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Summary Faithful chromosome segregation in meiosis requires crossover (CO) recombination, which is regulated to ensure at least one CO per homolog pair. We investigate failure to ensure COs in juvenile male mice. By monitoring recombination genome-wide using cytological assays and at hotspots using molecular assays, we show that juvenile mouse spermatocytes have fewer COs relative to adults. Analysis of recombination in the absence of MLH3 provides evidence for greater utilization in juveniles of pathways involving structure-selective nucleases and/or alternative complexes, which can act upon precursors to generate noncrossovers (NCOs) at the expense of COs. We propose that some designated CO sites fail to mature efficiently in juveniles owing to inappropriate activity of these alternative repair pathways, leading to chromosome mis-segregation. We also find lower MutLγ focus density in juvenile human spermatocytes, suggesting that weaker CO maturation efficiency may explain why younger men have higher risk of fathering children with Down syndrome.

Cisplatin occupies a crucial role in the treatment of various malignant tumours. However, its efficacy and applicability are heavily restricted by severe systemic toxicities and drug resistance. Our study exploits the active targeting of supramolecular metallacages to enhance the activity of cisplatin in cancer cells while reducing its toxicity. Thus, Pd2L4 cages (L = ligand) have been conjugated to four integrin ligands with different binding affinity and selectivity. Cage formation and encapsulation of cisplatin was proven by NMR spectroscopy. Upon encapsulation, cisplatin showed increased cytotoxicity in vitro, in melanoma A375 cells overexpressing αvβ3 integrins. Moreover, ex vivo studies in tissue slices indicated reduced toxicity towards healthy liver and kidney tissues for cage-encapsulated cisplatin. Analysis of metal content by ICP-MS demonstrated that encapsulated drug is less accumulated in these organs compared to the 'free' one.

Combining plasma activation and cross-reactivity of sensor array, we have developed a plasma-assisted cataluminescence (PA-CTL) sensor array for fast sensing and discrimination of gaseous hydrocarbons, which can be potentially used for fast diagnosis of lung cancer. Based on dielectric barrier discharge, a low-temperature plasma is generated to activate gaseous hydrocarbons with low cataluminescence (CTL) activities. Extremely increased CTL responses have been obtained, which resulted in a plasma assistance factor of infinity (∞) for some hydrocarbons. On a 4 × 3 PA-CTL sensor array made from alkaline-earth nanomaterials, gaseous hydrocarbons showed robust and unique CTL responses to generate characteristic patterns for fast discrimination. Because of the difference in the component of hydrocarbons in breath, exhaled breath samples from donors with and without lung cancer were tested, and good discrimination has been achieved by this technique. In addition, the feasibility of multidimentional detection based on temperature was confirmed. It had good reproducibility and gave a linear range of 65-6500 ng/mL or 77-7700 ppmv (R > 0.98) for CH(4) with a detection limit of 33 ng/mL (38 ppmv) on MgO. The PA-CTL sensor array is simple, low-cost, thermally stable, nontoxic, and has an abundance of alkaline-earth nanomaterials to act as sensing elements. This has expanded the applications of CTL-based senor arrays and will show great potential in clinical fast diagnosis.

Convoluted biological processes underlie the development of multicellular organisms and diseases. Advances in scRNA-seq make it possible to study these processes from cells at various developmental stages. Achieving accurate characterization is challenging, however, particularly for periodic processes, such as cell cycles. To address this, we developed Cyclum, a novel AutoEncoder approach that characterizes circular trajectories in the high-dimensional gene expression space. Cyclum substantially improves the accuracy and robustness of cell-cycle characterization beyond existing approaches. Applying Cyclum to removing cell-cycle effects leads to substantially improved delineations of cell subpopulations, which is useful for establishing various cell atlases and studying tumor heterogeneity. Cyclum is available at https://github.com/KChen-lab/cyclum. BackgroundConvoluted biological processes, which involve cell proliferation, differentiation, state transition, and cell-to-cell communication [1,2]. The course of development can be influenced by genetic (e.g., mutations), epigenetic, and environmental factors. Alterations to the genome, transcriptome, and proteome of individual cells also can result in pathogeneses [3]. Early efforts have been made to reconstruct the temporal ordering of biological samples using bulk data [4,5], although challenges associated with cellular heterogeneity make it difficult to infer accurate time series. Advances in single-cell RNA sequencing (scRNA-seq) enabled large-scale acquisition of singlecell transcriptomic profiles and provided an unprecedented opportunity to uncover latent biological processes that orchestrate dynamic expression of genes in single cells throughout the course of the development [6]. However, it is very challenging to deconvolute these processes from scRNA-seq data accurately. A sufficiently large number of cells across time, lineage, and space need to be sampled in order to capture detailed sub-populational features and reduce technological noise. Tremendous efforts have been made to develop trajectory inference methods from scRNA-seq data. Over 59 methods have been developed since 2014 [7], including the widely known Monocle and Wanderlust. These methods represent biological processes in linear, bifurcating, or other graph topologies.In many developmental processes, such as embryogenesis, organogenesis, and tumorigenesis [8], cell cycle plays a fundamental role. Distinct from processes that evoke linear changes in gene expression, cell cycle causes periodicity. A cycle starts from the G1 phase, goes through S and G2/M, and then returns to G1 within 24-hours for human cells [2]. This process is orchestrated elegantly by variable sets of genes (e.g., cyclins and cyclin-dependent kinases) that are turned on and off at relatively precise timings. As a result of such periodicity, the cycling cells at different transcriptomic states form a circular, non-linear trajectory in high-dimensional gene expression spaces. The positions of a cell alongside the circular trajec...

The recent development of mass spectrometry imaging (MSI) technology allowed to obtain highly detailed images of the spatial distribution of proteins in tissue at high spatial resolution reaching cell dimensions, high target specificity and a large dynamic concentration range. This review focusses on the development of two main MSI principles, targeted and untargeted detection of protein distribution in tissue samples, with special emphasis on the improvements in analyzed mass range and spatial resolution over the last 10 years. Untargeted MSI of in situ digested proteins with matrix-assisted laser desorption ionization is the most widely used approach, but targeted protein MSI technologies using laser ablation inductively coupled plasma (LA-ICP) and photocleavable mass tag chemical labeling strategies are gaining momentum. Moreover, this review also provides an overview of the effect of sample preparation on image quality and the bioinformatic challenge to identify proteins and quantify their distribution in complex MSI data.

Supramolecular PdL cages (L = ligand) hold promise as drug delivery systems. With the idea of achieving targeted delivery of the metallacages to tumor cells, the bioconjugation of exo-functionalized self-assembled PdL cages to peptides following two different approaches is reported for the first time. The obtained bioconjugates were analyzed and identified by high-resolution mass spectrometry.