The Cutting-edge of CRISPR for Cancer Treatment and its Future Prospects

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a versatile technology that allows precise modification of genes. One of its most promising applications is in cancer treatment. By targeting and editing specific genes involved in cancer development and progression, CRISPR has the potential to become a powerful tool in the fight against cancer. This review aims to assess the recent progress in CRISPR technology for cancer research and to examine the obstacles and potential strategies to address them. The two most commonly used CRISPR systems for gene editing are CRISPR/Cas9 and CRISPR/Cas12a. CRISPR/Cas9 employs different repairing systems, including homologous recombination (HR) and nonhomologous end joining (NHEJ), to introduce precise modifications to the target genes. However, off-target effects and low editing efficiency are some of the main challenges associated with this technology. To overcome these issues, researchers are exploring new delivery methods and developing CRISPR/Cas systems with improved specificity. Moreover, there are ethical concerns surrounding using CRISPR in gene editing, including the potential for unintended consequences and the creation of genetically modified organisms. It is important to address these issues through rigorous testing and strict regulations. Despite these challenges, the potential benefits of CRISPR in cancer therapy cannot be overlooked. By introducing precise modifications to cancer cells, CRISPR could offer a targeted and effective treatment option for patients with different types of cancer. Further investigation and development of CRISPR technology are necessary to overcome the existing challenges and harness its full potential in cancer therapy.

Renal outcome and evolution of disease activity in Chinese lupus patients after renal transplantation

Lupus nephritis constitutes the major cause of morbidity and mortality in SLE. The long-term outcome of renal transplantation in lupus patients remains controversial, and the recurrence of lupus activity is a major concern. This study aims to determine the long-term outcome of renal transplantation in Chinese lupus patients and the evolution of lupus activity. A total of 23 lupus patients undergoing renal transplantation were enrolled and compared with 94 matched controls. The overall patient and graft survival rates at 10 years post-transplant in lupus group were not different from the control group (95.2% and 57.7% vs. 90.7% and 66.3%). Recurrence of lupus nephritis in renal allograft and flare-ups of lupus activity were not observed in this study. The SLE group had less acute rejection than the control group (20.4% vs. 29.8%, P<0.05). The infection rate between the two groups was similar (39.1% vs. 51.1%, P=0.427), although SLE group had a significantly higher rate of developing avascular necrosis (17.4% vs. 2.1%, P=0.04). In conclusion, patient and graft survival rates and other major complications in Chinese lupus patients are comparable to non-lupus transplant recipients caused by other diseases. Chinese patients with SLE are suitable candidates for renal transplantation.

Severe emphysematous pyelonephritis in a renal allograft: successful treatment with percutaneous drainage and antibiotics

Emphysematous pyelonephritis is a rare, severe gas-forming infection of the kidney. Herein we report a case of a 51-year-old man who had received a cadaveric renal transplant 12 years ago. Post-transplant diabetes mellitus occurred 8 years later. He experienced urinary tract infection with graft pain one week before admission and presented with septic shock at the emergency room. Plain X-ray of the abdomen showed retroperitoneal air. A computed tomography scan of the abdomen showed retroperitoneal and extraperitoneal air being released from the graft kidney. These findings were compatible with extensive emphysematous pyelonephritis. The patient underwent percutaneous drainage. Blood culture and urine culture yielded Escherichia coli. After repeated percutaneous drainage and strong antibiotics for a prolonged period, the patient finally recovered.

The hybrid grey-based models for temperature prediction

In this paper several grey-based models are applied to temperature prediction problems. Standard normal distribution, linear regression, and fuzzy techniques are respectively integrated into the grey model to enhance the embedded GM(1, 1), a single variable first order grey model, prediction capability. The original data are preprocessed by the statistical method of standard normal distribution such that they will become normally distributed with a mean of zero and a standard deviation of one. The normalized data are then used to construct the grey model. Due to the inherent error between the predicted and actual outputs, the grey model is further supplemented by either the linear regression or fuzzy method or both to improve the prediction accuracy. Results from predicting the monthly temperatures for two different cities demonstrate that each proposed hybrid methodology can somewhat reduce the prediction errors. When both the statistics and fuzzy methods are incorporated with the grey model, the prediction capability of the hybrid model is quite satisfactory. We repeat the prediction problems in neural networks and the results are also presented for comparison.