Recent development of azole-sulfonamide hybrids with the anticancer potential.

Cancer exhibits heterogeneity that enables adaptability and remains grand challenges for effective treatment. Chemotherapy is a validated and critically important strategy for the treatment of cancer, but the emergence of multidrug resistance which may lead to recurrence of disease or even death is a major hurdle for successful chemotherapy. Azoles and sulfonamides are important anticancer pharmacophores, and azole-sulfonamide hybrids have the potential to simultaneously act on dual/multiple targets in cancer cells, holding great promise to overcome drug resistance. This review outlines the current scenario of azole-sulfonamide hybrids with the anticancer potential, and the structure-activity relationships as well as mechanisms of action are also discussed, covering articles published from 2020 onward.

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A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection.

Accuratedetection and segmentation of brain tumors is critical for medical diagnosis. However, current supervised learning methods require extensively annotated images and the state-of-the-art generative models used in unsupervised methods often have limitations in covering the whole data distribution. In this paper, we propose a novel framework Two-Stage Generative Model (TSGM) that combines Cycle Generative Adversarial Network (CycleGAN) and Variance Exploding stochastic differential equation using joint probability (VE-JP) to improve brain tumor detection and segmentation. The CycleGAN is trained on unpaired data to generate abnormal images from healthy images as data prior. Then VE-JP is implemented to reconstruct healthy images using synthetic paired abnormal images as a guide, which alters only pathological regions but not regions of healthy. Notably, our method directly learned the joint probability distribution for conditional generation. The residual between input and reconstructed images suggests the abnormalities and a thresholding method is subsequently applied to obtain segmentation results. Furthermore, the multimodal results are weighted with different weights to improve the segmentation accuracy further. We validated our method on three datasets, and compared with other unsupervised methods for anomaly detection and segmentation. The DSC score of 0.8590 in BraTs2020 dataset, 0.6226 in ITCS dataset and 0.7403 in In-house dataset show that our method achieves better segmentation performance and has better generalization.

Accelerating the 3D T1ρ mapping of cartilage using a signal-compensated robust tensor principal component analysis model.

BACKGROUND: Magnetic resonance (MR) quantitative T1ρ imaging has been increasingly used to detect the early stages of osteoarthritis. The small volume and curved surface of articular cartilage necessitate imaging with high in-plane resolution and thin slices for accurate T1ρ measurement. Compared with 2D T1ρ mapping, 3D T1ρ mapping is free from artifacts caused by slice cross-talk and has a thinner slice thickness and full volume coverage. However, this technique needs to acquire multiple T1ρ-weighted images with different spin-lock times, which results in a very long scan duration. It is highly expected that the scan time can be reduced in 3D T1ρ mapping without compromising the T1ρ quantification accuracy and precision. METHODS: To accelerate the acquisition of 3D T1ρ mapping without compromising the T1ρ quantification accuracy and precision, a signal-compensated robust tensor principal component analysis method was proposed in this paper. The 3D T1ρ-weighted images compensated at different spin-lock times were decomposed as a low-rank high-order tensor plus a sparse component. Poisson-disk random undersampling patterns were applied to k-space data in the phase- and partition-encoding directions in both retrospective and prospective experiments. Five volunteers were involved in this study. The fully sampled k-space data acquired from 3 volunteers were retrospectively undersampled at R=5.2, 7.7, and 9.7, respectively. Reference values were obtained from the fully sampled data. Prospectively undersampled data for R=5 and R=7 were acquired from 2 volunteers. Bland-Altman analyses were used to assess the agreement between the accelerated and reference T1ρ measurements. The reconstruction performance was evaluated using the normalized root mean square error and the median of the normalized absolute deviation (MNAD) of the reconstructed T1ρ-weighted images and the corresponding T1ρ maps. RESULTS: T1ρ parameter maps were successfully estimated from T1ρ-weighted images reconstructed using the proposed method for all accelerations. The accelerated T1ρ measurements and reference values were in good agreement for R=5.2 (T1ρ: 40.4±1.4 ms), R=7.7 (T1ρ: 40.4±2.1 ms), and R=9.7 (T1ρ: 40.9±2.2 ms) in the Bland-Altman analyses. The T1ρ parameter maps reconstructed from the prospectively undersampled data also showed promising image quality using the proposed method. CONCLUSIONS: The proposed method achieves the 3D T1ρ mapping of in vivo knee cartilage in eight minutes using a signal-compensated robust tensor principal component analysis method in image reconstruction.

Association of the Asp312Asn and Lys751Gln polymorphisms in the XPD gene with the risk of non-Hodgkin's lymphoma: evidence from a meta-analysis.

Polymorphisms in DNA repair genes may alter DNA repair capacity and, consequently, lead to genetic instability and carcinogenesis. Several studies have investigated the association of the Asp312Asn and Lys751Gln polymorphisms in the xeroderma pigmentosum complementation group D (XPD) gene with the risk of non-Hodgkin's lymphoma (NHL), but the conclusions have been inconsistent. Therefore, we performed this meta-analysis to more precisely estimate these relationships. A systematic literature search was performed using the PubMed, Embase, and Chinese Biomedical (CBM) databases. Ultimately, 6 studies of Asp312Asn, comprising 3,095 cases and 3,306 controls, and 7 studies of Lys751Gln, consisting of 3,249 cases and 3,676 controls, were included. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of each association. Overall, no association was observed between the Asp312Asn polymorphism and NHL risk (homozygous: OR = 1.11, 95% CI = 0.94-1.32; heterozygous: OR = 1.00, 95% CI = 0.89-1.11; recessive: OR = 1.12, 95% CI = 0.95-1.31; dominant: OR = 1.02, 95% CI = 0.92-1.13; and allele comparison: OR = 1.04, 95% CI = 0.96-1.12) or between the Lys751Gln polymorphism and NHL risk (homozygous: OR = 0.97, 95% CI = 0.83-1.15; heterozygous: OR = 0.96, 95% CI = 0.86-1.06; recessive: OR = 1.00, 95% CI = 0.86-1.16; dominant: OR = 0.96, 95% CI = 0.87-1.06; and allele comparison: OR = 0.98, 95% CI = 0.91-1.05). Furthermore, subgroup analyses did not reveal any association between these polymorphisms and ethnicity, the source of the controls, or the NHL subtype. These results indicated that neither the Asp312Asn nor Lys751Gln XPD polymorphism was related to NHL risk. Large and well-designed prospective studies are required to confirm this finding.

No association between MTR rs1805087 A > G polymorphism and non-Hodgkin lymphoma susceptibility: evidence from 11 486 subjects.

Numerous investigations have examined the association between MTR rs1805087 A> G polymorphism and non-Hodgkin lymphoma (NHL) susceptibility, yet have generated conflicting results. Therefore, the current meta-analysis was performed to comprehensively reevaluate this association. A systematic literature search of PubMed and Embase databases was conducted to seek eligible publications. The final analysis included 13 publications with a total of 4555 cases of NHL and 6931 controls. Overall, pooled analysis did not yield any statistically significant association between MTR rs1805087 A> G and NHL risk. Stratification analysis by source of controls showed a decreased risk of NHL with the polymorphism of interest in hospital-based studies, while no significant association was observed when data were stratified by ethnicity, sample size and NHL subtype. This meta-analysis does not indicate a major role of the MTR rs1805087 A> G polymorphism in modulating NHL risk. However, well-designed prospective studies with large sample sizes are encouraged to validate our findings.

The association between the polymorphisms of TNF-α and non-Hodgkin lymphoma: a meta-analysis.

Many genetic variations in the promoter region of tumor necrosis factor alpha (TNF-α) may confer host susceptibility to cancer by influencing TNF-α expression. Nevertheless, the results remain inconclusive. The current meta-analysis was performed to investigate the association between three common TNF-α promoter polymorphisms and the risk of non-Hodgkin lymphoma (NHL). A literature search was conducted mainly from PubMed for all eligible studies. The pooled odds ratios (ORs) and corresponding 95 % confidence intervals (CIs) were used to assess the association of TNF-α polymorphisms with the risk of NHL. TNF-α -308 A allele showed a statistically significant increased risk for NHL under the homozygous (AA vs. GG, OR = 1.51, 95 % CI = 1.26-1.80) and recessive (OR = 1.47, 95 % CI = 1.23-1.75) models, respectively. The stratified analyses showed an increased risk of NHL with the presence of TNF-α -308 A allele among Africans and Caucasians, but a decreased risk among Asians. No association was observed between -238 G/A polymorphism and NHL risk either in the overall analysis or in the stratified analysis. Similarly, pooled analysis did not reveal an altered risk of NHL with -857 C/T polymorphism. Nonetheless, a statistically significant association was observed among Asians when stratified by ethnicity. Among the three genetic variations of interest, TNF-α -308 G/A polymorphism was significantly associated with the risk of NHL; neither -238 G/A nor -857 C/T polymorphism was shown to alter the overall NHL risk; however, stratified analysis by ethnicity observed a statistically significant association between -857 C/T polymorphism and the risk of NHL among Asians.

[Cloning and efficient prokaryotic expression of soluble stage-specific antigen cC1 from Cysticercus cellulosae].

OBJECTIVE: To clone the coding gene of the stage-specific antigen cC1 from Cysticercus cellulosae and express high levels of soluble cC1 in E.coli. METHODS: The cC1 gene was amplified from Cysticercus cellulosae by RT-PCR and cloned into pMD18-T vector, followed by subcloning into the prokaryotic expression plasmid pET28a. The recombinant plasmid was transformed into E.coli BL21(DE3) and the expression conditions were optimized. The expressed product was purified by Ni(+)-affinity chromatography, analyzed by high-performance liquid chromatography (HPLC), and identified with SDS-PAGE and Western blotting. RESULTS: The fragment length of the amplification product by RT-PCR was 1056 bp. Comparison of the amplified gene sequence with the cC1 gene in Genbank identified a samesense point mutation at 423 position in the gene cloned into the expression plasmids. After a 6-h induction with 0.05 mmol/L IPTG at 37 degrees celsius;, the expression of the 40 kd soluble fusion protein exceeded 60% of the total bacterial protein, and the fusion protein was recognized by Cysticercus-infected human sera. The purity of the fusion protein was about 94% after purification by affinity chromatography. CONCLUSION: The stage-specific antigen cC1 from Cysticercus cellulosae has been successfully cloned and the soluble protein efficiently expressed in E.coli, which provides the basis for its further study and application.