NAD(P)H oxidase activity of Nox4 in chondrocytes is both inducible and involved in collagenase expression

Reactive oxygen species (ROS) are regulators of redox-sensitive cell signaling pathways. In osteoarthritis, human interleukin-1beta is implicated in cartilage destruction through an ROS-dependent matrix metalloproteinase production. To determine the molecular source of ROS production in the human IL-1beta (hIL-1beta)-sensitive chondrocyte immortalized cell line C-20/A4, transfected cells were constructed that overexpress NAD(P)H oxidases. First, RT-PCR analysis showed that the C-20/A4 cell line expressed Nox2, Nox4, p22( phox ), and p67( phox ), but not p47( phox ). It was found that ROS production by C-20/A4 chondrocytes does not depend on PMA and ionomycin activation. This indicates that Nox2 was not involved in the production of ROS. In C- 20/A4 cells that overexpress Nox4, hIL-1beta stimulated ROS production three times more than the normal production of C-20/A4 cells. Moreover, there was a fourfold increase in the production of collagenase (MMP-1) by chondrocytes that overexpress Nox4. Interestingly, MMP-1 production in cells that overexpress Nox2 was not sensitive to hIL-1beta. These data suggest that under hIL-1beta stimulation, C-20/A4 chondrocytes produce MMP-1 through a Nox4-mediated, ROS-dependent pathway.     

Revised spectrum of mutations in sarcoglycanopathies

To define the spectrum of mutations in alpha-, beta-, gamma-, and delta-sarcoglycan (SG) genes, we analyzed these genes in 69 probands with clinical and biological criteria compatible with the diagnosis of autosomal recessive limb-girdle muscular dystrophy. For 48 patients, muscle biopsies were available and multiplex western blot analysis of muscle proteins showed significant abnormalities of alpha- and gamma-SG. Our diagnostic strategy includes multiplex western blot, sequencing of SG genes, multiplex quantitative-fluorescent PCR and RT-PCR analyses. Mutations were detected in 57 patients and homozygous or compound heterozygous mutations were identified in 75% (36/48) of the patients with abnormal western blot, and in 52% (11/21) of the patients without muscle biopsy. Involvement of alpha-SG was demonstrated in 55.3% of cases (26/47), whereas gamma- and beta-SG were implicated in 25.5% (12/47) and in 17% (8/47) of cases, respectively. Interestingly, we identified 25 novel mutations, and a significant proportion of these mutations correspond to deletions (identified in 14 patients) of complete exon(s) of alpha- or gamma-SG genes, and partial duplications (identified in 5 patients) of exon 1 of beta-SG gene. This study highlights the high frequency of exonic deletions of alpha- and gamma-SG genes, as well as the presence of a hotspot of duplications affecting exon 1 of the beta-SG gene. In addition, protein analysis by multiplex western blot in combination with mutation screening and genotyping results allowed to propose a comprehensive and efficient diagnostic strategy and strongly suggested the implication of additional genes, yet to be identified, in sarcoglycanopathy-like disorders.     

Anticipated and unanticipated complications of severe dengue in a primigravida

As the incidence of dengue is rising among adults more cases of dengue fever are being reported during pregnancy. Physiological changes of pregnancy mask the pathognomonic features of severe dengue such as increased hematocrit, thrombocytopenia, and leukopenia and a high index of suspicion are required in endemic areas. Massive hemorrhage may complicate operative deliveries in unsuspected patients. World Health Organization recommends that all patients with severe dengue should be admitted to a hospital with access to intensive care facilities and blood transfusion. We present the successful management of hemorrhage and unanticipated complications of severe dengue in a young primigravida admitted to the Intensive Care Unit after an emergency cesarean section.     

Paucisymptomatic Dermoid Cyst with Fatal Outcome

Dermoid cysts of the central nervous system can cause devastating complications because of the mass effect of meningitis due to sinus tract. We report the case of a 5‐month‐old girl who presented with a crusted lesion of the occipital region of the scalp. Clinical examination noted skin abnormalities suggestive of occult dysraphism. Magnetic resonance imaging (MRI) was recommended, however, 40 days after this evaluation, and before the MRI could be performed, the girl presented with neurologic complications. Unfortunately, the diagnosis of dermoid cyst was made after the onset of severe complications that led to her death. The findings in this case emphasize the importance of more prompt MRI evaluation, particularly in cases where cranial or spinal dysraphism is suspected to have any connection to the skin as a pit or tract. Should we perform an urgent MRI for any cutaneous sign of dysraphism to avoid a dramatic evolution?     

Efficient Prediction of In Vitro Piroxicam Release and Diffusion From Topical Films Based on Biopolymers Using Deep Learning Models and Generative Adversarial Networks

The purpose of this study was to simultaneously predict the drug release and skin permeation of Piroxicam (PX) topical films based on Chitosan (CTS), Xanthan gum (XG) and its Carboxymethyl derivatives (CMXs) as matrix systems. These films were prepared by the solvent casting method, using Tween 80 (T80) as a permeation enhancer. All of the prepared films were assessed for their physicochemical parameters, their in vitro drug release and ex vivo skin permeation studies. Moreover, deep learning models and machine learning models were applied to predict the drug release and permeation rates. The results indicated that all of the films exhibited good consistency and physicochemical properties. Furthermore, it was noticed that when T80 was used in the optimal formulation (F8) based on CTS-CMX3, a satisfactory drug release pattern was found where 99.97% of PX was released and an amount of 1.18 mg/cm² was permeated after 48 h. Moreover, Generative Adversarial Network (GAN) efficiently enhanced the performance of deep learning models and DNN was chosen as the best predictive approach with MSE values equal to 0.00098 and 0.00182 for the drug release and permeation kinetics, respectively. DNN precisely predicted PX dissolution profiles with f₂ values equal to 99.99 for all the formulations.