zn-ion batteries(AZIBs)have attracted increasing attention in next-generation energy storage systems due to their high safety and economic.Unfortunately,the side reactions,dendrites and hydrogen evolution effects at the zinc anode interface in aqueous electrolytes seriously hinder the application of aqueous zinc-ion batteries.Here,we report a critical solvation strategy to achieve reversible zinc electrochemistry by introducing a small polar molecule acetonitrile to form a“catcher”to arrest active molecules(bound water molecules).The stable solvation structure of[Zn(H_(2)O)_(6)]^(2+)is capable of maintaining and completely inhibiting free water molecules.When[Zn(H_(2)O)_(6)]^(2+)is partially desolvated in the Helmholtz outer layer,the separated active molecules will be arrested by the“catcher”formed by the strong hydrogen bond N-H bond,ensuring the stable desolvation of Zn^(2+).The Zn||Zn symmetric battery can stably cycle for 2250 h at 1 mAh cm^(-2),Zn||V_(6)O_(13) full battery achieved a capacity retention rate of 99.2%after 10,000 cycles at 10 A g^(-1).This paper proposes a novel critical solvation strategy that paves the route for the construction of high-performance AZIBs.

Development of small molecule drugs targeting immune checkpoints

Immune checkpoint inhibitors(ICIs)are used to relieve and refuel anti-tumor immunity by blocking the interaction,transcription,and translation of co-inhibitory immune checkpoints or degrading co-inhibitory immune checkpoints.Thousands of small molecule drugs or biological materials,especially antibody-based ICIs,are actively being studied and antibodies are currently widely used.Limitations,such as anti-tumor efficacy,poor membrane permeability,and unneglected tolerance issues of antibody-based ICIs,remain evident but are thought to be overcome by small molecule drugs.Recent structural studies have broadened the scope of candidate immune checkpoint molecules,as well as innovative chemical inhibitors.By way of comparison,small molecule drug-based ICIs represent superior oral bioavailability and favorable pharmacokinetic features.Several ongoing clinical trials are exploring the synergetic effect of ICIs and other therapeutic strategies based on multiple ICI functions,including immune regulation,anti-angiogenesis,and cell cycle regulation.In this review we summarized the current progression of small molecule ICIs and the mechanism underlying immune checkpoint proteins,which will lay the foundation for further exploration.

Inetetamab combined with pyrotinib and chemotherapy in the treatment of breast cancer brain metastasis: A case report

BACKGROUND Breast cancer brain metastasis(BCBM)is an advanced breast disease that is difficult to treat and is associated with a high risk of death.Patient prognosis is usually poor,with reduced quality of life.In this context,we report the case of a patient with HER-2-positive BCBM treated with a macromolecular mAb(ine-tetamab)combined with a small molecule tyrosine kinase inhibitor(TKI).CASE SUMMARY The patient was a 58-year-old woman with a 12-year history of type 2 diabetes.She was compliant with regular insulin treatment and had good blood glucose control.The patient was diagnosed with invasive carcinoma of the right breast(T3N1M0 stage IIIa,HER2-positive type)through aspiration biopsy of the ipsilateral breast due to the discovery of a breast tumor in February 2019.Immunohistochemistry showed ER(-),PR(-),HER-2(3+),and Ki-67(55-60%+).Preoperative neoadjuvant chemotherapy,i.e.,the AC-TH regimen(epirubicin,cyclophosphamide,docetaxel-paclitaxel,and trastuzumab),was administered for 8 cycles.She underwent modified radical mastectomy of the right breast in November 2019 and received tocilizumab targeted therapy for 1 year.Brain metastasis was found 9 mo after surgery.She underwent brain metastasectomy in August 2020.Immunohistochemistry showed ER(-)and PR.(-),HER-2(3+),and Ki-67(10-20%+).In November 2020,the patient experienced headache symptoms.After an examination,tumor recurrence in the original surgical region of the brain was observed,and the patient was treated with inetetamab,pyrotinib,and capecitabine.Whole-brain radiotherapy was recommended.The patient and her family refused radiotherapy for personal reasons.In September 2021,a routine examination revealed that the brain tumor was considerably larger.The original systemic treatment was continued and combined with intensity-modulated radiation therapy for brain metastases,followed by regular hospitalization and routine examinations.The patient’s condition is generally stable,and she has a relatively high quality of life.This case report demonstrates that in patients with BCBM and resistance to trastuzumab,inetetamab combined with pyrotinib and chemotherapy can prolong survival.CONCLUSION Inetetamab combined with small molecule TKI drugs,chemotherapy and radiation may be an effective regimen for maintaining stable disease in patients with BCBM.

Magnetoelastic Instability in Ring-Shaped Molecule Magnets with Next-Nearest Neighbor Coupling

In considering next-nearest neighbor （NNN） coupling, we numerically investigate the magnetoelastic instability in ring-shaped mesoscopic antiferromagnetic Heisenberg spin 1/2 systems with spin-phonon interaction. The results indicate that, for antiferromagnetic NNN coupling J2, there may be a critical value J2^c, at which the ground state is dimerized for arbitrary lattice spring constant and beyond and below which the magnetoelastic instability behavior is different from each other. The values of J2^c are irrelevant to the system size. For ferromagnetic NNN coupling, only continuous transition is present from dimerized phase to uniform phase as lattice spring constant is increased.

Interaction and local magnetic moments of metal phthalocyanine and tetraphenylporphyrin molecules on noble metal surfaces

In order to understand the Kondo effect observed in molecular systems, first-principles calculations have been widely used to predict the ground state properties of molecules on metal substrates. In this work, the interaction and the local magnetic moments of magnetic molecules （3d-metal phthalocyanine and tetraphenylporphyrin molecules） on noble metal surfaces are investigated based on the density functional theory. The calculation results show that the dz2 orbital of the transition metal atom of the molecule plays a dominant role in the molecule-surface interaction and the adsorption energy exhibits a simple declining trend as the adsorption distance increases. In addition, the Au（111） surface generally has a weak interaction with the adsorbed molecule compared with the Cu（ll 1） surface and thus serves as a better candidate substrate for studying the Kondo effect. The relation between the local magnetic moment and the Coulomb interaction U is examined by carrying out the GGA＋U calculation according to Dudarev＇s scheme. We find that the Coulomb interaction is essential for estimating the local magnetic moment in molecule-surface systems, and we suggest that the reference values of parameter U are 2 eV for Fe and 2-3 eV for Co.

Deterministic Generation of Quantum State Transfer Between Spatially Separated Single Molecule Magnets

We propose a new scheme for realizing deterministic quantum state transfer （QST） between two spatially separated single molecule magnets （SMMs） with the framework of cavity quantum eleetrodynamics （QED）. In the present scheme, two SMMs are trapped in two spatially separated optical cavities coupled by an optical fiber. Through strictly numerically simulating, we demonstrate that our scheme is robust with respect to the SMMs＇ spontaneous decay and fiber loss under the conditions of dispersive SMMs-field interaction and strong coupling of cavity fiber. In addition, we also discuss the influence of photon leakage out of cavities and show that our proposal is good enough to demonstrate the generation of QST with high fidelity utilizing the current experimental technology. The present investigation provides research opportunities for realizing QST between solid-state qubits and may result in a substantial impact on the progress of solid-state-based quantum communications network.

Magnetic anisotropy in 5d transition metal-porphyrin molecules

Single molecule magnets(SMMs) with large magnetic anisotropy energy(MAE) have great potential applications in magnetic recording.Using the first-principles calculations,we investigate the MAE of 5 d transition metal-porphyrin-based SMMs by using the PBE and PBE+U with different U values,respectively.The results indicate that W-P,Re-P,Os-P,and Ir-P possess the considerably large MAE among 5 d TM-P SMMs.Furthermore,the MAE of 5 d TM-P can be facilely manipulated by tensile strain.The reduction of the absolute value of MAE for Ir-P molecule caused by tensile strain makes it easier to implement the writing operation.The decreasing of the occupation number of minority-spin channels of Ir-d_(x^(2)-y^(2)) orbital leads the MAE to decrease when the tensile strain increases.

Influence of nickel(II) oxide surface magnetism on molecule adsorption: A first-principles study

The influence of the magnetism of transition metal oxide,nickel(II)oxide(NiO),on its surface reactivity and the dependence of surface reactivity on surface orientation and reactant magnetism were studied by density functional theory plus U calculations.We considered five different antiferromagnetically ordered structures and one ferromagnetically ordered structure,NiO(001)and Ni(011)surfaces,paramagnetic molecule NO,and nonparamagnetic molecule CO.The calculations showed that the dependence of surface energies on magnetism was modest,ranging from49to54meV/?2for NiO(001)and from162to172meV/?2for NiO(011).On NiO(001),both molecules preferred the top site of the Ni cation exclusively for all NiO magnetic structures considered,and calculated adsorption energies ranged from?0.33to?0.37eV for CO and from?0.42to?0.46eV for NO.On NiO(011),both molecules preferred the bridge site of two Ni cations irrespective of the NiO magnetism.It was found that rather than the long‐range magnetism of bulk NiO,the local magnetic order of two coordinated Ni cations binding to the adsorbed molecule had a pronounced influence on adsorption.The calculated NO adsorption energy at the(↑↓)bridge sites ranged from?0.99to?1.05eV,and become stronger at the(↑↑)bridge sites with values of?1.21to?1.30eV.For CO,although the calculated adsorption energies at the(↑↓)bridge sites(?0.73to?0.75eV)were very close to those at the(↑↑)bridge sites(?0.71to?0.72eV),their electron hybridizations were very different.The present work highlights the importance of the local magnetic order of transition metal oxides on molecular adsorption at multi‐fold sites.

Formation of high-density cold molecules via electromagnetic trap

Preparation and control of cold molecules are advancing rapidly, motivated by many exciting applications ranging from tests of fundamental physics to quantum information processing. Here, we propose a trapping scheme to create high-density cold molecular samples by using a combination of electric and magnetic fields. In our theoretical analysis and numerical calculations, a typical alkaline-earth monofluoride, MgF, is used to test the feasibility of our proposal.A cold MgF molecular beam is first produced via an electrostatic Stark decelerator and then loaded into the proposed electromagnetic trap, which is composed of an anti-Helmholtz coil, an octupole, and two disk electrodes. Following that,a huge magnetic force is applied to the molecular sample at an appropriate time, which enables further compressing of the spatial distribution of the cold sample. Molecular samples with both higher number density and smaller volume are quite suitable for the laser confinement and other molecular experiments such as cold collisions in the next step.

Microwave-mediated magneto-optical trap for polar molecules

Realizing a molecular magneto-optical trap has been a dream for cold molecular physicists for a long time. However,due to the complex energy levels and the small effective Lande g-factor of the excited states, the traditional magneto-optical trap（MOT） scheme does not work very well for polar molecules. One way to overcome this problem is the switching MOT,which requires very fast switching of both the magnetic field and the laser polarizations. Switching laser polarizations is relatively easy, but fast switching of the magnetic field is experimentally challenging. Here we propose an alternative approach, the microwave-mediated MOT, which requires a slight change of the current experimental setup to solve the problem. We calculate the MOT force and compare it with the traditional MOT and the switching MOT scheme. The results show that we can operate a good MOT with this simple setup.

Interaction Energy Prediction of Organic Molecules using Deep Tensor Neural Network

The interaction energy of two molecules system plays a critical role in analyzing the interacting effect in molecular dynamic simulation.Since the limitation of quantum mechanics calculating resources,the interaction energy based on quantum mechanics can not be merged into molecular dynamic simulation for a long time scale.A deep learning framework,deep tensor neural network,is applied to predict the interaction energy of three organic related systems within the quantum mechanics level of accuracy.The geometric structure and atomic types of molecular conformation,as the data descriptors,are applied as the network inputs to predict the interaction energy in the system.The neural network is trained with the hierarchically generated conformations data set.The complex tensor hidden layers are simplified and trained in the optimization process.The predicted results of different molecular sys tems indica te that deep t ensor neural net work is capable to predic t the interaction energy with 1 kcal/mol of the mean absolute error in a relatively short time.The prediction highly improves the efficiency of interaction energy calculation.The whole proposed framework provides new insights to introducing deep learning technology into the interaction energy calculation.

Controllable Tunneling of Light through a Quantum-Dot-Molecule Dielectric Film via Electromagnetically Induced Transparency

Since discrete multilevel transitions of quantum-dot molecules driven by external electromagnetic fields can exhibit quantum coherence effects, such an optical characteristic can be utilized to control propagation of electromagnetic wave through a quantum-dot molecule dielectric film. Since inner-dot tunneling in quantum-dot molecules can be controlled by a gate voltage, destructive quantum coherence among multilevel transitions in quantum-dot molecule would give rise to EIT (electromagnetically induced transparency). In this report, we shall investigate controllable on- and off-resonance tunneling effects of an incident electromagnetic wave through such a quan-tum-dot-molecule dielectric film, of which the optical response is tuned by the switchable gate voltage. We have found from the theoretical mechanism that a high gate voltage can cause the EIT phenomenon of quan-tum-dot-molecule systems, and under the condition of on-resonance light tunneling through the thin film, the probe field will propagation without loss if the probe frequency detuning is zero. By taking advantage of these effects sensitive to the tunable gate voltage, such quantum coherence would be inte-grated in certain photonic structures, and some devices such as photonic switching and transistors can be designed. Transient evolution of optical characteristics in the quantum-dot-molecule dielectric film (once the tunable gate voltage is turned on or off) is also considered in this report.

Reinforcement Learning of Molecule Optimization with Bayesian Neural Networks

Creating new molecules with desired properties is a fundamental and challenging problem in chemistry. Reinforcement learning (RL) has shown its utility in this area where the target chemical property values can serve as a reward signal. At each step of making a new molecule, the RL agent learns selecting an action from a list of many chemically valid actions for a given molecule, implying a great uncertainty associated with its learning. In a traditional implementation of deep RL algorithms, deterministic neural networks are typically employed, thus allowing the agent to choose one action from one sampled action at each step. In this paper, we proposed a new strategy of applying Bayesian neural networks to RL to reduce uncertainty so that the agent can choose one action from a pool of sampled actions at each step, and investigated its benefits in molecule design. Our experiments suggested the Bayesian approach could create molecules of desirable chemical quality while maintained their diversity, a very difficult goal to achieve in machine learning of molecules. We further exploited their diversity by using them to train a generative model to yield more novel drug-like molecules, which were absent in the training molecules as we know novelty is essential for drug candidate molecules. In conclusion, Bayesian approach could offer a balance between exploitation and exploration in RL, and a balance between optimization and diversity in molecule design.

The Gravito-Chemical Bond and Structures of Hydrocarbons and Water Molecules with Real Magnetic Charges

Experimental and theoretical studies of the author (period: 1968-present) have shown that true sources of the magnetic field are magnetic fundamental particles (magnetic charges), and not moving electrons. The main reason for ignoring real magnetic charges, as well as true antielectrons in physical science is the hard conditions for confinement of these particles in atoms and substances, which is radically different from the confinement of electrons. Magnetic charges together with electric charges form the shells atoms which are electromagnetic, and not electronic. Namely, electromagnetic shells are sources of gravitational field which is a vortex electromagnetic field and described by the vortex rot [E - H]. Depending on the state polarization of vortex vectors rot [E - H] in compositions of atomic gravitational fields it is subdivided into paragravitational (PGF) and ferrogravitational fields (FGF). The overwhelming number of atoms emits PGF. Between the masses (bodies, atoms, nucleons and others) emitting PGF areas of negative gravitational “Dark Energy” are realized the forces of which press the masses towards each other. Namely, the compression of atoms by the forces of paragravitational “Dark Energy” underlies the chemical bond. The exception here is the ionic bond in ionic crystals. However, all ions have electromagnetic shells that generate the gravitational field. Consequently, ionic bonding is a relatively rare addition to gravito-chemical bond processes. The direct gravito-chemical bond of carbon atoms with hydrogen (1H) is physically forbidden due to the manifestation of the effect of ferrogravitational levitation between them and the repulsion of atoms from each other. Paradoxically, but all existing ideas about the structural device of hydrocarbons are based on such physically forbidden bonds which, moreover, must be realized through ionic bonds which in reality do not exist. Chemical bonding of carbon and hydrogen atoms to form hydrocarbons molecules is possible only if the hydrogen atoms are in the molecular form (1H2). In the composition of water, within the framework of the chemical formula H2O, two stable isomorphic molecular structures are formed. The chemical bond in the first structure is similar to the hydrocarbon scenario described above, i.e. in the process of combining paragravitational oxygen with a hydrogen molecule 1H2. The second molecular structure in water is formed under conditions of ferropolarization of the gravitational field of oxygen atoms under the influence of FGF of neighboring 1H atoms. In this case, the chemical bond is realized under the conditions of ferropolarization of the vortex vectors rot [E - H] of the gravitational fields of all atoms in the molecule and the co-directionality of them vectors Pfp ferropolarization. The gravito-physical properties of the presented molecular structures in the composition of water make it possible to name them, respectively, as heavy and light clusters.

Role of self-assembled molecules’anchoring groups for surface defect passivation and dipole modulation in inverted perovskite solar cells

Inverted perovskite solar cells have gained prominence in industrial advancement due to their easy fabrication,low hysteresis effects,and high stability.Despite these advantages,their efficiency is currently limited by excessive defects and poor carrier transport at the perovskite-electrode interface,particularly at the buried interface between the perovskite and transparent conductive oxide(TCO).Recent efforts in the perovskite community have focused on designing novel self-assembled molecules(SAMs)to improve the quality of the buried interface.However,a notable gap remains in understanding the regulation of atomic-scale interfacial properties of SAMs between the perovskite and TCO interfaces.This understanding is crucial,particularly in terms of identifying chemically active anchoring groups.In this study,we used the star SAM([2-(9H-carbazol-9-yl)ethyl]phosphonic acid)as the base structure to investigate the defect passivation effects of eight common anchoring groups at the perovskite-TCO interface.Our findings indicate that the phosphonic and boric acid groups exhibit notable advantages.These groups fulfill three key criteria:they provide the greatest potential for defect passivation,exhibit stable adsorption with defects,and exert significant regulatory effects on interface dipoles.Ionized anchoring groups exhibit enhanced passivation capabilities for defect energy levels due to their superior Lewis base properties,which effectively neutralize local charges near defects.Among various defect types,iodine vacancies are the easiest to passivate,whereas iodine-substituted lead defects are the most challenging to passivate.Our study provides comprehensive theoretical insights and inspiration for the design of anchoring groups in SAMs,contributing to the ongoing development of more efficient inverted perovskite solar cells.