Let $X_n:\Omega\to \mathbb{R}$ be an integrable random variable converging to integrable $X$ almost surely. I know that this does not mean $\{X_n:n\in\mathbb{N}\}$ is uniformly integrable.
But is there are any conditions that we can impose on $X_n$ or $X$ to guarantee uniform integrability (except for being dominated by an integrable non-negative random variable $Y$ i.e $|X_n| < Y$)?
Ideas of proof: (i) implies (iii). Fix $\varepsilon \gt 0$. By uniform integrability, there exists a $\delta$ such that if $\mathbb P(A)\leqslant \delta$, then $\mathbb E \left\lvert X\mathbf 1_A\right\rvert\lt\varepsilon$ and for all $n$, $\mathbb E \left\lvert X_n\mathbf 1_A\right\rvert\lt\varepsilon$. By Egoroff's theorem, there exists a set $S$ such that $\sup_{\omega\in S}\left\lvert X_n(\omega)-X(\omega)\right\rvert\to 0$ and the measure of $\Omega\setminus S$ is smaller than $\delta$. Then $$ \mathbb E\left\lvert X_n-X\right\rvert\leqslant \sup_{\omega\in S}\left\lvert X_n(\omega)-X(\omega)\right\rvert+\mathbb E \left\lvert X_n\mathbf 1_{\Omega\setminus S}\right\rvert+\mathbb E \left\lvert X\mathbf 1_{\Omega\setminus S}\right\rvert\leqslant \sup_{\omega\in S}\left\lvert X_n(\omega)-X(\omega)\right\rvert+2\varepsilon. $$
(iii) implies (i) does not require uniform integrability.
Implication $(ii) \Rightarrow (iii)$ can be established using Fatou's lemma with $Y_n:=\left\lvert X\right\rvert+\left\lvert X_n\right\rvert-\left\lvert X_n-X\right\rvert$. The converse is not hard.