In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Example Input: Although single cell RNA sequencing studies have begun providing compendia of cell expression profiles, it has proven more difficult to systematically identify and localize all molecular cell types in individual organs to create a full molecular cell atlas. Here we describe droplet-and plate-based single cell RNA sequencing applied to ~75,000 human lung and blood cells, combined with a multi-pronged cell annotation approach, which have allowed us to define the gene expression profiles and anatomical locations of 58 cell populations in the human lung, including 41 of 45 previously known cell types or subtypes and 14 new ones. This comprehensive molecular atlas elucidates the biochemical functions of lung cell types and the cell-selective transcription factors and optimal markers for making and monitoring them; defines the cell targets of circulating hormones and predicts local signaling interactions including sources and targets of chemokines in immune cell trafficking and expression changes on lung homing; and identifies the cell types directly affected by lung disease genes and respiratory viruses. Comparison to mouse identified 17 molecular types that appear to have been gained or lost during lung evolution and others whose expression profiles have been substantially altered, revealing extensive plasticity of cell types and cell-type-specific gene expression during organ evolution including expression switches between cell types. This atlas provides the molecular foundation for investigating how lung cell identities, functions, and interactions are achieved in development and tissue engineering and altered in disease and evolution. All rights reserved. No reuse allowed without permission.
Example Output: A molecular cell atlas of the human lung from single cell RNA sequencing

Example Input: Low cost, high throughput, easy quantitation, and rich descriptions have made gene expression profiling generated by DNA microarrays an optimal approach for describing host transcriptional responses (HTRs). However, efforts to characterize the landscape of HTRs to diverse pathogens are far from offering a comprehensive view. Here, we developed an HTR Connectivity Map based on systematic assessment of pairwise similarities of HTRs to 50 clinically important human pathogens using 1353 gene-expression profiles generated from >60 human cells/tissues. These 50 pathogens were further partitioned into eight robust "HTR communities" (i.e., groups with more consensus internal HTR similarities). These communities showed enrichment in specific infection attributes and differential gene expression patterns. Using query signatures of HTRs to external pathogens, we demonstrated four distinct modes of HTR associations among different pathogens types/class, and validated the reliability of the HTR community divisions for differentiating and categorizing pathogens from a host-oriented perspective. These findings provide a first-generation HTR Connectivity Map of 50 diverse pathogens, and demonstrate the potential for using annotated HTR community to detect functional associations among infectious pathogens.
Example Output: Inferring Infection Patterns Based on a Connectivity Map of Host Transcriptional Responses

Example Input: Waste ashes from three types of hospital waste (HW) incinerators, built in SARS (Severe Acute Respiratory Syndrome) period and currently running in China, were collected and polycyclic aromatic hydrocarbons (PAH) properties in the ashes were investigated. The mean ∑PAH levels in the waste ashes varied widely from 4.16 mg kg − 1 to 198.92 mg kg − 1 , and the mean amounts of carcinogenic PAHs ranged from 0.74 to 96.77 mg kg − 1 , exceeding the limits regulated by several countries. Among the three types of incinerators, two medium-scale incinerators generated relatively high levels of PAHs (mean ∑PAH 22.50 and 198.92 mg kg − 1 ) compared to small-scale and large-scale incinerators (mean ∑PAH 4.16 and 16.43 mg kg − 1 ). Bottom ashes were dominated by low molecular weight PAHs (LM-PAH; containing two-to three-ringed PAHs) and medium molecular weight PAHs (MM-PAH; containing four-ringed PAHs), while fly ashes were abundant in MM-PAH and high molecular weight PAHs (HM-PAH, containing five-to six-ringed PAHs). Statistical analysis indicated that there was a positive relationship (R 2 = 0.88) between organic matter and total PAHs thus it has the potential to be used as an indicator for PAHs in HW ashes. Moreover, it was found that PAHs in the ashes correlated highly with some metallic elements either positively (e.g. Fe, Ti, Mg) or negatively (Ca), indicating that these elements might promote or prevent PAH formation during HW combustion. Although bottom ash resulted from HW incinerators has not been classified as hazardous material, the results of this study indicated that this type of waste ash contained high levels of PAHs thus need special treatment before landfill. Hospital waste ash Carcinogenic substance Molecular weight distribution Heavy metal ⁎ Corresponding author. Tel.: +86 10 6284 9515; fax: +86 10 6289515. a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m w w w. e l s e v i e r. c o m / l o c a t e / s c i t o t e n v
Example Output:
Levels of polycyclic aromatic hydrocarbons in different types of hospital waste incinerator ashes