Metformin improves boar sperm quality via 5'-AMP-activated protein kinase-mediated energy metabolism in vitro.

Sperm are specialized cells that require adenosine triphosphate (ATP) to support their function. Maintaining sperm energy homeostasis in vitro is vitally important to improve the efficacy of boar sperm preservation. Metformin can activate 5'-AMP-activated protein kinase (AMPK) to improve metabolic flexibility and maintain energy homeostasis. Thus, the aim of the present study was to investigate whether metformin can improve boar sperm quality through AMPK mediation of energy metabolism. Sperm motility parameters, membrane integrity, acrosome integrity, mitochondrial membrane potential (ΔΨ m), ATP content, glucose uptake, and lactate efflux were analyzed. Localization and expression levels of AMPK and phospho-Thr 172-AMPK (p-AMPK) were also detected by immunofluorescence and western blotting. We found that metformin treatment significantly increased sperm motility parameters, ΔΨ m, and ATP content during storage at 17 °C. Moreover, results showed that AMPK was localized at the acrosomal region, connecting piece, and midpiece of sperm and p-AMPK was distributed at the post-acrosomal region, connecting piece, and midpiece. When sperm were incubated with metformin for 4 h at 37 °C, sperm motility parameters, ΔΨ m, ATP content, p-AMPK, glucose uptake, and lactate efflux all significantly increased, whereas the addition of Compound C treatment, an inhibitor of AMPK, counteracted these positive effects. Together, our results suggest that metformin promotes AMPK activation, which contributes to the maintenance of energy hemostasis and mitochondrial activity, thereby maintaining boar sperm functionality and improving the efficacy of semen preservation.

Sample sizes in dosage investigational clinical trials: a systematic evaluation.

The main purpose of investigational phase II clinical trials is to explore indications and effective doses. However, as yet, there is no clear rule and no related published literature about the precise suitable sample sizes to be used in phase II clinical trials. To explore this, we searched for clinical trials in the ClinicalTrials.gov registry using the keywords "dose-finding" or "dose-response" and "Phase II". The time span of the search was September 20, 1999, to December 31, 2013. A total of 2103 clinical trials were finally included in our review. Regarding sample sizes, 1,156 clinical trials had <40 participants in each group, accounting for 55.0% of the studies reviewed, and only 17.2% of the studies reviewed had >100 patient cases in a single group. Sample sizes used in parallel study designs tended to be larger than those of crossover designs (median sample size 151 and 37, respectively). In conclusion, in the earlier phases of drug research and development, there are a variety of designs for dosage investigational studies. The sample size of each trial should be comprehensively considered and selected according to the study design and purpose.

[Quality control of clinical data management based on EDC].

With the wide application of electronic data management (EDC), the data management is shifting to a new mode. In order to recognize the advantages of EDC, we choose 20 representative registered clinical trials, which involve 5 404 subjects and 321 sites. We found that EDC has many beneficial impacts on the course of clinical trial data management, including the process of data collection, data cleaning, data quality control and clinical trial decision-making. The result also provides a reference for the adoption of EDC in clinical trials.

An S-curve-based approach of identifying biological sequences.

The main idea of S-curve diagram is to assign different angle values (from 0 degrees to 180 degrees ) to different nucleotide acid residues or to different protein amino acids, and then according to cos alpha(j) and sin alpha(j), the values are accumulated to construct an S-curve diagram, which is in strict one-to-one correspondence with the biological sequence. In addition, the S-curve diagram proves to be without the degeneracy phenomenon, so that both the degeneracy problem represented by diagrams and the problem of visualization for biological sequence data are solved. Meanwhile, a new approach to differentiate the similarity of biological sequences--the degree of similarity--is put forward on the basis of the S-curve diagram. To put it in detail, the least square approach is first adopted to obtain a straight line equation according to the S-curve diagram, then according to the distance formula of the point to the straight line, the average ratio of square sum for the distance between the S-curve and the straight line is calculated, and finally, the similarity of the biological sequences is presented by the new standard--the degree of similarity. As is shown by the experimental results, the S-curve diagram can better represent biological sequences (such as protein's) within Cartesian coordinate system, and the mutation point of biological sequence. Thus, it turns out that the new standard-the degree of similarity is of obviously great advantage.