Microscopic internal spermatic-inferior epigastric vein anastomosis for treating left varicocele.

OBJECTIVE: To evaluate the clinical efficacy of microscopic internal spermatic-inferior epigastric vein anastomosis in the treatment of left varicocele and compare it with microscopic spermatic vein ligation for the same condition. METHODS: A retrospective analysis of 74 patients with left varicocele between July 2020 and July 2022 was performed. The patients were divided into two groups based on the surgical method used. Group A consisted of 37 patients who underwent microscopic internal spermatic-inferior epigastric vein anastomosis, while Group B consisted of 37 patients who underwent microscopic spermatic vein ligation. Comparison of preoperative and postoperative semen quality, reproductive hormone levels, scrotal ultrasound results, duration of surgery, length of hospital stay, postoperative recurrence rate, and occurrence of complications with a follow-up time of 12 mo between two groups. RESULTS: Both groups showed significant improvements in semen quality and serum reproductive hormone levels. The Group A demonstrated significantly improved sperm forward motility compared to Group B, but had longer operation times and hospital stays (P < 0.05). After 1 year of follow-up, 8 partners in Group A and 6 partners in Group B achieved natural conception, with no significant difference between the two groups. There were no recurrences observed in either group during the follow-up period, and no significant statistical differences were found in other postoperative observation indicators. CONCLUSIONS: Both microscopic internal spermatic-inferior epigastric vein anastomosis and microscopic spermatic vein ligation are effective surgical methods for treating left varicocele. Anastomosis surgery provides greater improvement in sperm motility, although it is associated with longer operation times and hospital stays.

Computational investigation of the inhibitory interaction of IRF3 and SARS-CoV-2 accessory protein ORF3b.

ORF3b is one of the SARS-CoV-2 accessory proteins. Previous experimental study suggested that ORF3b prevents IRF3 translocating to nucleus. However, the biophysical mechanism of ORF3b-IRF3 interaction is elusive. Here, we explored the conformation ensemble of ORF3b using all-atom replica exchange molecular dynamics simulation. Disordered ORF3b has mixed α-helix, ß-turn and loop conformers. The potential ORF3b-IRF3 binding modes were searched by docking representative ORF3b conformers with IRF3, and 50 ORF3b-IRF3 complex poses were screened using molecular dynamics simulations ranging from 500 to 1000 ns. We found that ORF3b binds IRF3 predominantly on its CBP binding and phosphorylated pLxIS motifs, with CBP binding site has the highest binding affinity. The ORF3b-IRF3 binding residues are highly conserved in SARS-CoV-2. Our results provided biophysics insights into ORF3b-IRF3 interaction and explained its interferon antagonism mechanism.

Evaluation of Molecular Simulations and Deep Learning Prediction of Antibodies' Recognition of TRBC1 and TRBC2.

T cell receptor ß-chain constant (TRBC) is a promising class of cancer targets consisting of two highly homologous proteins, TRBC1 and TRBC2. Developing targeted antibody therapeutics against TRBC1 or TRBC2 is expected to eradicate the malignant T cells and preserve half of the normal T cells. Recently, several antibody engineering strategies have been used to modulate the TRBC1 and TRBC2 specificity of antibodies. Here, we used molecular simulation and artificial intelligence methods to quantify the affinity difference in antibodies with various mutations for TRBC1 and TRBC2. The affinity of the existing mutants was verified by FEP calculations aided by the AI. We also performed long-time molecular dynamics simulations to reveal the dynamical antigen recognition mechanisms of the TRBC antibodies.

Recent Progress in Antibody Epitope Prediction.

Recent progress in epitope prediction has shown promising results in the development of vaccines and therapeutics against various diseases. However, the overall accuracy and success rate need to be improved greatly to gain practical application significance, especially conformational epitope prediction. In this review, we examined the general features of antibody-antigen recognition, highlighting the conformation selection mechanism in flexible antibody-antigen binding. We recently highlighted the success and warning signs of antibody epitope predictions, including linear and conformation epitope predictions. While deep learning-based models gradually outperform traditional feature-based machine learning, sequence and structure features still provide insight into antibody-antigen recognition problems.

Accelerating antibody discovery and design with artificial intelligence: Recent advances and prospects.

Therapeutic antibodies are the largest class of biotherapeutics and have been successful in treating human diseases. However, the design and discovery of antibody drugs remains challenging and time-consuming. Recently, artificial intelligence technology has had an incredible impact on antibody design and discovery, resulting in significant advances in antibody discovery, optimization, and developability. This review summarizes major machine learning (ML) methods and their applications for computational predictors of antibody structure and antigen interface/interaction, as well as the evaluation of antibody developability. Additionally, this review addresses the current status of ML-based therapeutic antibodies under preclinical and clinical phases. While many challenges remain, ML may offer a new therapeutic option for the future direction of fully computational antibody design.

Chemo- and Enantioselective Hydrogenation of α-Formyl Enamides: An Efficient Access to Chiral α-Amido Aldehydes.

In order to effectively synthesize chiral α-amino aldehydes, which have a wide range of potential applications in organic synthesis and medicinal chemistry, a highly chemo- and enantioselective hydrogenation of α-formyl enamides has been developed, catalyzed by a rhodium complex of a P-stereogenic bisphosphine ligand. Under different hydrogen pressures, the chiral α-amido aldehydes and ß-amido alcohols were obtained in high yields (97-99 %) and with excellent chemo- and enantioselectivities (up to >99.9 % ee). The hydrogenation can be carried out on a gram scale and with a high substrate/catalyst ratio (up to 20 000 S/C), and the hydrogenated products were further converted into several important chiral products. Computations of the catalytic cycle gave a clear description for the R/S pathways, provided a reasonable explanation for the enantioselectivity, and revealed several other specific features.

Palladium-catalyzed direct sulfonylation of C-H bonds with the insertion of sulfur dioxide.

A palladium-catalyzed direct sulfonylation of C-H bonds with the insertion of sulfur dioxide under mild conditions is reported. The sulfonylative couplings with the insertion of sulfur dioxide into C-H bonds are effective, and two classes of sulfonylative products are formed in moderate to good yields by the combination of radical chemistry and palladium-catalyzed C-H activation.