Advancing teeth whitening efficacy via dual-phototherapeutic strategy incorporating molybdenum disulfide embedded in carrageenan hydrogel for dental healthcare.

Teeth discoloration poses a widespread challenge in dental health across various regions. Conventional teeth whitening methods often result in enamel deterioration and soft tissue harm due to the utilization of incompatible whitening agents and continuous intense light exposure. Here, we propose an effective phototherapy technique for teeth whitening, employing pathways of energy transition through intersystem crossing. The integration of MoS2 nanosheets into carrageenan gel (MoS2 NSs@Carr) facilitates both photothermal-hyperthermia and the generation of reactive oxygen species (ROS) through photocatalytic processes. The efficacy of ROS generation by the phototherapeutic MoS2 NSs@Carr on teeth whitening in all scenarios. This approach ensures comprehensive teeth whitening by eliminating deep-seated stains on the teeth while preserving structural integrity and avoiding any tissue toxicity. This research highlights the efficacy of the phototherapeutic MoS2 NSs@Carr for dental whitening and underscores the potential of exploring nanostructures based on MoS2 NSs for treating oral ailments.

Proton Collective Quantum Tunneling Induces Anomalous Thermal Conductivity of Ice under Pressure.

Proton tunneling is believed to be nonlocal in ice, but its range has been shown to be limited to only a few molecules. Here, we measured the thermal conductivity of ice under pressure up to 50 GPa and found it increases with pressure until 20 GPa but decreases at higher pressures. We attribute this nonmonotonic thermal conductivity to the collective tunneling of protons at high pressures, supported by large-scale quantum molecular dynamics simulations. The collective tunneling loops span several picoseconds in time and are as large as nanometers in space, which match the phonon periods and wavelengths, leading to strong phonon scattering at high pressures. Our results show direct evidence of global quantum motion existing in high-pressure ice and provide a new perspective to understanding the coupling between phonon propagation and atomic tunneling.

Electricity generated by upstream proton diffusion in two-dimensional nanochannels.

The movement of ions along the pressure-driven water flow in narrow channels, known as downstream ionic transport, has been observed since 1859 to induce a streaming potential and has enabled the creation of various hydrovoltaic devices. In contrast, here we demonstrate that proton movement opposing the water flow in two-dimensional nanochannels of MXene/poly(vinyl alcohol) films, termed upstream proton diffusion, can also generate electricity. The infiltrated water into the channel causes the dissociation of protons from functional groups on the channel surface, resulting in a high proton concentration inside the channel that drives the upstream proton diffusion. Combined with the particularly sluggish water diffusion in the channels, a small water droplet of 5 µl can generate a voltage of ~400 mV for over 330 min. Benefiting from the ultrathin and flexible nature of the film, a wearable device is built for collecting energy from human skin sweat.

The Role of Transition Metal Versus Coordination Mode in Single-Atom Catalyst for Electrocatalytic Sulfur Reduction Reaction.

Electrocatalytic sulfur reduction reaction (SRR) is emerging as an effective strategy to combat the polysulfide shuttling effect, which remains a critical factor impeding the practical application of the Li-S battery. Single-atom catalyst (SAC), one of the most studied catalytic materials, has shown considerable potential in addressing the polysulfide shuttling effect in a Li-S battery. However, the role played by transition metal vs coordination mode in electrocatalytic SRR is trial-and-error, and the general understanding that guides the synthesis of the specific SAC with desired property remains elusive. Herein, we use first-principles calculations and machine learning to screen a comprehensive data set of graphene-based SACs with different transition metals, heteroatom doping, and coordination modes. The results reveal that the type of transition metal plays the decisive role in SAC for electrocatalytic SRR, rather than the coordination mode. Specifically, the 3d transition metals exhibit admirable electrocatalytic SRR activity for all of the coordination modes. Compared with the reported N3C1 and N4 coordinated graphene-based SACs covering 3d, 4d, and 5d transition metals, the proposed para-MnO2C2 and para-FeN2C2 possess significant advantages on the electrocatalytic SRR, including a considerably low overpotential down to 1 mV and reduced Li2S decomposition energy barrier, both suggesting an accelerated conversion process among the polysulfides. This study may clarify some understanding of the role played by transition metal vs coordination mode for SAC materials with specific structure and desired catalytic properties toward electrocatalytic SRR and beyond.

How I diagnose and treat organizing pneumonia in hematopoietic cell transplant recipients.

Organizing pneumonia (OP) is a known non-infectious pulmonary complication following allogeneic hematopoietic cell transplant (HCT) and represents a significant risk factor for non-relapse mortality in HCT recipients. Unlike bronchiolitis obliterans syndrome, it is not universally acknowledged as a distinctive pulmonary manifestation of chronic-graft-versus-host disease (cGVHD) and therefore, its diagnostic criteria and management approach is lacking. Given it shared similar clinical features, radiological and histological findings to OP in non-HCT population, the diagnostic approach and treatment strategy for OP in HCT recipient is largely adapted from the non-HCT population. In this paper, we aim to enhance the understanding of OP within the context of cGVHD following HCT, distinguish its clinical features and treatment strategy from non-HCT counterpart, thereby reinforcing its recognition as a pulmonary manifestation of GVHD. We will propose the diagnostic criteria and outline our approach in diagnosis and treatment strategy, highlighting the potential challenges that may arise in each process. Finally, we will discuss knowledge gaps in this field and identify the area of need for future research.

Efficient and Accurate Estimation of Electronic Polarization Energies for Organic Semiconductors: An Embedding Charge Quantum Mechanics/Continuum Dielectric Model.

Electronic polarization plays a pivotal role in determining the molecular energy levels of organic semiconductors (OSCs) in the condensed phase. However, accurate estimation of the electronic polarization energy is a challenging task due to the intricate imbalance between the precision and efficiency. In this work, we have developed an embedding charge quantum mechanics/continuum dielectric (EC-QM/CD) model, which enables quantitative evaluation of the ionization potential (IP), electron affinity (EA), and polarization energy in both crystalline and amorphous solids for OSCs. The benchmark calculations on both p-type OSCs of oligoacenes and n-type OSCs of A-D-A small-molecule acceptors show that the values of IP, EA, and polarization energy obtained by EC-QM/CD are in good accordance with the experimental measurements or the results by high-precision methods, while the computational costs are substantially reduced. Given its balance between the accuracy and efficiency, the EC-QM/CD model exhibits considerable potential to broaden the applications in the field of OSCs, for instance, high-throughput screening by using solid-state energy levels or polarization energies as critical descriptors.

Developing a Differentiable Long-Range Force Field for Proteins with E(3) Neural Network-Predicted Asymptotic Parameters.

Accurately describing long-range interactions is a significant challenge in molecular dynamics (MD) simulations of proteins. High-quality long-range potential is also an important component of the range-separated machine learning force field. This study introduces a comprehensive asymptotic parameter database encompassing atomic multipole moments, polarizabilities, and dispersion coefficients. Leveraging active learning, our database comprehensively represents protein fragments with up to 8 heavy atoms, capturing their conformational diversity with merely 78,000 data points. Additionally, the E(3) neural network (E3NN) is employed to predict the asymptotic parameters directly from the local geometry. The E3NN models demonstrate exceptional accuracy and transferability across all asymptotic parameters, achieving an R2 of 0.999 for both protein fragments and 20 amino acid dipeptide test sets. The long-range electrostatic and dispersion energies can be obtained using the E3NN-predicted parameters, with an error of 0.07 and 0.02 kcal/mol, respectively, when compared to symmetry-adapted perturbation theory (SAPT). Therefore, our force fields demonstrate the capability to accurately describe long-range interactions in proteins, paving the way for next-generation protein force fields.

Moxibustion for declined cardiorespiratory fitness of apparently healthy older adults: A study protocol for a randomized controlled trial.

BACKGROUND: Aging and age-related declines lead to varying degrees of decreased cardiorespiratory fitness (CRF) in apparently healthy older adults. Exercise training, the primary approach for enhancing CRF, encounters several constraints when used with elderly individuals. Existing evidence implies that moxibustion might enhance the CRF of older adults. However, clinical research in this area still needs to be improved. METHODS: This study will employ a randomized, assessor-blinded, controlled trial design involving 126 eligible participants. These participants will be stratified and randomly assigned to one moxibustion group, one sham moxibustion group, and one blank control group. Acupoints of bilateral Zusanli (ST36), Shenque (CV8), and Guanyuan (CV4) are selected for both real and sham moxibustion groups. The treatment will last 60 min per session, 5 sessions a week for 12 weeks. The blank control group will not receive any intervention for CRF improvement. Primary outcomes will be the mean change in peak oxygen uptake (VO2peak), anaerobic threshold (AT), and serum central carbon metabolites (CCB) from the baseline to observation points. Secondary outcome measures involve the six-minute walk distance (6MWD), the Short Form 36 Health Survey (SF-36), and the Qi and Blood Status Questionnaire (QBSQ). Outcome assessments will be conducted at weeks 4, 8, 12, and 24 as part of the follow-up. Adverse events will be assessed at each visit. DISCUSSION: This trial can potentially ascertain moxibustion's effectiveness and safety in enhancing CRF among apparently healthy older adults. TRAIL REGISTRATION: ChiCTR, ChiCTR2300070303. Registered on April 08, 2023.

Biocompatible aggregation-induced emission active polyphosphate-manganese nanosheets with glutamine synthetase-like activity in excitotoxic nerve cells.

Glutamine synthetase (GS) is vital in maintaining ammonia and glutamate (Glu) homeostasis in living organisms. However, the natural enzyme relies on adenosine triphosphate (ATP) to activate Glu, resulting in impaired GS function during ATP-deficient neurotoxic events. To date, no reports demonstrate using artificial nanostructures to mimic GS function. In this study, we synthesize aggregation-induced emission active polyP-Mn nanosheets (STPE-PMNSs) based on end-labeled polyphosphate (polyP), exhibiting remarkable GS-like activity independent of ATP presence. Further investigation reveals polyP in STPE-PMNSs serves as phosphate source to activate Glu at low ATP levels. This self-feeding mechanism offers a significant advantage in regulating Glu homeostasis at reduced ATP levels in nerve cells during excitotoxic conditions. STPE-PMNSs can effectively promote the conversion of Glu to glutamine (Gln) in excitatory neurotoxic human neuroblastoma cells (SH-SY5Y) and alleviate Glu-induced neurotoxicity. Additionally, the fluorescence signal of nanosheets enables precise monitoring of the subcellular distribution of STPE-PMNSs. More importantly, the intracellular fluorescence signal is enhanced in a conversion-responsive manner, allowing real-time tracking of reaction progression. This study presents a self-sustaining strategy to address GS functional impairment caused by ATP deficiency in nerve cells during neurotoxic events. Furthermore, it offers a fresh perspective on the potential biological applications of polyP-based nanostructures.

Low-latency gravitational wave alert products and their performance at the time of the fourth LIGO-Virgo-KAGRA observing run.

Multimessenger searches for binary neutron star (BNS) and neutron star-black hole (NSBH) mergers are currently one of the most exciting areas of astronomy. The search for joint electromagnetic and neutrino counterparts to gravitational wave (GW)s has resumed with ALIGO's, AdVirgo's and KAGRA's fourth observing run (O4). To support this effort, public semiautomated data products are sent in near real-time and include localization and source properties to guide complementary observations. In preparation for O4, we have conducted a study using a simulated population of compact binaries and a mock data challenge (MDC) in the form of a real-time replay to optimize and profile the software infrastructure and scientific deliverables. End-toend performance was tested, including data ingestion, running online search pipelines, performing annotations, and issuing alerts to the astrophysics community. We present an overview of the low-latency infrastructure and the performance of the data products that are now being released during O4 based on the MDC. We report the expected median latency for the preliminary alert of full bandwidth searches (29.5 s) and show consistency and accuracy of released data products using the MDC. We report the expected median latency for triggers from early warning searches (-3.1 s), which are new in O4 and target neutron star mergers during inspiral phase. This paper provides a performance overview for LIGO-Virgo-KAGRA (LVK) low-latency alert infrastructure and data products using theMDCand serves as a useful reference for the interpretation of O4 detections.

Discovering unknown Madagascar biodiversity: integrative taxonomy of raft spiders (Pisauridae: Dolomedes).

Madagascar is a global biodiversity hotspot, but its biodiversity continues to be underestimated and understudied. Of raft spiders, genus Dolomedes Latreille, 1804, literature only reports two species on Madagascar. Our single expedition to humid forests of eastern and northern Madagascar, however, yielded a series of Dolomedes exemplars representing both sexes of five morphospecies. To avoid only using morphological diagnostics, we devised and tested an integrative taxonomic model for Dolomedes based on the unified species concept. The model first determines morphospecies within a morphometrics framework, then tests their validity via species delimitation using COI. It then incorporates habitat preferences, geological barriers, and dispersal related traits to form hypotheses about gene flow limitations. Our results reveal four new Dolomedes species that we describe from both sexes as Dolomedes gregoric sp. nov., D. bedjanic sp. nov., D. hydatostella sp. nov., and D. rotundus sp. nov. The range of D. kalanoro Silva & Griswold, 2013, now also known from both sexes, is expanded to eastern Madagascar. By increasing the known raft spider diversity from one valid species to five, our results merely scratch the surface of the true Dolomedes species diversity on Madagascar. Our integrative taxonomic model provides the framework for future revisions of raft spiders anywhere.

Band Structure Engineering and Orbital Orientation Control Constructing Dual Active Sites for Efficient Sulfur Redox Reaction.

The kinetics difference among multistep electrochemical processes leads to the accumulation of soluble polysulfides and thus shuttle effect in lithium-sulfur (Li-S) batteries. While the interaction between catalysts and representative species has been reported, the root of the kinetics difference, interaction change among redox reactions, remains unclear, which significantly impedes the catalysts design for Li-S batteries. Here, this work deciphers the interaction change among electrocatalytic sulfur reactions, using tungsten disulfide (WS2 ) a model system to demonstrate the efficiency of modifying electrocatalytic selectivity via dual-coordination design. Band structure engineering and orbital orientation control are combined to guide the design of WS2 with boron dopants and sulfur vacancies (B-WS2- x ), accurately modulating interaction with lithium and sulfur sites in polysulfide species for relatively higher interaction with short-chain polysulfides. The modified interaction trend is experimentally confirmed by distinguishing the kinetics of each electrochemical reaction step, indicating the effectiveness of the designed strategy. An Ah-level pouch cell with B-WS2- x delivers a gravimetric energy density of up to 417.6 Wh kg-1 with a low electrolyte/sulfur ratio of 3.6 µL mg-1 and negative/positive ratio of 1.2. This work presents a dual-coordination strategy for advancing evolutionarily catalytic activity, offering a rational strategy to develop effective catalysts for practical Li-S batteries.

PhyNEO: A Neural-Network-Enhanced Physics-Driven Force Field Development Workflow for Bulk Organic Molecule and Polymer Simulations.

An accurate, generalizable, and transferable force field plays a crucial role in the molecular dynamics simulations of organic polymers and biomolecules. Conventional empirical force fields often fail to capture precise intermolecular interactions due to their negligence of important physics, such as polarization, charge penetration, many-body dispersion, etc. Moreover, the parameterization of these force fields relies heavily on top-down fittings, limiting their transferabilities to new systems where the experimental data are often unavailable. To address these challenges, we introduce a general and fully ab initio force field construction strategy, named PhyNEO. It features a hybrid approach that combines both the physics-driven and the data-driven methods and is able to generate a bulk potential with chemical accuracy using only quantum chemistry data of very small clusters. Careful separations of long-/short-range interactions and nonbonding/bonding interactions are the key to the success of PhyNEO. By such a strategy, we mitigate the limitations of pure data-driven methods in long-range interactions, thus largely increasing the data efficiency and the scalability of machine learning models. The new approach is thoroughly tested on poly(ethylene oxide) and polyethylene glycol systems, giving superior accuracies in both microscopic and bulk properties compared to conventional force fields. This work thus offers a promising framework for the development of advanced force fields in a wide range of organic molecular systems.

Transcutaneous Spinal Cord Stimulation to Stabilize Seated Systolic Blood Pressure in Persons With Chronic Spinal Cord Injury: Protocol Development.

Transcutaneous spinal cord stimulation (tSCS) is an emerging therapeutic strategy to target spinal autonomic circuitry to normalize and stabilize blood pressure (BP) in hypotensive persons living with chronic spinal cord injury (SCI). Our aim is to describe our current methodological approach to identify individual tSCS parameters that result in the maintenance of seated systolic blood pressure (SBP) within a pre-defined target range. The parent study is a prospective, randomized clinical trial in which eligible participants will undergo multiple mapping sessions to optimize tSCS parameter settings to promote stable SBP within a target range of 110-120 mm Hg for males and 100-120 mm Hg for females. Parameter mapping includes cathode electrode placement site (T7/8, T9/10, T11/12, and L1/2), stimulation frequency (30, 60 Hz), current amplitudes (0-120 mA), waveform (mono- and biphasic), pulse width (1000 µs), and use of carrier frequency (0, 10 kHz). Each participant will undergo up to 10 mapping sessions involving different electrode placement sites and parameter settings. BP will be continuously monitored throughout each mapping session. Stimulation amplitude (mA) will be increased at intervals of between 2 and 10 mA until one of the following occurs: 1) seated SBP reaches the target range; 2) tSCS intensity reaches 120 mA; or 3) the participant requests to stop. Secondary outcomes recorded include 1) symptoms related to autonomic dysreflexia and orthostatic hypotension, 2) Likert pain scale, and 3) skin appearance after removal of the tSCS electrode. Clinical Trials Registration: NCT05180227.

Discriminating between Homogeneous (AC-1) and Dense Fine Speckled (AC-2) Antinuclear Antibody Patterns: Re-Evaluation of Immunofluorescence Imaging.

Antinuclear antibodies (ANAs) are essential diagnostic markers in systemic autoimmune rheumatic diseases. Among the 30 ANA patterns, homogeneous (AC-1) and dense fine speckled (AC-2) should be focused on owing to their somewhat indistinct presentation in immunofluorescence imaging and distinct correlation with clinical conditions. This study aimed to develop a flowchart to guide discrimination between AC-1 and AC-2 patterns and to re-evaluate ANA samples according to this flowchart to verify its detection ability. We re-evaluated immunofluorescence imaging of 62 ANA blood samples simultaneously subjected to solid-phase assays for autoantibodies against dsDNA, nucleosomes, histones, and DFS70. The results showed statistically significant odd ratios (ORs) of detection of anti-DFS70 using AC-2 after re-evaluation of total samples (OR 101.9, 95% CI 11.7-886.4, p-value < 0.001) and subgroup analysis of patients' samples (OR 53.8, 95% CI 5.9-493.6, p-value < 0.001). The OR of anti-nucleosome/histone/dsDNA detection using AC-1 in re-evaluated data increased to 5.43 (95% CI 1.00-29.61, p-value = 0.05). In the analysis of specific autoantibodies, more than half of the samples with an AC-2 pattern (54.2%) had specific autoantibodies other than anti-DFS70. We conclude that the flowchart for discriminating between AC-1 and AC-2 ANA patterns in this study is a viable practical guide for other laboratories when encountering equivocal ANA results.

Remote Ischemic conditioning as an emerging tool to improve corticospinal transmission in individuals with chronic spinal cord injury.

PURPOSE OF REVIEW: Remote ischemic conditioning (RIC) involves transient blood flow restriction to one limb leading to systemic tissue-protective effects. RIC shares some potential underlying mechanisms with intermittent hypoxia (IH), in which brief bouts of systemic hypoxia trigger increases in growth factor expression and neural plasticity. RIC has shown promise in acute myocardial infarction and stroke but may be applicable toward chronic neuropathology as well. Consequently, this review discusses similarities and differences between RIC and IH and presents preliminary and ongoing research findings regarding RIC. RECENT FINDINGS: Several publications demonstrated that combining RIC with motor training may enhance motor learning in adults with intact nervous systems, though the precise mechanisms were unclear. Our own preliminary data has found that RIC, in conjunction with task specific exercise, can increase corticospinal excitability in a subset of people without neurological injury and in those with chronic cervical spinal cord injury or amyotrophic lateral sclerosis. SUMMARY: RIC is a low-cost intervention easy to deliver in a clinical or home setting. Its potential application to facilitate neural plasticity and motor learning during rehabilitation training for individuals with chronic neurological disorders is a novel concept requiring further investigation to characterize mechanisms, safety, and efficacy.

Constrained Hybrid Monte Carlo Sampling Made Simple for Chemical Reaction Simulations.

Most electrochemical reactions should be studied under a grand canonical ensemble condition with a constant potential and/or a constant pH value. Free energy profiles provide key insights into understanding the reaction mechanisms. However, many molecular dynamics (MD)-based theoretical studies for electrochemical reactions did not employ an exact grand canonical ensemble sampling scheme for the free energy calculations, partially due to the issues of discontinuous trajectories induced by the particle-number variations during MD simulations. An alternative statistical sampling approach, the Monte Carlo (MC) method, is naturally appropriate for the open-system simulations if we focus on the thermodynamic properties. An advanced MC scheme, the hybrid Monte Carlo (HMC) method, which can efficiently sample the configurations of a system with large degrees of freedom, however, has limitations in the constrained-sampling applications. In this work, we propose an adjusted constrained HMC method to compute free energy profiles using the thermodynamic integration (TI) method. The key idea of the method for handling the constraint in TI is to integrate the reaction coordinate and sample the rest degrees of freedom by two types of MC schemes, the HMC scheme and the Metropolis algorithm with unbiased trials (M(RT)2-UB). We test the proposed method on three different systems involving two kinds of reaction coordinates, which are the distance between two particles and the difference of particles' distances, and compare the results to those generated by the constrained M(RT)2-UB method serving as benchmarks. We show that our proposed method has the advantages of high sampling efficiency and convenience of implementation, and the accuracy is justified as well. In addition, we show in the third test system that the proposed constrained HMC method can be combined with the path integral method to consider the nuclear quantum effects, indicating a broader application scenario of the sampling method reported in this work.

The effect of uveitis and undiagnosed spondyloarthritis: a systematic review and meta-analysis.

Delay diagnosis of spondyloarthritis (SpA) is associated with poor functional ability and quality of life. Uveitis is the most frequent extraarticular manifestation in SpA, and its prevalence increases with longer disease duration. This study examines the effect of uveitis on the disease activity and functional outcome of undiagnosed SpA. We reviewed published and unpublished studies. Data were pooled using the random-effects model; pooled means, and mean differences (MDs) were calculated. In the included 14 studies, disease activity, functional index, and inflammatory markers were measured in 2581 patients with SpA with uveitis and 13,972 without. The pooled mean delay in diagnosis of SpA with uveitis (6.08 years; 95% CI 4.77 to 7.38) was longer than those without (5.41 years; 95% CI 3.94 to 6.89). The Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) score was the highest for a delay of 2-5 years (5.60, 95% CI 5.47 to 5.73) and the Bath Ankylosing Spondylitis Functional Index (BASFI) score was the lowest for a delay of < 2 years (2.92, 95% CI 2.48 to 3.37) and gradually increased to delay of > 10 years (4.17, 95% CI 2.93 to 5.41). Patients with SpA with uveitis had higher trend of Ankylosing Spondylitis Disease Activity Score (ASDAS)-CRP and BASDAI. The delay to diagnosis was longer in SpA with uveitis, and disease activity was often higher than those without uveitis. Early diagnosis of SpA with timely initiation of an appropriate management plan may reduce the adverse effects of the disease and improve functional ability.

Finding the Common Single-Nucleotide Polymorphisms in Three Autoimmune Diseases and Exploring Their Bio-Function by Using a Reporter Assay.

In clinical practice, it is found that autoimmune thyroid disease often additionally occurs with systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). In addition, several studies showed that eye-specific autoimmune diseases may have a strong relationship with systemic autoimmune diseases. We focused on Graves' disease (GD) with ocular conditions, also known as Graves' ophthalmopathy (GO), trying to find out the potential genetic background related to GO, RA, and SLE. There were 40 GO cases and 40 healthy controls enrolled in this study. The association between single-nucleotide polymorphisms (SNPs) of the co-stimulatory molecule genes and GO was analyzed using a chi-square test. It showed that rs11571315, rs733618, rs4553808, rs11571316, rs16840252, and rs11571319 of CTLA4, rs3181098 of CD28, rs36084323 and rs10204525 of PDCD1, and rs11889352 and rs4675379 of ICOS were significantly associated with GO based on genotype analysis and/or allele analysis (p < 0.05). After summarizing the GO data and the previously published SLE and RA data, it was found that rs11571315, rs733618, rs4553808, rs16840252, rs11571319, and rs36084323 were shared in these three diseases. Furthermore, the bio-function was confirmed by dual-luciferase reporter assay. It was shown that rs733618 T > C and rs4553808 A > G significantly decreased the transcriptional activity (both p < 0.001). This study is the first to confirm that these three diseases share genetically predisposing factors, and our results support the proposal that rs733618 T > C and rs4553808 A > G have bio-functional effects on the transcriptional activity of the CTLA4 gene.

DMFF: An Open-Source Automatic Differentiable Platform for Molecular Force Field Development and Molecular Dynamics Simulation.

In the simulation of molecular systems, the underlying force field (FF) model plays an extremely important role in determining the reliability of the simulation. However, the quality of the state-of-the-art molecular force fields is still unsatisfactory in many cases, and the FF parameterization process largely relies on human experience, which is not scalable. To address this issue, we introduce DMFF, an open-source molecular FF development platform based on an automatic differentiation technique. DMFF serves as a powerful tool for both top-down and bottom-up FF development. Using DMFF, both energies/forces and thermodynamic quantities such as ensemble averages and free energies can be evaluated in a differentiable way, realizing an automatic, yet highly flexible FF optimization workflow. DMFF also eases the evaluation of forces and virial tensors for complicated advanced FFs, helping the fast validation of new models in molecular dynamics simulation. DMFF has been released as an open-source package under the LGPL-3.0 license and is available at https://github.com/deepmodeling/DMFF.