Exceeding the limits of algorithmic self-calibration in super-resolution imaging

Fourier ptychographic microscopy is a computational imaging technique that provides quantitative phase information and high resolution over a large field-of-view. Although the technique presents numerous advantages over conventional microscopy, model mismatch due to unknown optical aberrations can significantly limit reconstruction quality. Many attempts to address this issue rely on embedding pupil recovery into the reconstruction algorithm. In this paper we demonstrate the limitations of a purely algorithmic approach and evaluate the merits of implementing a simple, dedicated calibration procedure. In simulations, we find that for a target sample reconstruction error, we can image without any aberration corrections up to a maximum aberration magnitude of $\lambda$/40. When we use algorithmic self-calibration, we can increase the aberration magnitude up to $\lambda$/10, and with our in situ speckle calibration technique, this working range is extended further to a maximum aberration magnitude of $\lambda$/3. Hence, one can trade-off complexity for accuracy by using a separate calibration process, which is particularly useful for larger aberrations

Clinical characteristics of subjects in this study.

Clinical characteristics of subjects in this study.</p

Microbial diversity and species richness of upper and lower airway microbiome in CF children and non-CF disease controls.

(A) Shannon indices were calculated to denote microbial diversity and are plotted on the y-axis. Upper airway microbiome was sampled using throat swab, and lower airway microbiome was sampled by bronchioalveolar lavage (BAL). Values were compared using unpaired t-test. (B) The number of OTUs for each sample is plotted on the y-axis. CF = cystic fibrosis. Non-CF denotes non-CF disease controls. *** p < 0.001, ** p<0.01, ns = not significant.</p

Phylum level composition of upper and lower airway microbiome sampled concurrently in each subject.

Proportions of microbial taxa are shown on the y-axis, and paired upper and lower airway samples are shown side by side (left: BAL; right: Throat) for comparison. Top: CF children; bottom: non-CF controls.</p

Plots showing clustering of airway microbiome communities.

(A) Upper airway and lower airway microbiome of CF (left) and non-CF (right) children represented by nonmetric multidimensional scaling (NMDS) of pairwise weighted Unifrac distances. Weighted UniFrac distance matrices were generated using QIIME v 1.8.0 and visualized via NMDS in the R statistical environment using the vegan package. (B) Lower (left) and upper airway (right) microbial communities stratified by CF and non-CF status represented by NMDS of pairwise weighted Unifrac distances. Statistical significance of clustering by group was determined using PERMANOVA.</p

Lung microbiome diversity and inflammation in CF and non-CF controls.

(A) Neutrophil counts in CF and non-CF controls. Neutrophil count in the BAL was used as a surrogate for lung inflammation, and is shown in the y-axis. ** P = 0.0054 (Mann-Whitney U Test). (B) Spearman Correlation between neutrophil counts and microbial diversity (left) or species richness (right) in the BAL. Shannon diversity and species richness are shown in the y-axis as a function of BAL neutrophil counts.</p

Relative abundance of major bacterial taxa at the family level in upper and lower airways of CF and non-CF children.

Proportion of reads for each family is shown on the y-axis.</p

Relative proportions of microbial taxa of the aggregate microbiome at the phylum level.

(A) microbial composition of the upper airways of CF children (left) and non-CF controls (right), (B) microbial composition of the lower airways of CF children (left) and non-CF controls (right). Each color denotes the proportion of taxa at the level of the phylum indicated.</p

Upper versus lower airway microbiome and metagenome in children with cystic fibrosis and their correlation with lung inflammation - Fig 6

Differentially abundant gene functions comparing CF and non-CF metagenomes in (A) lower and (B) upper airways. Functional categories of genes of the airway metagenome were predicted using PICRUSt, and differentially abundant functions were then identified using linear discriminant analysis (LDA) coupled with effect size measurements (LEfSe). Gene functions enriched in non-CF metagenome are indicated with positive linear discriminant analysis scores (green), and functions differentially enriched in CF metagenome are indicated with negative linear discriminant analysis scores (red).</p

Early Warning System for Illicit Drug Use at Large Public Events: Trace Residue Analysis of Discarded Drug Packaging Samples

Inspired by Locard’s exchange principle, which states “every contact leaves a trace”, a trace residue sampling strategy has been developed for the analysis of discarded drug packaging samples (DPS), as part of an early warning system for illicit drug use at large public events including music/dance festivals. Using direct analysis in real time/mass spectrometry and tandem mass spectrometry, rapid and high-throughput identification and characterization of a wide range of illicit drugs and adulterant substances was achieved, including in complex polydrug mixtures and at low relative ion abundances. A total of 1362 DPS were analyzed either off-site using laboratory-based instrumentation or on-site and in close to real time using a transportable mass spectrometer housed within a mobile analytical laboratory, with each analysis requiring less than 1 min per sample. Of the DPS analyzed, 92.2% yielded positive results for at least one of 15 different drugs and/or adulterants, including cocaine, MDMA, and ketamine, as well as numerous novel psychoactive substances (NPS). Also, 52.6% of positive DPS were found to contain polydrug mixtures, and a total of 42 different drug and polydrug combinations were observed throughout the study. For analyses performed on-site, reports to key stakeholders including event organizers, first aid and medical personnel, and peer-based harm reduction workers could be provided in as little as 5 min after sample collection. Following risk assessment of the potential harms associated with their use, drug advisories or alerts were then disseminated to event staff and patrons and subsequently to the general public when substances with particularly toxic properties were identified