Necrostatin-1s Suppresses RIPK1-driven Necroptosis and Inflammation in Periventricular Leukomalacia Neonatal Mice.

Periventricular leukomalacia (PVL), a predominant form of brain injury in preterm survivors, is characterized by hypomyelination and microgliosis and is also the major cause of long-term neurobehavioral abnormalities in premature infants. Receptor-interacting protein kinase 1 (RIPK1) plays a pivotal role in mediating cell death and inflammatory signaling cascade. However, very little is known about the potential effect of RIPK1 in PVL and the underlying mechanism. Herein, we found that the expression level of RIPK1 was drastically increased in the brain of PVL neonatal mice models, and treatment of PVL neonatal mice with Necrostatin-1s (Nec-1s), an inhibitor of RIPK1, greatly ameliorated cerebral ischemic injury, exhibiting an increase of body weights, reduction of cerebral infarct size, neuronal loss, and occurrence of necrosis-like cells, and significantly improved the long-term abnormal neurobehaviors of PVL. In addition, Nec-1s significantly suppressed hypomyelination and promoted the differentiation of oligodendrocyte precursor cells (OPCs), as demonstrated by the increased expression levels of MBP and Olig2, the decreased expression level of GPR17, a significant increase in the number of CC-1-positive cells, and suppression of myelin ultrastructure impairment. Moreover, the mechanism of neuroprotective effects of Nec-1s against PVL is closely associated with its suppression of the RIPK1-mediated necrosis signaling molecules, RIPK1, PIPK3, and MLKL. More importantly, inhibition of RIPK1 could reduce microglial inflammatory injury by triggering the M1 to M2 microglial phenotype, appreciably decreasing the levels of M1 marker CD86 and increasing the levels of M2 markers Arg1 or CD206 in PVL mice. Taken together, inhibition of RIPK1 markedly ameliorates the brain injury and long-term neurobehavioral abnormalities of PVL mice through the reduction of neural cell necroptosis and reversing neuroinflammation.

Thiazolidine-2,4-dione derivatives as potential α-glucosidase inhibitors: Synthesis, inhibitory activity, binding interaction and hypoglycemic activity.

In order to find effective α-glucosidase inhibitors, a series of thiazolidine-2,4-dione derivatives (C1 âˆ¼ 36) were synthesized and evaluated for α-glucosidase inhibitory activity. Compared to positive control acarbose (IC50 = 654.35 ± 65.81 µM), all compounds (C1 âˆ¼ 36) showed stronger α-glucosidase inhibitory activity with IC50 values of 0.52 ± 0.06 âˆ¼ 9.31 ± 0.96 µM. Among them, C23 with the best anti-α-glucosidase activity was a reversible mixed-type inhibitor. Fluorescence quenching suggested the binding process of C23 with α-glucosidase in a static process. Fluorescence quenching, CD spectra, and 3D fluorescence spectra results also implied that the binding of C23 with α-glucosidase caused the conformational change of α-glucosidase to inhibit the activity. Molecular docking displayed the binding interaction of C23 with α-glucosidase. Compound C23 (8 âˆ¼ 64 µM) showed no cytotoxicity against LO2 and 293 cells. Moreover, oral administration of C23 (50 mg/kg) could reduce blood glucose and improve glucose tolerance in mice.

Upregulation of PGC-1α Attenuates Oxygen-Glucose Deprivation-Induced Hippocampal Neuronal Injury.

Hippocampal neuronal damage likely underlies cognitive impairment in vascular dementia (VaD). PPARγ coactivator-1α (PGC-1α) is a master regulator of mitochondrial biogenesis. However, the role and the precise mechanism of how PGC-1α alleviates hippocampal neuronal injury remain unknown. To address this question, HT-22 cells, an immortalized hippocampal neuron cell line, with or without PGC-1α overexpression were subjected to oxygen-glucose deprivation (OGD), which mimics the circumstance of chronic cerebral hypoperfusion in VaD. After OGD, cell viability was assessed using the MTS assay. The mitochondrial function and reactive oxygen species (ROS) were both detected. ChIP-Seq analysis was employed to discover the underlying molecular mechanism of PGC-1α-mediated neuroprotective effects. Our results showed that mitochondrial membrane potentials were increased and ROS production was decreased in PGC-1α overexpressing cells, which increased cell viability. The further bioinformatics analysis from ChIP-Seq data indicated that PGC-1α may participate in the regulation of apoptosis, autophagy, and mitophagy pathways in HT-22 cells. We found that PGC-1α promoted the LC3-II formation and reduced the neuronal apoptosis determined by TUNEL staining. In addition, PGC-1α upregulated the expressions of mitochondrial antioxidants, including SOD2, Trx2, and Prx3. In summary, our findings indicate that PGC-1α may attenuate OGD-induced hippocampal neuronal damage by regulating multiple mechanisms, like autophagy and mitochondrial function. Thus, PGC-1α may be a potential therapeutic target for hippocampal damage associated with cognitive impairment.

Low Correlation Interference OFDM-NLFM Waveform Design for MIMO Radar Based on Alternating Optimization.

The OFDM chirp signal is suitable for MIMO radar applications due to its large time-bandwidth product, constant time-domain, and almost constant frequency-domain modulus. Particularly, by introducing the time-frequency structure of the non-linear frequency modulation (NLFM) signal into the design of an OFDM chirp waveform, a new OFDM-NLFM waveform with low peak auto-correlation sidelobe ratio (PASR) and peak cross-correlation ratio (PCCR) is obtained. IN-OFDM is the OFDM-NLFM waveform set currently with the lowest PASR and PCCR. Here we construct the optimization model of the OFDM-NLFM waveform set with the objective function being the maximum of the PASR and PCCR. Further, this paper proposes an OFDM-NLFM waveform set design algorithm inspired by alternating optimization. We implement the proposed algorithm by the alternate execution of two sub-algorithms. First, we keep both the sub-chirp sequence code matrix and sub-chirp rate plus and minus (PM) code matrix unchanged and use the particle swarm optimization (PSO) algorithm to obtain the optimal parameters of the NLFM signal's time-frequency structure (NLFM parameters). Next, we keep current optimal NLFM parameters unchanged, and optimize the sub-chirp sequence code matrix and sub-chirp rate PM code matrix using the block coordinate descent (BCD) algorithm. The above two sub-algorithms are alternately executed until the objective function converges to the optimal solution. The results show that the PASR and PCCR of the obtained OFDM-NLFM waveform set are about 5 dB lower than that of the IN-OFDM.

A New Multiple Hypothesis Tracker Using Validation Gate with Motion Direction Constraint.

In multi-target tracking scenarios with dense and heterogeneous clutter, there is a substantial increase in the false measurements that originated from the clutter within the validation gate, and consequently, the number of measurement-to-track association hypothesis grows rapidly in traditional multiple hypothesis tracker (MHT), leading to a sharp decrease in data association accuracy and tracking performance. A new multiple hypothesis tracker using validation gate with motion direction constraint (MHT-MDC) is proposed to solve these problems. In the MHT-MDC, a motion direction constraint (MDC) gate is designed by considering the prior target maneuvering information, which effectively reduces the volume of validation gate and, thus, diminishes the number of false measurements in the gate when the innovation covariance is large. Subsequently, the clutter density in the MDC gate is adaptively estimated by the conditional mean estimator of clutter density (CMECD), based on which the score functions in the MDC gate can be calculated. The MHT-MDC is compared with the MHT algorithm in simulations, and the experimental results demonstrate its superior tracking performance for weakly maneuvering targets in high clutter density scenarios.

Pattern Synthesis of Linear Antenna Array Using Improved Differential Evolution Algorithm with SPS Framework.

In this paper, an improved differential evolution (DE) algorithm with the successful-parent-selecting (SPS) framework, named SPS-JADE, is applied to the pattern synthesis of linear antenna arrays. Here, the pattern synthesis of the linear antenna arrays is viewed as an optimization problem with excitation amplitudes being the optimization variables and attaining sidelobe suppression and null depth being the optimization objectives. For this optimization problem, an improved DE algorithm named JADE is introduced, and the SPS framework is used to solve the stagnation problem of the DE algorithm, which further improves the DE algorithm's performance. Finally, the combined SPS-JADE algorithm is verified in simulation experiments of the pattern synthesis of an antenna array, and the results are compared with those obtained by other state-of-the-art random optimization algorithms. The results demonstrate that the proposed SPS-JADE algorithm is superior to other algorithms in the pattern synthesis performance with a lower sidelobe level and a more satisfactory null depth under the constraint of beamwidth requirement.

A New Multiple Hypothesis Tracker Integrated with Detection Processing.

In extant radar signal processing systems, detection and tracking are carried out independently, and detected measurements are utilized as inputs to the tracking procedure. Therefore, the tracking performance is highly associated with detection accuracy, and this performance may severely degrade when detections include a mass of false alarms and missed-targets errors, especially in dense clutter or closely-spaced trajectories scenarios. To deal with this issue, this paper proposes a novel method for integrating the multiple hypothesis tracker with detection processing. Specifically, the detector acquires an adaptive detection threshold from the output of the multiple hypothesis tracker algorithm, and then the obtained detection threshold is employed to compute the score function and sequential probability ratio test threshold for the data association and track estimation tasks. A comparative analysis of three tracking algorithms in a clutter dense scenario, including the proposed method, the multiple hypothesis tracker, and the global nearest neighbor algorithm, is conducted. Simulation results demonstrate that the proposed multiple hypothesis tracker integrated with detection processing method outperforms both the standard multiple hypothesis tracker algorithm and the global nearest neighbor algorithm in terms of tracking accuracy.

δ-Generalized Labeled Multi-Bernoulli Filter Using Amplitude Information of Neighboring Cells.

The amplitude information (AI) of echoed signals plays an important role in radar target detection and tracking. A lot of research shows that the introduction of AI enables the tracking algorithm to distinguish targets from clutter better and then improves the performance of data association. The current AI-aided tracking algorithms only consider the signal amplitude in the range-azimuth cell where measurement exists. However, since radar echoes always contain backscattered signals from multiple cells, the useful information of neighboring cells would be lost if directly applying those existing methods. In order to solve this issue, a new δ-generalized labeled multi-Bernoulli (δ-GLMB) filter is proposed. It exploits the AI of radar echoes from neighboring cells to construct a united amplitude likelihood ratio, and then plugs it into the update process and the measurement-track assignment cost matrix of the δ-GLMB filter. Simulation results show that the proposed approach has better performance in target's state and number estimation than that of the δ-GLMB only using single-cell AI in low signal-to-clutter-ratio (SCR) environment.

Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory.

Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

Semi-Supervised Generative Adversarial Nets with Multiple Generators for SAR Image Recognition.

As an important model of deep learning, semi-supervised learning models are based on Generative Adversarial Nets (GANs) and have achieved a competitive performance on standard optical images. However, the training of GANs becomes unstable when they are applied to SAR images, which reduces the feature extraction capability of the discriminator in GANs. This paper presents a new semi-supervised GANs with Multiple generators and a classifier (MCGAN). This model improves the stability of training for SAR images by employing multiple generators. A multi-classifier is introduced to the new GANs to utilize the labeled images during the training of the GANs, which shares the low level layers with the discriminator. Then, the layers of the trained discriminator and the classifier construct the recognition network for SAR images after having been finely tuned using a small number of the labeled images. Experiments on the Moving and Stationary Target Acquisition and Recognition (MSTAR) databases show that the proposed recognition network achieves a better and more stable recognition performance than several traditional semi-supervised methods as well as other GANs-based semi-supervised methods.

Time- and Space-Varying Atmospheric Phase Correction in Discontinuous Ground-Based Synthetic Aperture Radar Deformation Monitoring.

Ground-based synthetic aperture radar (GB-SAR) uses active microwave remote-sensing observation mode to achieve two-dimensional deformation measurement and deformation trend extraction, which shows great prospects in the field of deformation monitoring. However, in the process of GB-SAR deformation monitoring, the disturbances caused by atmospheric effect cannot be neglected, and the atmospheric phases will seriously affect the precision of deformation monitoring. In discontinuous GB-SAR deformation monitoring mode, the atmospheric phases are particularly affected by changes of time and space, so the traditional models of atmospheric phase correction are no longer applicable. In this paper, the interferometric phase signal model considering atmospheric phase is first established. Then, the time- and space-varying characteristics of the atmospheric phase are analyzed, and a novel time- and space-varying atmospheric phase correction algorithm, based on coherent scatterers analysis, is proposed. Finally, slope deformation monitoring experiments are carried out to verify the validity and robustness of the proposed algorithm.

MicroRNA-27b exerts an oncogenic function by targeting Fbxw7 in human hepatocellular carcinoma.

Aberrant expression of microRNAs (miRNAs) plays fundamental effect on the pathogenesis of hepatocellular carcinoma (HCC). MiR-27b was previously found to play important roles in human cancers. However, its expression status, clinical significance, and biological functions in HCC remain largely unclear. The expression status of miR-27b in HCC specimens and cells were determined with qRT-PCR. MTT, 5-bromodeoxyuridine (BrdU) proliferation assays, and flow cytometry analysis were carried out to assay proliferation, cell cycle, and apoptosis. A subcutaneous model was used to evaluated the HCC tumor growth in vivo. The putative target gene of miR-27b was disclosed by TargetScan and a luciferase reporter assay. The levels of miR-27b were overexpressed in HCC. Overexpression of miR-27b was correlated with adverse prognostic features and reduced survival rate. Inhibition of miR-27b in SMMC-7721 cells remarkably suppressed proliferative ability and cell-cycle progression while enhanced apoptosis. In contrast, miR-27b overexpression resulted in prominent increased proliferation and process of cell cycle and reduced apoptosis of Hep3B cells. In vivo studies showed that knockdown of miR-27b inhibited the in vivo growth of SMMC-7721 cells in mouse xenograft model. Furthermore, we confirmed that Fbxw7 was directly regulated by miR-27b and mediated the roles of miR-27b in HCC. We suggest that miR-27b serves as an oncogenic miRNA in HCC by modulating proliferation, cell-cycle progression, and apoptosis, and its oncogenic effect is mediated by its downstream target gene, Fbxw7.

Inosine pretreatment of pregnant rats ameliorates maternal inflammation-mediated hypomyelination in pups via microglia polarization switch.

Periventricular leukomalacia (PVL) is a neurological condition observed in premature infants, characterized by hypomyelination and activation of microglia. Maternal inflammation-induced brain injury in offspring significantly contributes to the development of PVL. Currently, there are no clinical pharmaceutical interventions available for pregnant women to prevent maternal inflammation-mediated brain injury in their offspring. Inosine has been shown to modulate the immune response in diverse stressful circumstances, such as injury, ischemia, and inflammation. The aim of this investigation was to examine the potential prophylactic impact of inosine on offspring PVL induced by maternal inflammation. This was accomplished by administering a 1 mg/ml inosine solution (40 ml daily) to pregnant Sprague-Dawley (SD) rats for 16 consecutive days prior to their intraperitoneal injection of lipopolysaccharide (350 µg/kg, once a day, for two days). The results showed that maternal inosine pretreatment significantly reversed the reduction in MBP and CNPase (myelin-related markers), CC-1 and Olig2 (oligodendrocyte-related markers) in their PVL pups (P7), suggesting that inosine administration during pregnancy could improve hypomyelination and enhance the differentiation of oligodendrocyte precursor cells (OPCs) in their PVL pups. Furthermore, the protective mechanism of inosine against PVL is closely associated with the activation and polarization of microglia. This is evidenced by a notable reduction in the quantity of IBA 1-positive microglia, a decrease in the level of CD86 (a marker for M1 microglia), an increase in the level of Arg 1 (a marker for M2 microglia), as well as a decrease in the level of pro-inflammatory factors TNF-α, IL-1ß, and IL-6, and an increase in the level of anti-inflammatory factors IL-4 and IL-10 in the brain of PVL pups following maternal inosine pretreatment. Taken together, inosine pretreatment of pregnant rats can improve hypomyelination in their PVL offspring by triggering the M1/M2 switch of microglia.

Chuanzhitongluo Inhibits Neuronal Apoptosis in Mice with Acute Ischemic Stroke by Regulating the PI3K/AKT Signaling Pathway.

BACKGROUND AND PURPOSE: Apoptosis is involved in the occurrence and development of acute ischemic stroke (AIS). This study aimed to assess whether Chuanzhitongluo (CZTL), a multi-target and multi-pathway compound preparation, plays a neuroprotective role in AIS by modulating neuronal apoptosis via the PI3K/AKT signaling pathway. METHODS: A mouse model of AIS was established by photochemical processes. Cerebral infarction volume was measured by 2% staining with 2, 3, and 5-triphenyl tetrazole chloride (TTC). Neuron apoptosis was assessed by TUNEL staining. Apoptosis RNA arrays were used to detect changes in apoptosis-related gene expression profiles. Western blotting was used to detect proteins involved in the PI3K/AKT signaling pathway. RESULTS: The study demonstrated that CZTL could potentially mitigate neuronal apoptosis in AIS mice. This appears to be achieved via the up-regulation of certain genes such as BCL-2, Birc6, and others, coupled with the down-regulation of genes like BAX, Bid, and Casp3. Further validation revealed that CZTL could enhance the expression of BCL-2 and reduce the expression of Cleaved Caspase-3 and BAX at both the gene and protein levels. The study also found that CZTL can enhance the phosphorylation level of the PI3K/AKT signaling pathway. In contrast to these findings, the PI3K inhibitor LY294002 notably amplified neuronal apoptosis in AIS mice. CONCLUSIONS: These findings imply that CZTL's ability to inhibit neuronal apoptosis may be linked to the activation of AIS's PI3K/AKT signaling pathway.

Chuanzhitongluo capsule improves cognitive impairment in mice with chronic cerebral hypoperfusion via the cholinergic anti-inflammatory pathway.

Vascular cognitive impairment (VCI) has become a common disease-causing cognitive deficit in humans, second only to Alzheimer's Disease (AD). Chuanzhitongluo capsule (CZTL) is a Traditional Chinese Medicine (TCM) preparation known for its effective protection against cerebral ischemia. However, its potential to ameliorate VCI remains unclear. This study aimed to investigate the cognitive improvement effects of CZTL in a mouse model of VCI. Chronic cerebral hypoperfusion (CCH) was induced in mice by bilateral common carotid artery stenosis (BCAS) to simulate the pathological changes associated with VCI. Spatial learning and memory abilities were assessed using the Morris Water Maze (MWM). RNA sequencing (RNA-Seq) was employed to identify differentially expressed genes (DEGs) in the hippocampus. Levels of inflammatory factors were measured through enzyme-linked immunosorbent assay (ELISA), while immunofluorescence (IF) determined the expression intensity of target proteins. Western Blot (WB) confirmed the final action pathway. Results indicated that CZTL significantly improved the spatial learning and memory abilities of CCH mice, along with alterations in gene expression profiles in the hippocampus. It also reduced neuroinflammation in the hippocampus and upregulated the choline acetyltransferase (ChAT) and α7 subunit-containing nicotinic acetylcholine receptor (α7nAChR), which are in synaptic plasticity and neuronal development. Moreover, CZTL inhibited the NF-κB signaling pathway. In conclusion, CZTL may alleviate neuroinflammation induced by CCH and improve cognitive impairment in CCH mice by regulating the cholinergic anti-inflammatory pathway (CAIP) involving ChAT/α7nAChR/NF-κB.

Synthesis and biological evaluation of indole derivatives containing thiazolidine-2,4-dione as α-glucosidase inhibitors with antidiabetic activity.

In order to develop potential α-glucosidase inhibitors with antidiabetic activity, twenty-six indole derivatives containing thiazolidine-2,4-dione were synthesized. All compounds presented potential α-glucosidase inhibitory activities with IC50 values ranging from 2.35 ± 0.11 to 24.36 ± 0.79 µM, respectively compared to acarbose (IC50 = 575.02 ± 10.11 µM). Especially, compound IT4 displayed the strongest α-glucosidase inhibitory activity (IC50 = 2.35 ± 0.11 µM). The inhibition mechanism of compound IT4 on α-glucosidase was clarified by the investigation of kinetics studies, fluorescence quenching, CD spectra, 3D fluorescence spectra, and molecular docking. In vivo antidiabetic experiments demonstrated that oral administration of compound IT4 would suppress fasting blood glucose level and ameliorate their glucose tolerance and dyslipidemia in diabetic mice.

Subtyping treatment response of tirofiban in acute ischemic stroke based on neuroimaging features.

In a previously published clinical trial, we demonstrated that tirofiban was effective and safe in acute ischemic stroke (AIS) patients who did not undergo early recanalization treatments. We aimed to evaluate neuroimaging characteristics and their clinical significance to guide tirofiban treatment. In this post hoc analysis, location of infarcts (anterior circulation stroke [ACS] vs. posterior circulation stroke [PCS]), degree of cerebral artery stenosis (≤69% vs. ≥70% or occlusion), total infarct volume, and ASPECTS were used to predict the treatment effects of tirofiban, defined as the proportions of excellent and favorable functional outcome (modified Rankin Scale [mRS] score of 0-1, 0-2) at 90 days. ACS patients were more likely to achieve excellent (OR 2.08; 95% CI 1.25-3.45; p = 0.004) and favorable functional outcome (OR 2.28; 95% CI 1.24-4.22; p = 0.008) when treated with tirofiban. However, there was no significant difference in PCS patients between tirofiban and the control group. For patients with severe stenosis (≥70% or occlusion), tirofiban treatment improved the proportion of good outcomes (OR 2.84; 95% CI 1.44-5.60; p = 0.002 for mRS 0-1; OR 2.42; 95% CI 1.22-4.77; p = 0.011 for mRS 0-2). Meanwhile, we found that tirofiban improved outcome in patients with ASPECTS 8-10 and was independent of total infarct volume. These findings support the hypothesis that patients with ACS and severe stenosis may be recommended for tirofiban treatment, which can be predicted independent of total infarct volume.

Tirofiban mediates neuroprotective effects in acute ischemic stroke by reducing inflammatory response.

Growing evidence suggests that neuroinflammation is a critical driver of the development, worsening, and cell death observed in acute ischemic stroke (AIS). While prior research has demonstrated that tirofiban enhances functional recovery in AIS patients by suppressing platelet aggregation, its impact and underlying mechanisms in AIS-related neuroinflammation remain elusive. The current study established an AIS mouse model employing photochemical techniques and assessed neurological function and brain infarct size using the modified neurological severity scale (mNSS) and 2,3,5-Triphenyltetrazolium chloride (TTC) staining, respectively. Tirofiban significantly reduced the volume of cerebral infarction in AIS mice, accompanied by an enhancement in their neurological functions. Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays along with experiments assessing oxidative stress showed that tirofiban mitigated oxidative damage and apoptosis in the ischemic penumbra post-AIS. Additionally, DNA microarray analysis revealed alterations in gene expression patterns in the ischemic penumbra after tirofiban treatment. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that most gene-level downregulated signaling pathways were closely related to the inflammatory response. Moreover, the protein microarray analysis revealed that tirofiban diminished the expression levels of inflammatory cytokines, such as interleukin-1 (IL-1), IL-6, and tumor necrosis factor-alpha, in the ischemic penumbra. Additionally, immunofluorescence staining showed that tirofiban regulated inflammatory responses by altering the state and phenotype of microglia. In conclusion, this study suggests that tirofiban reduces inflammatory response by regulating microglial state and phenotype and lowering the levels of inflammatory factors, providing neuroprotection in acute ischemic stroke.

Identification of 1,3,4-Thiadiazolyl-Containing Thiazolidine-2,4-dione Derivatives as Novel PTP1B Inhibitors with Antidiabetic Activity.

Forty-one 1,3,4-thiadiazolyl-containing thiazolidine-2,4-dione derivatives (MY1-41) were designed and synthesized as protein tyrosine phosphatase 1B (PTP1B) inhibitors with activity against diabetes mellitus (DM). All synthesized compounds (MY1-41) presented potential PTP1B inhibitory activities, with half-maximal inhibitory concentration (IC50) values ranging from 0.41 ± 0.05 to 4.68 ± 0.61 µM, compared with that of the positive control lithocholic acid (IC50 = 9.62 ± 0.14 µM). The most potent compound, MY17 (IC50 = 0.41 ± 0.05 µM), was a reversible, noncompetitive inhibitor of PTP1B. Circular dichroism spectroscopy and molecular docking were employed to analyze the binding interaction between MY17 and PTP1B. In HepG2 cells, MY17 treatment could alleviate palmitic acid (PA)-induced insulin resistance by upregulating the expression of phosphorylated insulin receptor substrate and protein kinase B. In vivo, oral administration of MY17 could reduce the fasting blood glucose level and improve glucose tolerance and dyslipidemia in mice suffering from DM.