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Liquid biopsy is a valuable emerging alternative to tissue biopsy with great potential in the noninvasive early diagnostics of cancer. Liquid biopsy based on single cell analysis can be a powerful approach to identify circulating tumor cells (CTCs) in the bloodstream and could provide new opportunities to be implemented in routine screening programs. Since CTCs are very rare, the accurate classification based on high-throughput and highly informative microscopy methods should minimize the false negative rates. Here, we show that holographic flow cytometry is a valuable instrument to obtain quantitative phase-contrast maps as input data for artificial intelligence (AI)-based classifiers. We tackle the problem of discriminating between A2780 ovarian cancer cells and THP1 monocyte cells based on the phase-contrast images obtained in flow cytometry mode. We compare conventional machine learning analysis and deep learning architectures in the non-ideal case of having a dataset with unbalanced populations for the AI training step. The results show the capacity of AI-aided holographic flow cytometry to discriminate between the two cell lines and highlight the important role played by the phase-contrast signature of the cells to guarantee accurate classification.

Teaching intervention planning is enhanced with an intentional course design that incorporates critical thinking in order to prepare the next generation of occupational therapy practitioners. The context for this study was a physical disabilities intervention course for an entry-level occupational therapy program that used Fink's Taxonomy of Significant Learning as a basis for learning outcomes. A novel formative intervention planning assignment required students to use the Rehabilitation Treatment Specification System (RTSS) as a framework to guide their thinking. A qualitative retrospective content analysis of student reflections at the end of the course revealed that the RTSS added value to their learning. Two main themes emerged from the student reflections; "Growth takes Practice" to use this framework effectively and the RTSS was perceived as a "Bridge from Classroom to Practice." These findings support the possible benefits of integrating this framework into occupational therapy curricula as a means to help students further develop critical thinking and clinical reasoning skills. Providing opportunities to scaffold learning may enhance the student learning experience and integration of the framework into future intervention planning and delivery.

Abstract: Lyman break galaxies (LBGs) are promising probes for clustering measurements at high redshift, z > 2, a region only covered so far by Lyman-α forest measurements. In this paper, we investigate the feasibility of selecting LBGs by exploiting the existence of a strong deficit of flux shortward of the Lyman limit, due to various absorption processes along the line of sight. The target selection relies on deep imaging data from the HSC and CLAUDS surveys in the g, r, z and u bands, respectively, with median depths reaching 27 AB in all bands. The selections were validated by several dedicated spectroscopic observation campaigns with DESI. Visual inspection of spectra has enabled us to develop an automated spectroscopic typing and redshift estimation algorithm specific to LBGs. Based on these data and tools, we assess the efficiency and purity of target selections optimised for different purposes. Selections providing a wide redshift coverage retain 57% of the observed targets after spectroscopic confirmation with DESI, and provide an efficiency for LBGs of 83±3%, for a purity of the selected LBG sample of 90±2%. This would deliver a confirmed LBG density of ~ 620 deg-2 in the range 2.3 < z < 3.5 for a r-band limiting magnitude r < 24.2. Selections optimised for high redshift efficiency retain 73% of the observed targets after spectroscopic confirmation, with 89±4% efficiency for 97±2% purity. This would provide a confirmed LBG density of ~ 470 deg-2 in the range 2.8 < z < 3.5 for a r-band limiting magnitude r < 24.5. A preliminary study of the LBG sample 3d-clustering properties is also presented and used to estimate the LBG linear bias. A value of b LBG = 3.3 ± 0.2  (stat.) is obtained for a mean redshift of 2.9 and a limiting magnitude in r of 24.2, in agreement with results reported in the literature.

The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra.

Granulicatella adiacens is a gram-positive coccus that is normally found in the human oral cavity and gastrointestinal and urogenital tracts but can rarely cause infection. When it does cause infection, Granulicatella adiacens has been most associated with bacteremia and endovascular infection, but to our knowledge, there are no previously documented cases of arteriovenous graft (AVG) infection. We present a case of Granulicatella adiacens bacteremia with associated AVG infection.

Wrinkling has recently attracted an increasing interest by suggesting a number of unforeseeable applications in many emerging material science and engineering fields. If guided and somehow designed, wrinkles could be in fact used as an alternative printing way for realizing complex surface geometries and thus employed as an innovative bottom-up process in the fabrication of nano- and micro-devices. For these reasons, the prediction of wrinkles of films adhering on flat as well as on structured substrata is a challenging task, genesis and development of the phenomenon being not yet completely understood both when thin membranes are coupled with soft supports and in cases where the geometry of the surfaces are characterized by complex three-dimensional profiles. Here we investigate the experimental formation of new intriguing and somehow unforeseeable wrinkled patterns achieved on periodic structures, by showing prediction through a new hybrid analytical-numerical strategy capable to overcome some common obstacles encountered in modeling film wrinkling on flat and 3D-shaped substrata. The proposed approach, which drastically reduces the computational effort, furnishes a helpful way for predicting both qualitative and quantitative results in terms of wrinkling patterns, magnitude and wavelength, by also allowing to follow the onset of film instabilities and the progressive evolution of the phenomenon until its final stage. Keywords: Thin film, Wrinkling, PDMS substrates, Lithium niobate crystals, FEM simulations

A measurement of a primordial non-Gaussianity (PNG) signal through late- or early-Universe probes has the potential to transform our understanding of the physics of the primordial Universe. While large-scale structure observables in principle contain vital information, interpreting these measurements is challenging due to poorly understood astrophysical effects. Luckily, N-body simulations, such as the abacuspng set presented in this study, consisting of 9 boxes, each of size Lbox=2 Gpc/h and particle mass of 1.01×1010M⊙/h, provide a viable path forward. As validation, we find good agreement between the simulations and our expectations from one-loop perturbation theory (PT) and the "separate universe"method for the matter bispectrum, matter power spectrum and the halo bias parameter associated with PNG, bφ. As a science application, we investigate the link between halo assembly bias and bφ for halo properties known to play a vital role in accurately predicting galaxy clustering: concentration, shear (environment), and accretion rate. We find a strong response for all three parameters, suggesting that the connection between bφ and the assembly history of halos needs to be taken into account by future PNG analyses. We further perform the first study of the bφ parameter from fits to early DESI data of the luminous red galaxy (LRG) and quasistellar object (QSO) samples and comment on the effect on fNL constraints for the allowed galaxy-halo models (note that σ[fNL]∝σ[bφ]bφ). We find that the error on fNL is 15, 8, 7 for the LRGs at z=0.5 and z=0.8 and QSOs at z=1.4, respectively, suggesting that a thorough understanding of galaxy assembly bias is warranted so as to perform robust high-precision analysis of local-type PNG with future surveys.

Peculiar velocities of galaxies and halos can be reconstructed from their spatial distribution alone. This technique is analogous to the baryon acoustic oscillations reconstruction, using the continuity equation to connect density and velocity fields. The resulting reconstructed velocities can be used to measure imprints of galaxy velocities on the cosmic microwave background like the kinematic Sunyaev-Zel'dovich effect or the moving lens effect. As the precision of these measurements increases, characterizing the performance of the velocity reconstruction becomes crucial to allow unbiased and statistically optimal inference. In this paper, we quantify the relevant performance metrics: the variance of the reconstructed velocities and their correlation coefficient with the true velocities. We show that the relevant velocities to reconstruct for kSZ and moving lens are actually the halo - rather than galaxy - velocities. We quantify the impact of redshift-space distortions, photometric redshift errors, satellite galaxy fraction, incorrect cosmological parameter assumptions and smoothing scale on the reconstruction performance. We also investigate hybrid reconstruction methods, where velocities inferred from spectroscopic samples are evaluated at the positions of denser photometric samples. We find that using exclusively the photometric sample is better than performing a hybrid analysis. The 2 Gpc/h length simulations from abacussummit with realistic galaxy samples for DESI and Rubin LSST allow us to perform this analysis in a controlled setting. In the companion paper [B. Hadzhiyska, S. Ferraro, B. Ried Guachalla, and E. Schaan, companion paper, Phys. Rev. D 109, 103534 (2024).PRVDAQ2470-001010.1103/PhysRevD.109.103534], we further include the effects of evolution along the light cone and give realistic performance estimates for DESI luminous red galaxies, emission line galaxies, and Rubin LSST-like samples.

UNLABELLED: Gonorrhea, caused by the bacterium Neisseria gonorrhoeae (Gc), is characterized by neutrophilic influx to infection sites. Gc has developed mechanisms to resist killing by neutrophils that include modifications to its surface lipooligosaccharide (LOS). One such LOS modification is sialylation: Gc sialylates its terminal LOS sugars with cytidine-5-monophosphate-N-acetylneuraminic acid, which is scavenged from the host using LOS sialyltransferase (Lst) since Gc cannot make its sialic acid. Sialylation enables sensitive strains of Gc to resist complement-mediated killing in a serum-dependent manner. However, little is known about the contribution of sialylation to complement-independent, direct Gc-neutrophil interactions. In the absence of complement, we found sialylated Gc expressing opacity-associated (Opa) proteins decreased the oxidative burst and granule exocytosis from primary human neutrophils. In addition, sialylated Opa+ Gc survived better than vehicle treated or Δlst Gc when challenged with neutrophils. However, Gc sialylation did not significantly affect Opa-dependent association with or internalization of Gc by neutrophils. Previous studies have implicated sialic acid-binding immunoglobulin-type lectins (Siglecs) in modulating neutrophil interactions with sialylated Gc. Blocking neutrophil Siglecs with antibodies that bind to their extracellular domains eliminated the ability of sialylated Opa+ Gc to suppress the oxidative burst and resist neutrophil killing. These findings highlight a new role for sialylation in Gc evasion of human innate immunity, with implications for the development of vaccines and therapeutics for gonorrhea. IMPORTANCE: Neisseria gonorrhoeae, the bacterium that causes gonorrhea, is an urgent global health concern due to increasing infection rates, widespread antibiotic resistance, and its ability to thwart protective immune responses. The mechanisms by which Gc subverts protective immune responses remain poorly characterized. One way N. gonorrhoeae evades human immunity is by adding sialic acid that is scavenged from the host onto its lipooligosaccharide, using the sialyltransferase Lst. Here, we found that sialylation enhances N. gonorrhoeae survival from neutrophil assault and inhibits neutrophil activation, independently of the complement system. Our results implicate bacterial binding of sialic acid-binding lectins (Siglecs) on the neutrophil surface, which dampens neutrophil antimicrobial responses. This work identifies a new role for sialylation in protecting N. gonorrhoeae from cellular innate immunity, which can be targeted to enhance the human immune response in gonorrhea.

We present tomographic measurements of structure growth using cross-correlations of Atacama Cosmology Telescope (ACT) DR6 and Planck cosmic microwave background (CMB) lensing maps with the unWISE Blue and Green galaxy samples, which span the redshift ranges 0.2 ≲ z ≲ 1.1 and 0.3 ≲ z ≲ 1.8, respectively. We improve on prior unWISE cross-correlations not just by making use of the new, high-precision ACT DR6 lensing maps, but also by including additional spectroscopic data for redshift calibration and by analyzing our measurements with a more flexible theoretical model. We determine the amplitude of matter fluctuations at low redshifts (z ≃ 0.2-1.6), finding S 8 ≡ σ 8 ( Ω m / 0.3 ) 0.5 = 0.813 ± 0.021 using the ACT cross-correlation alone and S 8 = 0.810 ± 0.015 with a combination of Planck and ACT cross-correlations; these measurements are fully consistent with the predictions from primary CMB measurements assuming standard structure growth. The addition of baryon acoustic oscillation data breaks the degeneracy between σ 8 and Ωm , allowing us to measure σ 8 = 0.813 ± 0.020 from the cross-correlation of unWISE with ACT and σ 8 = 0.813 ± 0.015 from the combination of cross-correlations with ACT and Planck. These results also agree with the expectations from primary CMB extrapolations in ΛCDM cosmology; the consistency of σ 8 derived from our two redshift samples at z ∼ 0.6 and 1.1 provides a further check of our cosmological model. Our results suggest that structure formation on linear scales is well described by ΛCDM even down to low redshifts z ≲ 1.

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg2 over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg2 using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg2 program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.