Emerging evidence suggests that liquid–liquid phase separation (LLPS) represents a vital and ubiquitous phenomenon underlying the formation of membraneless organelles in eukaryotic cells (also known as biomolecular condensates or droplets). Recent studies have revealed evidences that indicate that LLPS plays a vital role in human health and diseases. In this review, we describe our current understanding of LLPS and summarize its physiological functions. We further describe the role of LLPS in the development of human diseases. Additionally, we review the recently developed methods for studying LLPS. Although LLPS research is in its infancy—but is fast-growing—it is clear that LLPS plays an essential role in the development of pathophysiological conditions. This highlights the need for an overview of the recent advances in the field to translate our current knowledge regarding LLPS into therapeutic discoveries.

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Approximate queries on a collection of strings are important in many applications such as record linkage, spell checking, and Web search, where inconsistencies and errors exist in data as well as queries. Several existing algorithms use the concept of "grams," which are substrings of strings used as signatures for the strings to build index structures. A recently proposed technique, called VGRAM, improves the performance of these algorithms by using a carefully chosen dictionary of variable-length grams based on their frequencies in the string collection. Since an index structure using fixed-length grams can be viewed as a special case of VGRAM, a fundamental problem arises naturally: what is the relationship between the gram dictionary and the performance of queries? We study this problem in this paper. We propose a dynamic programming algorithm for computing a tight lower bound on the number of common grams shared by two similar strings in order to improve query performance. We analyze how a gram dictionary affects the index structure of the string collection and ultimately the performance of queries. We also propose an algorithm for automatically computing a dictionary of high-quality grams for a workload of queries. Our experiments on real data sets show the improvement on query performance achieved by these techniques. To our best knowledge, this study is the first cost-based quantitative approach to deciding good grams for approximate string queries.

Inhibiting Plasmodium development in mosquitoes will block malaria transmission. Fibrinogen-related protein 1 (FREP1) is critical for parasite infection in Anopheles gambiae and facilitates Plasmodium invasion in mosquitoes through interacting with gametocytes and ookinetes. To test the hypothesis that small molecules that disrupt this interaction will prevent parasites from infecting mosquitoes, we developed an ELISA-based method to screen a fungal extract library. We obtained a candidate fungal extract of Aspergillus niger that inhibited the interaction between FREP1 and P. falciparum infected cells by about 92%. The inhibition specificity was confirmed by immunofluorescence assays. Notably, feeding mosquitoes with the candidate fungal extract significantly inhibited P. falciparum infection in the midgut without cytotoxicity or inhibition of the development of P. falciparum gametocytes or ookinetes. A bioactive natural product that prevents FREP1 from binding to gametocytes or ookinetes was isolated and identified as P-orlandin. Importantly, the nontoxic orlandin significantly reduced P. falciparum infection intensity in mosquitoes. Therefore, disruption of the interaction between FREP1 and parasites effectively reduces Plasmodium infection in mosquitoes. Targeting FREP1 with small molecules is thus an effective novel approach to block malaria transmission.