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Summary Azoospermia factor (AZF) genes on the long arm of the human Y chromosome are involved in spermatogenesis, and microdeletions in the AZF region have been recognised to be the second major genetic cause of spermatogenetic failure resulting in male infertility. While screening for these microdeletions can avoid unnecessary medical and surgical treatments, current methods are generally time‐consuming. Therefore, we established a new method to detect and analyse microdeletions in the AZF region quickly, safely and efficiently. In total, 1,808 patients with spermatogenetic failure were recruited from three hospitals in southern China, of which 600 patients were randomly selected for screening for Y chromosome microdeletions in AZF regions employing real‐time polymerase chain reaction with a TaqMan probe. In our study, of 1,808 infertile patients, 150 (8.3%) were found to bear microdeletions in the Y chromosome using multiplex PCR, while no deletions were found in the controls. Among the AZF deletions detected, two were in AZFa, three in AZFb, 35 in AZFc, three in AZFb+c and two in AZFa+b+c. Our method is fast—it permits the scanning of DNA from a patient in one and a half hours—and reliable, minimising the risk of cross‐contamination and false‐positive and false‐negative results.

Recent years have seen a resurgence of interest in inexpensive low magnetic field (< 0.3 T) MRI systems mainly due to advances in magnet, coil and gradient set designs. Most of these advances have focused on improving hardware and signal acquisition strategies, and far less on the use of advanced image reconstruction methods to improve attainable image quality at low field. We describe here the use of our end-to-end deep neural network approach (AUTOMAP) to improve the image quality of highly noise-corrupted low-field MRI data. We compare the performance of this approach to two additional state-of-the-art denoising pipelines. We find that AUTOMAP improves image reconstruction of data acquired on two very different low-field MRI systems: human brain data acquired at 6.5 mT, and plant root data acquired at 47 mT, demonstrating SNR gains above Fourier reconstruction by factors of 1.5- to 4.5-fold, and 3-fold, respectively. In these applications, AUTOMAP outperformed two different contemporary image-based denoising algorithms, and suppressed noise-like spike artifacts in the reconstructed images. The impact of domain-specific training corpora on the reconstruction performance is discussed. The AUTOMAP approach to image reconstruction will enable significant image quality improvements at low-field, especially in highly noise-corrupted environments.

T-cell exhaustion was originally identified during chronic infection in mice, and was subsequently observed in humans with cancer. The exhausted T cells in the tumor microenvironment show overexpressed inhibitory receptors, decreased effector cytokine production and cytolytic activity, leading to the failure of cancer elimination. Restoring exhausted T cells represents an inspiring strategy for cancer treatment, which has yielded promising results and become a significant breakthrough in the cancer immunotherapy. In this review, we overview the updated understanding on the exhausted T cells in cancer and their potential regulatory mechanisms and discuss current therapeutic interventions targeting exhausted T cells in clinical trials.

Three-dimensional printing (3DP) is a computer-controlled additive manufacturing technique which is able to repeatedly and accurately fabricate objects with complicated geometry and internal structures. After 30 years of fast development, 3DP has become a mainstream manufacturing process in various fields. This study focuses on identifying the most suitable 3DP material from five targeted available 3DP materials, i.e. ceramics, gypsum, PMMA (poly(methyl methacrylate)), SR20 (acrylic copolymer) and resin (Accura® 60), to simulate brittle and hard rocks. Firstly, uniaxial compression tests were performed to determine the mechanical properties and failure patterns of the 3DP samples fabricated by those five materials. Experimental results indicate that among current 3DP techniques, the resin produced via stereolithography (SLA) is the most suitable 3DP material for mimicking brittle and hard rocks, although its brittleness needs to be improved. Subsequently, three methods including freezing, incorporation of internal macro-crack and addition of micro-defects were adopted to enhance the brittleness of the 3DP resin, followed by uniaxial compression tests on the treated samples. Experimental results reveal that 3DP resin samples with the suggested treatments exhibited brittle properties and behaved similarly to natural rocks. Finally, some prospective improvements which can be used to facilitate the application of 3DP techniques to rock mechanics were also discussed. The findings of this paper could contribute to promoting the application of 3DP technique in rock mechanics.

Understanding quantum thermalization through entanglement build up in isolated quantum systems addresses fundamental questions on how unitary dynamics connects to statistical physics. Spin systems made of long-range interacting atoms offer an ideal experimental platform to investigate this question. Here, we study the spin dynamics and approach towards local thermal equilibrium of a macroscopic ensemble of S = 3 chromium atoms pinned in a three dimensional optical lattice and prepared in a pure coherent spin state, under the effect of magnetic dipole–dipole interactions. Our isolated system thermalizes under its own dynamics, reaching a steady state consistent with a thermal ensemble with a temperature dictated from the system’s energy. The build up of quantum correlations during the dynamics is supported by comparison with an improved numerical quantum phase-space method. Our observations are consistent with a scenario of quantum thermalization linked to the growth of entanglement entropy. Isolated many-body quantum systems do not thermalize with an external environment but in most cases the internal dynamics leads to the emergence of an effective thermal equilibrium for local degrees of freedom. Here the authors study this behaviour with a realization of a long-range spin model.

The clinical success of immunotherapy that inhibits the negative immune regulatory pathway programmed cell death protein 1/PD-1 ligand (PD-1/PD-L1) has initiated a new era in the treatment of metastatic cancer. PD-L1 expression is upregulated in many solid tumors including lung cancer and functions predominantly in lactate-enriched tumor microenvironments. Here, we provided evidence for PD-L1 induction in response to lactate stimulation in lung cancer cells. Lactate-induced PD-L1 induction was mediated by its receptor GPR81. The silencing of GPR81 signaling in lung cancer cells resulted in a decrease in PD-L1 protein levels and functional inactivation of PD-L1 promoter activity. In addition, GPR81-mediated upregulation of PD-L1 in glucose-stimulated lung cancer cells that recapitulates the enhanced glycolysis in vivo was dependent on lactate dehydrogenase A (LDHA). We also demonstrated that activation of GPR81 decreases intracellular cAMP levels and inhibits protein kinase A (PKA) activity, leading to activation of the transcriptional coactivator TAZ. Interaction of TAZ with the transcription factor TEAD was essential for TAZ activation of PD-L1 and induction of its expression. Furthermore, we found that lactate-induced activation of PD-L1 in tumor cells led to reduced production of interferon-γ and induction of apoptosis of cocultured Jurkat T-cell leukemia cells. Our findings reveal an unexpected role of lactate in contributing to tumor cell protection from cytotoxic T-cell targeting and establishes a direct connection between tumor cell metabolic reprograming and tumor evasion from the immune response.

We investigate the emergence of a time crystal (TC) in a driven dissipative many-body spin array. In this system the interplay between incoherent spin pumping and collective emission stabilizes a synchronized non-equilibrium steady state which in the thermodynamic limit features a self-generated time-periodic pattern imposed by collective elastic interactions. In contrast to prior realizations where the time symmetry is already broken by an external drive, here it is only spontaneously broken by the elastic exchange interactions and manifest in the two-time correlation spectrum. Employing a combination of exact numerical calculations and a second-order cumulant expansion, we investigate the impact of many-body correlations on the TC formation and establish a connection between the regime where it is stable and where the system features a slow growth rate of the mutual information. This observation allows us to conclude that the TC studied here is an emergent semi-classical out-of-equilibrium state of matter. We also confirm the rigidity of the TC to single-particle dephasing. Finally, we discuss an experimental implementation using long lived dipoles in an optical cavity.

Neural representation is often described by the tuning curves of individual neurons with respect to certain stimulus variables. Despite this tradition, it has become increasingly clear that neural tuning can vary substantially in accordance with a collection of internal and external factors. A challenge we are facing is the lack of appropriate methods to accurately capture the moment-to-moment tuning variability directly from the noisy neural responses. Here we introduce an unsupervised statistical approach, Poisson functional principal component analysis (Pf-PCA), which identifies different sources of systematic tuning fluctuations, moreover encompassing several current models (e.g.,multiplicative gain models) as special cases. Applying this method to neural data recorded from macaque primary visual cortex– a paradigmatic case for which the tuning curve approach has been scientifically essential– we discovered a simple relationship governing the variability of orientation tuning, which unifies different types of gain changes proposed previously. By decomposing the neural tuning variability into interpretable components, our method enables discovery of unexpected structure of the neural code, capturing the influence of the external stimulus drive and internal states simultaneously. Accurately capturing the tuning variability directly from the noisy neural responses is an important and challenging issue. Here, the authors introduce an unsupervised statistical approach to decomposing tuning variability, leading to a simple and unifying rule of tuning modulation in V1.

Due to the desirable characteristic of the Bonferroni mean (BM) that it can capture the interrelationship between input arguments, and in order to provide the properties and the modelling capability of the BMs under hesitant fuzzy environment, we explore some new hesitant fuzzy Bonferroni means (HFBMs). The properties and the special cases of HFBMs are studied in detail. We specially define a concept of hesitant Bonferroni element (HBE), which is considered as a 'bonding satisfaction' factor used as a calculation unit in the HFBM. The HBE can reflect the correlation between hesitant fuzzy arguments, which makes the HFBM have particular advantages in aggregating arguments. In addition, the weighted hesitant fuzzy Bonferroni mean (WHFBM) is also proposed considering different importance degrees of input arguments. Furthermore, the procedure of multi-criteria decision making based on the WHFBM is given under hesitant fuzzy environment as typical applications, which has much sense in theory and practice for the BM.

We investigate collective emission from coherently driven ultracold 88 Sr atoms. We perform two sets of experiments using a strong and weak transition that are insensitive and sensitive, respectively, to atomic motion at 1 μK. We observe highly directional forward emission with a peak intensity that is enhanced, for the strong transition, by > 10 3 compared with that in the transverse direction. This is accompanied by substantial broadening of spectral lines. For the weak transition, the forward enhancement is substantially reduced due to motion. Meanwhile, a density-dependent frequency shift of the weak transition (∼10% of the natural linewidth) is observed. In contrast, this shift is suppressed to < 1% of the natural linewidth for the strong transition. Along the transverse direction, we observe strong polarization dependences of the fluorescence intensity and line broadening for both transitions. The measurements are reproduced with a theoretical model treating the atoms as coherent, interacting radiating dipoles. Light scattering from a dense coherent medium is determined by the interplay of dispersive and radiative dipole–dipole interactions. Here, the authors control the motional effects that obscure the coherence of scattered light and study collective emission in a driven gas of cold strontium-88 atoms.