Long-Chain Molecular Crystals Antimony(III) Alkanethiolates Sb(SCnH2n+1)3 (n ≥ 12): Synthesis, Crystal and Electronic Structures, and Supramolecular Self-Assembly via Secondary Interactions.

Currently, there is not much success in solving the molecular and crystal structures of long-chain metal alkanethiolate complexes [M(SCnH2n+1)m] at the atomic level. Taking Sb(SC16H33)3 (1) as an example, we herein disclose the structural characteristics of long-chain trivalent antimony(III) alkanethiolates Sb(SCnH2n+1)3 (n ≥ 12) by single-crystal X-ray crystallography. Specifically, the Sb atom is three-coordinated by alkanethiolate ligands and a slightly distorted triangular pyramid SbS3 core is formed owing to the unique intramolecular stereochemistry of three alkyl chains, namely, two of them almost parallel aligning and the third chain extending alone around the SbS3 core. We further determine the conformation, spatial orientation and packing density of alkyl chains in 1 along with a comparison to those in other long-chain crystalline systems, and reveal the roles of intermolecular van der Waals and Sb···S secondary interactions in molecular self-assembly, which enables 1 to be a layer-structured molecular crystal with a monoclinic P21/c unit cell. The band structures and the atomic orbital contributions to the valence band maximum and conduction band minimum for 1 have also been evaluated by DFT calculations and rationally correlated with its optical absorption property. This study will help understand and discover new structures and structure-property relations of long-chain chemical systems.

Automatic, dynamic, and nearly optimal learning rate specification via local quadratic approximation.

In deep learning tasks, the update step size determined by the learning rate at each iteration plays a critical role in gradient-based optimization. However, determining the appropriate learning rate in practice typically relies on subjective judgment. In this work, we propose a novel optimization method based on local quadratic approximation (LQA). In each update step, we locally approximate the loss function along the gradient direction by using a standard quadratic function of the learning rate. Subsequently, we propose an approximation step to obtain a nearly optimal learning rate in a computationally efficient manner. The proposed LQA method has three important features. First, the learning rate is automatically determined in each update step. Second, it is dynamically adjusted according to the current loss function value and parameter estimates. Third, with the gradient direction fixed, the proposed method attains a nearly maximum reduction in the loss function. Extensive experiments were conducted to prove the effectiveness of the proposed LQA method.

The Role of Mitochondria in Systemic Lupus Erythematosus: A Glimpse of Various Pathogenetic Mechanisms.

BACKGROUND: Systemic Lupus Erythematosus (SLE) is a polysystem autoimmune disease that adversely affects human health. Various organs can be affected, including the kidney or brain. Traditional treatment methods for SLE primarily rely on glucocorticoids and immunosuppressors. Unfortunately, these therapeutic agents cannot prevent a high recurrence rate after SLE remission. Therefore, novel therapeutic targets are urgently required. METHODS: A systematic search of the published literature regarding the abnormal structure and function of mitochondria in SLE and therapies targeting mitochondria was performed in several databases. RESULTS: Accumulating evidence indicates that mitochondrial dysfunction plays important roles in the pathogenesis of SLE, including influencing mitochondrial DNA damage, mitochondrial dynamics change, abnormal mitochondrial biogenesis and energy metabolism, mitophagy, oxidative stress, inflammatory reactions, apoptosis and NETosis. Further investigation of mitochondrial pathophysiological roles will result in further clarification of SLE. Specific lupus-induced organ damage also exhibits characteristic mitochondrial changes. CONCLUSION: This review aimed to summarize the current research on the role of mitochondrial dysfunction in SLE, which will necessarily provide potential novel therapeutic targets for SLE.

The Impact of Vitamin D Receptor Gene Polymorphisms on the Susceptibility of Diabetic Vascular Complications: A Meta-Analysis.

Background: To determine whether vitamin D receptor (VDR) gene polymorphisms are correlated with susceptibility to diabetic vascular complications. Methods: We included all eligible studies, and used Stata12.0 to calculate the pooled results. Results: Eight thousand eleven diabetic patients and 1635 normal controls from 27 studies were included. Our results showed that there was no correlation between VDR gene TaqI variants and diabetic nephropathy (DN) or diabetic retinopathy (DR) susceptibility. In comparison with diabetic patients without DN, there was a link between the VDR gene ApaI variant and DN susceptibility under allelic model (p = 0.029) in all populations. In addition, the VDR gene BsmI variant correlated with DN under both dominant (p = 0.005) and allelic (p = 0.003) models in Asian populations. The VDR gene FokI variant was also correlated with DN susceptibility under the recessive model (p = 0.027) in the Asian subgroup. In comparison with diabetic patients without DR, we identified a link between the VDR gene ApaI variant and DR susceptibility under the dominant model (p = 0.034) in all populations. Also, the VDR gene FokI variant was correlated with DR under the recessive (p = 0.016), the allelic (p = 0.001), and the dominant (p < 0.001) models in all populations. When compared with healthy controls, the VDR gene BsmI variant was associated with DR under the additive (p = 0.014), the allelic (p = 0.033), and the dominant (p < 0.001) models in Indian populations. Conclusions: The VDR gene BsmI, ApaI, and FokI gene variants are associated with DN and DR susceptibility. No association was found between the VDR gene TaqI gene variants and diabetic vascular complications.