Should I consider a two sample t test?

We have a series of tests that we can consider such as two sample t test, wilcoxon rank sum, signed rank, paired t test, etc. But here since we don't have the actual data, this means that I am limited in what tests I could use. So for this I did not assume equal variance but the samples are large enough to assume normality. The groups are independent from one another and the observations are as well (this may work here but there could be some dependence since the flies were in the same cages). In this case would it be appropriate if I conduct a two sample t test (unequal variances)?

The usual F-test for equality of variances has the test statistic $8^2/2^2 = 16$ with $199$ degrees of freedom in each of the numerator and denominator, and the probability that an F-distributed random variable with those degrees of freedom would exceed $16$ is effectively $0$. This strongly points to unequal variances. I think the validity of this test may be sensitive to the assumption of normality of the two distributions, and we have no way to assess that without seeing more than summary statistics.