The advent of immune checkpoint inhibition (ICI) using antibodies against PD1 and its ligand PDL1 has prompted substantial efforts to develop complementary drugs. Although many of these are antibodies directed against additional checkpoint proteins, there is an increasing interest in small-molecule immuno-oncology drugs that address intracellular pathways, some of which have recently entered clinical trials. In parallel, small molecules that target pro-tumorigenic pathways in cancer cells and the tumour microenvironment have been found to have immunostimulatory effects that synergize with the action of ICI antibodies, leading to the approval of an increasing number of regimens that combine such drugs. Combinations with small molecules targeting cancer metabolism, cytokine/chemokine and innate immune pathways, and T cell checkpoints are now under investigation. This Review discusses the recent milestones and hurdles encountered in this area of drug development, as well as our views on the best path forward. <<<

G(M1) gangliosidosis and Morquio B are autosomal recessive lysosomal storage diseases associated with a neurodegenerative disorder or dwarfism and skeletal abnormalities, respectively. These diseases are caused by deficiencies in the lysosomal enzyme β-d-galactosidase (β-Gal), which lead to accumulations of the β-Gal substrates, G(M1) ganglioside, and keratan sulfate. β-Gal is an exoglycosidase that catalyzes the hydrolysis of terminal β-linked galactose residues. This study shows the crystal structures of human β-Gal in complex with its catalytic product galactose or with its inhibitor 1-deoxygalactonojirimycin. Human β-Gal is composed of a catalytic TIM barrel domain followed by β-domain 1 and β-domain 2. To gain structural insight into the molecular defects of β-Gal in the above diseases, the disease-causing mutations were mapped onto the three-dimensional structure. Finally, the possible causes of the diseases are discussed. <<<

Maternal brain adaptations have been found across pregnancy and postpartum, but little is known about the long-term effects of parity on the maternal brain. Using neuroimaging and machine learning, we investigated structural brain characteristics in 12,021 middle-aged women from the UK Biobank, demonstrating that parous women showed less evidence of brain aging compared to their nulliparous peers. The relationship between childbirths and a "younger-looking" brain could not be explained by common genetic variation or relevant confounders. Although prospective longitudinal studies are needed, the results suggest that parity may involve neural changes that could influence women's brain aging later in life. <<<

Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation. Generally, MAS methods register multiple atlases, i.e., medical images with corresponding labels, to a target image; and the transformed atlas labels can be combined to generate target segmentation via label fusion schemes. Many conventional MAS methods employed the atlases from the same modality as the target image. However, the number of atlases with the same modality may be limited or even missing in many clinical applications. Besides, conventional MAS methods suffer from the computational burden of registration or label fusion procedures. In this work, we design a novel cross-modality MAS framework, which uses available atlases from a certain modality to segment a target image from another modality. To boost the computational efficiency of the framework, both the image registration and label fusion are achieved by well-designed deep neural networks. For the atlas-to-target image registration, we propose a bi-directional registration network (BiRegNet), which can efficiently align images from different modalities. For the label fusion, we design a similarity estimation network (SimNet), which estimates the fusion weight of each atlas by measuring its similarity to the target image. SimNet can learn multi-scale information for similarity estimation to improve the performance of label fusion. The proposed framework was evaluated by the left ventricle and liver segmentation tasks on the MM-WHS and CHAOS datasets, respectively. Results have shown that the framework is effective for cross-modality MAS in both registration and label fusion. <<<

Atlas building and image registration are important tasks for medical image analysis. Once one or multiple atlases from an image population have been constructed, commonly (1) images are warped into an atlas space to study intra-subject or inter-subject variations or (2) a possibly probabilistic atlas is warped into image space to assign anatomical labels. Atlas estimation and nonparametric transformations are computationally expensive as they usually require numerical optimization. Additionally, previous approaches for atlas building often define similarity measures between a fuzzy atlas and each individual image, which may cause alignment difficulties because a fuzzy atlas does not exhibit clear anatomical structures in contrast to the individual images. This work explores using a convolutional neural network (CNN) to jointly predict the atlas and a stationary velocity field (SVF) parameterization for diffeomorphic image registration with respect to the atlas. Our approach does not require affine pre-registrations and utilizes pairwise image alignment losses to increase registration accuracy. We evaluate our model on 3D knee magnetic resonance images (MRI) from the OAI-ZIB dataset. Our results show that the proposed framework achieves better performance than other state-of-the-art image registration algorithms, allows for end-to-end training, and for fast inference at test time. <<<

In a search for the genetic basis for the structural difference between the related Streptococcus pneumoniae capsular serotypes 15B and 15C and for the reported reversible switching between these serotypes, the corresponding capsular polysaccharide synthesis (cps) loci were investigated by keeping in mind that at the structural level, the capsules differ only in O acetylation. The cps locus of a serotype 15B strain was identified, partially PCR amplified with primers based on the related serotype 14 sequence, and sequenced. Sequence analysis revealed, among other open reading frames, an intact open reading frame (designated cps15bM) whose product, at the protein level, exhibited characteristics of previously identified acetyltransferases. Genetic analysis of the corresponding region in a serotype15C strain indicated that the same gene was present but had a premature stop in translation. Closer analysis indicated that the serotype 15B gene contained a short tandem TA repeat consisting of eight TA units. In serotype 15C, this gene contained nine TA units that resulted in a frameshift and a truncated product. Genetic analysis of 17 serotype 15B and 15C clinical isolates revealed a perfect correlation between the serotype and the length of the short tandem repeat in the putative O-acetyltransferase gene. The number of TA repeating units varied between seven and nine in the various isolates. Together, the data strongly suggest that the structural difference between serotypes 15B and 15C is based on variation in the short tandem TA repeat in the O-acetyltransferase gene and that the transition between serotypes is due to slipped-strand mispairing with deletion or insertion of TA units in the cps15bM gene. <<<

Diffusion models are a class of deep generative models that have shown impressive results on various tasks with a solid theoretical foundation. Despite demonstrated success than state-of-the-art approaches, diffusion models often entail costly sampling procedures and sub-optimal likelihood estimation. Significant efforts have been made to improve the performance of diffusion models in various aspects. In this article, we present a comprehensive review of existing variants of diffusion models. Specifically, we provide the taxonomy of diffusion models and categorize them into three types: sampling-acceleration enhancement, likelihood-maximization enhancement, and data-generalization enhancement. We also introduce the other generative models (i.e., variational autoencoders, generative adversarial networks, normalizing flow, autoregressive models, and energy-based models) and discuss the connections between diffusion models and these generative models. Then we review the applications of diffusion models, including computer vision, natural language processing, waveform signal processing, multi-modal modeling, molecular graph generation, time series modeling, and adversarial purification. Furthermore, we propose new perspectives pertaining to the development of generative models. Github: this https URL. <<<

The ability to select short DNA oligonucleotide sequences capable of binding solely to their intended target is of great importance in developing nucleic acid based detection technologies. Applications such as multiplex PCR rely on primers binding to unique regions in a genome. Competing side reactions with other primer pairs or template DNA decrease PCR efficiency. Freely available primer design software such as Primer3 screens for potential hairpin and primer-dimer interactions while selecting a single primer pair. The development of multiplex PCR assays (in the range of 5 to 20 loci) requires the screening of all primer pairs for potential cross-reactivity. However, a logistical problem results due to the number of total number of comparisons required. Comparing the primer set for a 10-plex assay (20 total primer sequences) results in 210 primer-primer combinations that must be screened. The ability to screen sets of candidate oligomers rapidly for potential cross-reactivity reduces overall assay development time. Here we report the application of a familiar sliding algorithm for comparing two strands of DNA in an overlapping fashion. The algorithm has been employed in a software package wherein the user can compare multiple sequences in a single computational run. After the screening is completed, a score is assigned to potential duplex interactions exceeding a user-defined threshold. Additional criteria of predicted melting temperature (Tm) and free energy of melting (ΔG) are included for further ranking. Sodium counterion and total stand concentrations can be adjusted for the Tm and ΔG calculations. The predicted interactions are saved in a text file for further evaluation. <<<

Insight denotes a mental restructuring that leads to a sudden gain of explicit knowledge allowing qualitatively changed behaviour. Anecdotal reports on scientific discovery suggest that pivotal insights can be gained through sleep. Sleep consolidates recent memories and, concomitantly, could allow insight by changing their representational structure. Here we show a facilitating role of sleep in a process of insight. Subjects performed a cognitive task requiring the learning of stimulus-response sequences, in which they improved gradually by increasing response speed across task blocks. However, they could also improve abruptly after gaining insight into a hidden abstract rule underlying all sequences. Initial training establishing a task representation was followed by 8 h of nocturnal sleep, nocturnal wakefulness, or daytime wakefulness. At subsequent retesting, more than twice as many subjects gained insight into the hidden rule after sleep as after wakefulness, regardless of time of day. Sleep did not enhance insight in the absence of initial training. A characteristic antecedent of sleep-related insight was revealed in a slowing of reaction times across sleep. We conclude that sleep, by restructuring new memory representations, facilitates extraction of explicit knowledge and insightful behaviour. <<<

Dongqiang Zeng, Zilan Ye, Rongfang Shen, Guangchuang Yu, Jiani Wu, Yi Xiong, Rui Zhou, Wenjun Qiu, Na Huang, Li Sun, Xuejun Li, Jianping Bin, Yulin Liao, Min Shi, Wangjun Liao <<<

Recent advances in next-generation sequencing (NGS) technologies have triggered the rapid accumulation of publicly available multi-omics datasets. The application of integrated omics to explore robust signatures for clinical translation is increasingly emphasized, and this is attributed to the clinical success of immune checkpoint blockades in diverse malignancies. However, effective tools for comprehensively interpreting multi-omics data are still warranted to provide increased granularity into the intrinsic mechanism of oncogenesis and immunotherapeutic sensitivity. Therefore, we developed a computational tool for effective Immuno-Oncology Biological Research (IOBR), providing a comprehensive investigation of the estimation of reported or user-built signatures, TME deconvolution, and signature construction based on multi-omics data. Notably, IOBR offers batch analyses of these signatures and their correlations with clinical phenotypes, long non-coding RNA (lncRNA) profiling, genomic characteristics, and signatures generated from single-cell RNA sequencing (scRNA-seq) data in different cancer settings. Additionally, IOBR integrates multiple existing microenvironmental deconvolution methodologies and signature construction tools for convenient comparison and selection. Collectively, IOBR is a user-friendly tool for leveraging multi-omics data to facilitate immuno-oncology exploration and to unveil tumor-immune interactions and accelerating precision immunotherapy. <<<

Yajie Zhao, Eugene J Gardner, Marcus A Tuke, Huairen Zhang, Maik Pietzner, Mine Koprulu, Raina Y Jia, Katherine S Ruth, Andrew R Wood, Robin N Beaumont, Jessica Tyrrell, Samuel E Jones, Hana Lango Allen, Felix R Day, Claudia Langenberg, Timothy M Frayling, Michael N Weedon, John R B Perry, Ken K Ong, Anna Murray <<<

PURPOSE: The study aimed to systematically ascertain male sex chromosome abnormalities, 47,XXY (Klinefelter syndrome [KS]) and 47,XYY, and characterize their risks of adverse health outcomes.METHODS: We analyzed genotyping array or exome sequence data in 207,067 men of European ancestry aged 40 to 70 years from the UK Biobank and related these to extensive routine health record data.RESULTS: Only 49 of 213 (23%) of men whom we identified with KS and only 1 of 143 (0.7%) with 47,XYY had a diagnosis of abnormal karyotype on their medical records or self-report. We observed expected associations for KS with reproductive dysfunction (late puberty: risk ratio [RR] = 2.7; childlessness: RR = 4.2; testosterone concentration: RR = -3.8 nmol/L, all P < 2 × 10-8), whereas XYY men appeared to have normal reproductive function. Despite this difference, we identified several higher disease risks shared across both KS and 47,XYY, including type 2 diabetes (RR = 3.0 and 2.6, respectively), venous thrombosis (RR = 6.4 and 7.4, respectively), pulmonary embolism (RR = 3.3 and 3.7, respectively), and chronic obstructive pulmonary disease (RR = 4.4 and 4.6, respectively) (all P < 7 × 10-6).CONCLUSION: KS and 47,XYY were mostly unrecognized but conferred substantially higher risks for metabolic, vascular, and respiratory diseases, which were only partially explained by higher levels of body mass index, deprivation, and smoking. <<<

颂扬牺牲是危机时代女性解放议程中必然的一部分。尽管如此,作为传统中国"列女传"的一脉,女性牺牲者进入男性荣誉的烈士谱系并非名正言顺。看似悖谬的是,现代第一女烈士秋瑾在革命告成之前因为是"女性"被排除在外,革命胜利之后又因为是"女性"而备受优待。女性进入烈士谱系是一个神圣化的过程,也是一个去性别化的过程。在文学史的意义上,丁玲的"准烈士"小说不仅颠覆了传统文学节妇烈女的叙事模式,而且打破了烈士文章过度颂扬的刻板程式。 <<<

Xingyao Xiong, Junbo Gou, Qinggang Liao, Yanlin Li, Qian Zhou, Guiqi Bi, Chong Li, Ran Du, Xiaotong Wang, Tianshu Sun, Lvjun Guo, Haifei Liang, Pengjun Lu, Yaoyao Wu, Zhonghua Zhang, Dae-Kyun Ro, Yi Shang, Sanwen Huang, Jianbin Yan <<<

The ancient gymnosperm genus Taxus is the exclusive source of the anticancer drug paclitaxel, yet no reference genome sequences are available for comprehensively elucidating the paclitaxel biosynthesis pathway. We have completed a chromosome-level genome of Taxus chinensis var. mairei with a total length of 10.23 gigabases. Taxus shared an ancestral whole-genome duplication with the coniferophyte lineage and underwent distinct transposon evolution. We discovered a unique physical and functional grouping of CYP725As (cytochrome P450) in the Taxus genome for paclitaxel biosynthesis. We also identified a gene cluster for taxadiene biosynthesis, which was formed mainly by gene duplications. This study will facilitate the elucidation of paclitaxel biosynthesis and unleash the biotechnological potential of Taxus. <<<

The mTOR complex 1 (mTORC1) is an essential metabolic hub that coordinates cellular metabolism with the availability of nutrients, including amino acids. Sestrin2 has been identified as a cytosolic leucine sensor that transmits leucine status signals to mTORC1. In this study, we identify an E3 ubiquitin ligase RING finger protein 167 (RNF167) and a deubiquitinase STAMBPL1 that function in concert to control the polyubiquitination level of Sestrin2 in response to leucine availability. Ubiquitination of Sestrin2 promotes its interaction with GATOR2 and inhibits mTORC1 signaling. Bioinformatic analysis reveals decreased RNF167 expression and increased STAMBPL1 expression in gastric and colorectal tumors. Knockout of STAMBPL1 or correction of the heterozygous STAMBPL1 mutation in a human colon cancer cell line suppresses xenograft tumor growth. Lastly, a cell-permeable peptide that blocks the STAMBPL1-Sestrin2 interaction inhibits mTORC1 and provides a potential option for cancer therapy. <<<

Genome-wide association studies (GWAS) test hundreds of thousands of genetic variants across many genomes to find those statistically associated with a specific trait or disease. This methodology has generated a myriad of robust associations for a range of traits and diseases, and the number of associated variants is expected to grow steadily as GWAS sample sizes increase. GWAS results have a range of applications, such as gaining insight into a phenotype’s underlying biology, estimating its heritability, calculating genetic correlations, making clinical risk predictions, informing drug development programmes and inferring potential causal relationships between risk factors and health outcomes. In this Primer, we provide the reader with an introduction to GWAS, explaining their statistical basis and how they are conducted, describe state-of-the art approaches and discuss limitations and challenges, concluding with an overview of the current and future applications for GWAS results. <<<

MRI provides a powerful tool for studying the functional and structural connections in the brain non-invasively. The technique of functional connectivity (FC) exploits the intrinsic temporal correlations of slow spontaneous signal fluctuations to characterise brain functional networks. In addition, diffusion MRI fibre-tracking can be used to study the white matter structural connections. In recent years, there has been considerable interest in combining these two techniques to provide an overall structural-functional description of the brain. In this work we applied the recently proposed super-resolution track-weighted imaging (TWI) methodology to demonstrate how whole-brain fibre-tracking data can be combined with FC data to generate a track-weighted (TW) FC map of FC networks. The method was applied to data from 8 healthy volunteers, and illustrated with (i) FC networks obtained using a seeded connectivity-based analysis (seeding in the precuneus/posterior cingulate cortex, PCC, known to be part of the default mode network), and (ii) with FC networks generated using independent component analysis (in particular, the default mode, attention, visual, and sensory-motor networks). TW-FC maps showed high intensity in white matter structures connecting the nodes of the FC networks. For example, the cingulum bundles show the strongest TW-FC values in the PCC seeded-based analysis, due to their major role in the connection between medial frontal cortex and precuneus/posterior cingulate cortex; similarly the superior longitudinal fasciculus was well represented in the attention network, the optic radiations in the visual network, and the corticospinal tract and corpus callosum in the sensory-motor network. The TW-FC maps highlight the white matter connections associated with a given FC network, and their intensity in a given voxel reflects the functional connectivity of the part of the nodes of the network linked by the structural connections traversing that voxel. They therefore contain a different (and novel) image contrast from that of the images used to generate them. The results shown in this study illustrate the potential of the TW-FC approach for the fusion of structural and functional data into a single quantitative image. This technique could therefore have important applications in neuroscience and neurology, such as for voxel-based comparison studies. <<<

We propose a novel method for unsupervised image-to-image translation, which incorporates a new attention module and a new learnable normalization function in an end-to-end manner. The attention module guides our model to focus on more important regions distinguishing between source and target domains based on the attention map obtained by the auxiliary classifier. Unlike previous attention-based method which cannot handle the geometric changes between domains, our model can translate both images requiring holistic changes and images requiring large shape changes. Moreover, our new AdaLIN (Adaptive Layer-Instance Normalization) function helps our attention-guided model to flexibly control the amount of change in shape and texture by learned parameters depending on datasets. Experimental results show the superiority of the proposed method compared to the existing state-of-the-art models with a fixed network architecture and hyper-parameters. Our code and datasets are available at this https URL or this https URL. <<<

Previous studies have identified neurons in the postsubiculum which discharge as a function of the animal's head direction in the horizontal plane, independent of its behavior and location in the environment. Anatomical studies have shown that the postsubiculum contains reciprocal connections with the anterior thalamic nuclei (ATN). In order to determine how the head direction (HD) cell signal is processed in the brain, single- unit recordings were monitored in the ATN of freely moving rats in order to characterize their behavioral and spatial correlates. Animals were trained to retrieve food pellets thrown randomly into a cylindrical apparatus containing a single orientation cue. Single unit recordings in the ATN showed that approximately 60% of the recorded cells discharged in relation to the animal's head direction in the horizontal plane. Observation of the animal and quantitative analyses showed that HD cell firing was not dependent on the animal's behavior, trunk position, linear speed, angular head velocity, or location in the environment. Most of these cells were localized to the anterior dorsal thalamic nucleus. Each HD cell contained only one head direction at which the cell discharged maximally and the firing rate decreased linearly away from this preferred direction. The preferred firing directions from all cells recorded were distributed over a 360° range. Quantitative analysis showed that these cells contained similar discharge parameters (peak firing rate, directional firing range) to values reported previously for post-subicular HD cells (Taube et el., 1990a). Experiments involving rotation of the orientation cue showed that the preferred firing direction could be controlled by a salient visual cue. In contrast to postsubicular HD cells, passive rotation of a restrained animal showed that most ATN HD cells ceased discharging when the animal's head was oriented in the preferred direction. These findings demonstrate the presence of HD cells in the ATN and indicate the potential importance of this area for spatial navigation. The origin of the head direction signal is discussed and it is concluded that because of the presence of reciprocal connections between the postsubiculum and the ATN, further studies are required in order to determine the direction in which this head-directional information is flowing. Finally, ATN HD cells differ from postsubicular HD cells by appearing to require volitional motoric input. <<<

Teri A Manolio, Francis S Collins, Nancy J Cox, David B Goldstein, Lucia A Hindorff, David J Hunter, Mark I McCarthy, Erin M Ramos, Lon R Cardon, Aravinda Chakravarti, Judy H Cho, Alan E Guttmacher, Augustine Kong, Leonid Kruglyak, Elaine Mardis, Charles N Rotimi, Montgomery Slatkin, David Valle, Alice S Whittemore, Michael Boehnke, Andrew G Clark, Evan E Eichler, Greg Gibson, Jonathan L Haines, Trudy F C Mackay, Steven A McCarroll, Peter M Visscher <<<

Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment. <<<