Artificial intelligence powered advancements in upper extremity joint MRI: A review.

Magnetic resonance imaging (MRI) is an indispensable medical imaging examination technique in musculoskeletal medicine. Modern MRI techniques achieve superior high-quality multiplanar imaging of soft tissue and skeletal pathologies without the harmful effects of ionizing radiation. Some current limitations of MRI include long acquisition times, artifacts, and noise. In addition, it is often challenging to distinguish abutting or closely applied soft tissue structures with similar signal characteristics. In the past decade, Artificial Intelligence (AI) has been widely employed in musculoskeletal MRI to help reduce the image acquisition time and improve image quality. Apart from being able to reduce medical costs, AI can assist clinicians in diagnosing diseases more accurately. This will effectively help formulate appropriate treatment plans and ultimately improve patient care. This review article intends to summarize AI's current research and application in musculoskeletal MRI, particularly the advancement of DL in identifying the structure and lesions of upper extremity joints in MRI images.

Nardilysin-regulated scission mechanism activates polo-like kinase 3 to suppress the development of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) develops through step-wise genetic and molecular alterations including Kras mutation and inactivation of various apoptotic pathways. Here, we find that development of apoptotic resistance and metastasis of KrasG12D-driven PDAC in mice is accelerated by deleting Plk3, explaining the often-reduced Plk3 expression in human PDAC. Importantly, a 41-kDa Plk3 (p41Plk3) that contains the entire kinase domain at the N-terminus (1-353 aa) is activated by scission of the precursor p72Plk3 at Arg354 by metalloendopeptidase nardilysin (NRDC), and the resulting p32Plk3 C-terminal Polo-box domain (PBD) is removed by proteasome degradation, preventing the inhibition of p41Plk3 by PBD. We find that p41Plk3 is the activated form of Plk3 that regulates a feed-forward mechanism to promote apoptosis and suppress PDAC and metastasis. p41Plk3 phosphorylates c-Fos on Thr164, which in turn induces expression of Plk3 and pro-apoptotic genes. These findings uncover an NRDC-regulated post-translational mechanism that activates Plk3, establishing a prototypic regulation by scission mechanism.

YY1 Lactylation Aggravates Autoimmune Uveitis by Enhancing Microglial Functions via Inflammatory Genes.

Activated microglia in the retina are essential for the development of autoimmune uveitis. Yin-Yang 1 (YY1) is an important transcription factor that participates in multiple inflammatory and immune-mediated diseases. Here, an increased YY1 lactylation in retinal microglia within in the experimental autoimmune uveitis (EAU) group is observed. YY1 lactylation contributed to boosting microglial activation and promoting their proliferation and migration abilities. Inhibition of lactylation suppressed microglial activation and attenuated inflammation in EAU. Mechanistically, cleavage under targets & tagmentation ï¼ˆCUT&Tag） analysis revealed that YY1 lactylation promoted microglial activation by regulating the transcription of a set of inflammatory genes, including STAT3, CCL5, IRF1, IDO1, and SEMA4D. In addition, p300 is identified as the writer of YY1 lactylation. Inhibition of p300 decreased YY1 lactylation and suppressed microglial inflammation in vivo and in vitro. Collectively, the results showed that YY1 lactylation promoted microglial dysfunction in autoimmune uveitis by upregulating inflammatory cytokine secretion and boosting cell migration and proliferation. Therapeutic effects can be achieved by targeting the lactate/p300/YY1 lactylation/inflammatory genes axis.

Regulation of quantum spin conversions in a single molecular radical.

Free radicals, generally formed through the cleavage of covalent electron-pair bonds, play an important role in diverse fields ranging from synthetic chemistry to spintronics and nonlinear optics. However, the characterization and regulation of the radical state at a single-molecule level face formidable challenges. Here we present the detection and sophisticated tuning of the open-shell character of individual diradicals with a donor-acceptor structure via a sensitive single-molecule electrical approach. The radical is sandwiched between nanogapped graphene electrodes via covalent amide bonds to construct stable graphene-molecule-graphene single-molecule junctions. We measure the electrical conductance as a function of temperature and track the evolution of the closed-shell and open-shell electronic structures in real time, the open-shell triplet state being stabilized with increasing temperature. Furthermore, we tune the spin states by external stimuli, such as electrical and magnetic fields, and extract thermodynamic and kinetic parameters of the transition between closed-shell and open-shell states. Our findings provide insights into the evolution of single-molecule radicals under external stimuli, which may proof instrumental for the development of functional quantum spin-based molecular devices.

Vision-Language Models for Vision Tasks: A Survey.

Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, leading to a laborious and time-consuming visual recognition paradigm. To address the two challenges, Vision-Language Models (VLMs) have been intensively investigated recently, which learns rich vision-language correlation from web-scale image-text pairs that are almost infinitely available on the Internet and enables zero-shot predictions on various visual recognition tasks with a single VLM. This paper provides a systematic review of visual language models for various visual recognition tasks, including: (1) the background that introduces the development of visual recognition paradigms; (2) the foundations of VLM that summarize the widely-adopted network architectures, pre-training objectives, and downstream tasks; (3) the widely-adopted datasets in VLM pre-training and evaluations; (4) the review and categorization of existing VLM pre-training methods, VLM transfer learning methods, and VLM knowledge distillation methods; (5) the benchmarking, analysis and discussion of the reviewed methods; (6) several research challenges and potential research directions that could be pursued in the future VLM studies for visual recognition. A project associated with this survey has been created at https://github.com/jingyi0000/VLM_survey.

Effects of repeated low-level red-light therapy on macular retinal thickness and microvascular system in children with myopia.

OBJECTIVE: The objective of the study was to use optical coherence tomography angiography (OCTA) to analyze the effects of repeated low-level red-light (LLLT) therapy on macular retinal thickness and the microvascular system in children with myopia to evaluate the safety of this therapy. METHODS: This prospective study included 40 school-age children with myopia (80 eyes), aged 7-14 years, who received therapy using a LLLT instrument. At baseline and therapy for 1 month, 3 months, 6 months, all children underwent comprehensive ophthalmological examinations, including slit-lamp examination, uncorrected visual acuity, best-corrected visual acuity, spherical equivalent degree, axial length, and OCTA. The vessel densities of the superficial retinal capillary plexus, macular inner retinal thickness, and full-layer retinal thickness were measured. RESULTS: The macular inner retinal thickness increased at 1 month and remained unchanged thereafter, It differed significantly in nine areas at 1, 3, and 6 months compared to the thicknesses before therapy (P < 0.05); however, we observed no significant differences between the different time points (P > 0.05). The macular full-layer retinal thickness increased at 1 month and remained unchanged thereafter; the changes showed significant differences at 1 month and 3 months compared to before therapy, for the inner nasal region (P < 0.05). The other eight areas showed significant differences at 1, 3, and 6 months compared with before therapy (P < 0.05); however, no significant difference was observed between the different time points after therapy (P > 0.05). The vessel density of the superficial retinal capillary plexus did not differ significantly among the four groups (P > 0.05). CONCLUSIONS: LLLT therapy was safe. The school-aged children exhibited macular thickening after LLLT therapy, which had no significant effect on macular microcirculation.

Loratidine is associated with improved prognosis and exerts antineoplastic effects via apoptotic and pyroptotic crosstalk in lung cancer.

BACKGROUND: Tumor-associated inflammation suggests that anti-inflammatory medication could be beneficial in cancer therapy. Loratadine, an antihistamine, has demonstrated improved survival in certain cancers. However, the anticancer mechanisms of loratadine in lung cancer remain unclear. OBJECTIVE: This study investigates the anticancer mechanisms of loratadine in lung cancer. METHODS: A retrospective cohort of 4,522 lung cancer patients from 2006 to 2018 was analyzed to identify noncancer drug exposures associated with prognosis. Cellular experiments, animal models, and RNA-seq data analysis were employed to validate the findings and explore the antitumor effects of loratadine. RESULTS: This retrospective study revealed a positive association between loratadine administration and ameliorated survival outcomes in lung cancer patients, exhibiting dose dependency. Rigorous in vitro and in vivo assays demonstrated that apoptosis induction and epithelial-mesenchymal transition (EMT) reduction were stimulated by moderate loratadine concentrations, whereas pyroptosis was triggered by elevated dosages. Intriguingly, loratadine was found to augment PPARγ levels, which acted as a gasdermin D transcription promoter and caspase-8 activation enhancer. Consequently, loratadine might incite a sophisticated interplay between apoptosis and pyroptosis, facilitated by the pivotal role of caspase-8. CONCLUSION: Loratadine use is linked to enhanced survival in lung cancer patients, potentially due to its role in modulating the interplay between apoptosis and pyroptosis via caspase-8.

A postmeiotically bifurcated roadmap of honeybee spermatogenesis marked by phylogenetically restricted genes.

Haploid males of hymenopteran species produce gametes through an abortive meiosis I followed by meiosis II that can either be symmetric or asymmetric in different species. Thus, one spermatocyte could give rise to two spermatids with either equal or unequal amounts of cytoplasm. It is currently unknown what molecular features accompany these postmeiotic sperm cells especially in species with asymmetric meiosis II such as bees. Here we present testis single-cell RNA sequencing datasets from the honeybee (Apis mellifera) drones of 3 and 14 days after emergence (3d and 14d). We show that, while 3d testes exhibit active, ongoing spermatogenesis, 14d testes only have late-stage spermatids. We identify a postmeiotic bifurcation in the transcriptional roadmap during spermatogenesis, with cells progressing toward the annotated spermatids (SPT) and small spermatids (sSPT), respectively. Despite an overall similarity in their transcriptomic profiles, sSPTs express the fewest genes and the least RNA content among all the sperm cell types. Intriguingly, sSPTs exhibit a relatively high expression level for Hymenoptera-restricted genes and a high mutation load, suggesting that the special meiosis II during spermatogenesis in the honeybee is accompanied by phylogenetically young gene activities.

Interspecific Host Variation and Biotic Interactions Drive Pathogen Community Assembly in Chinese Bumblebees.

Bumblebees have been considered one of the most important pollinators on the planet. However, recent reports of bumblebee decline have raised concern about a significant threat to ecosystem stability. Infectious diseases caused by multiple pathogen infections have been increasingly recognized as an important mechanism behind this decline worldwide. Understanding the determining factors that influence the assembly and composition of pathogen communities among bumblebees can provide important implications for predicting infectious disease dynamics and making effective conservation policies. Here, we study the relative importance of biotic interactions versus interspecific host resistance in shaping the pathogen community composition of bumblebees in China. We first conducted a comprehensive survey of 13 pathogens from 22 bumblebee species across China. We then applied joint species distribution modeling to assess the determinants of pathogen community composition and examine the presence and strength of pathogen-pathogen associations. We found that host species explained most of the variations in pathogen occurrences and composition, suggesting that host specificity was the most important variable in predicting pathogen occurrences and community composition in bumblebees. Moreover, we detected both positive and negative associations among pathogens, indicating the role of competition and facilitation among pathogens in determining pathogen community assembly. Our research demonstrates the power of a pluralistic framework integrating field survey of bumblebee pathogens with community ecology frameworks to understand the underlying mechanisms of pathogen community assembly.

Pueraria thomsonii Radix Water Extract Alleviate Type 2 Diabetes Mellitus in db/db Mice through Comprehensive Regulation of Metabolism and Gut Microbiota.

Type 2 diabetes mellitus (T2DM) is an increasingly prevalent and serious health problem. Its onset is typically associated with metabolic disorders and disturbances in the gut microbiota. Previous studies have reported the anti-T2DM effects of Pueraria thomsonii Radix as a functional food. However, the mechanism of action is still unknown. In this study, rich polyphenols and polysaccharides from Pueraria Thomsonii Radix water extract (PTR) were quantitatively determined, and then the effects of PTR on db/db mice were evaluated by pharmacology, metabolomics, and 16S rRNA gene sequencing. The results showed that PTR could alleviate pancreatic tissue damage, significantly decrease fasting blood glucose (FBG), fasting serum insulin (FINS), homeostasis model assessment insulin resistance (HOMA-IR), urinary glucose (UGLU), and urinary albumin/creatinine ratio (UACR). Metabolomics showed that the Diabetes Control (DM) group produced 109 differential metabolites, of which 74 could be regulated by PTR. In addition, 16S rRNA sequencing was performed in fecal samples and results showed that PTR could reduce the Firmicutes/Bacteroidetes(F/B) ratio and regulate three beneficial bacteria and one harmful bacterium. In conclusion, the results showed that PTR could ameliorate the T2DM symptoms, metabolic disorder, and gut microbiota imbalance of db/db mice, and it was superior to metformin in some aspects. We suggested for the first time that γ-aminobutyric acid (GABA) may be involved in the regulation of the microbiota-gut-brain axis (MGB) and thus affects the metabolic disorders associated with T2DM. This study will provide a scientific basis for the development of functional food with PTR.

Global lactylome reveals lactylation-dependent mechanisms underlying TH17 differentiation in experimental autoimmune uveitis.

Dysregulation of CD4+ T cell differentiation is linked to autoimmune diseases. Metabolic reprogramming from oxidative phosphorylation to glycolysis and accumulation of lactate are involved in this process. However, the underlying mechanisms remain unclear. Our study showed that lactate-derived lactylation regulated CD4+ T cell differentiation. Lactylation levels in CD4+ T cells increased with the progression of experimental autoimmune uveitis (EAU). Inhibition of lactylation suppressed TH17 differentiation and attenuated EAU inflammation. The global lactylome revealed the landscape of lactylated sites and proteins in the CD4+ T cells of normal and EAU mice. Specifically, hyperlactylation of Ikzf1 at Lys164 promoted TH17 differentiation by directly modulating the expression of TH17-related genes, including Runx1, Tlr4, interleukin-2 (IL-2), and IL-4. Delactylation of Ikzf1 at Lys164 impaired TH17 differentiation. These findings exemplify how glycolysis regulates the site specificity of protein lactylation to promote TH17 differentiation and implicate Ikzf1 lactylation as a potential therapeutic target for autoimmune diseases.

Discovery of novel isopropanolamine inhibitors against MoTPS1 as potential fungicides with unique mechanisms.

The resistance and ecotoxicity of fungicides seriously restrict our ability to effectively control Magnaporthe oryzae. Discovering fungicidal agents based on novel targets, including MoTPS1, could efficiently address this situation. Here, we identified a hit VS-10 containing an isopropanolamine fragment as a novel MoTPS1 inhibitor through virtual screening, and forty-four analogs were synthesized by optimizing the structure of VS-10. Utilizing our newly established ion-pair chromatography (IPC) and leaf inoculation methods, we found that compared to VS-10, its analog j11 exhibited substantially greater inhibitory activity against both MoTPS1 and the pathogenicity of M. oryzae. Molecular simulations clarified that the electrostatic interactions between the bridging moiety of isopropanolamine and residue Glu396 of contributed significantly to the binding of j11 and MoTPS1. We preliminarily revealed the unique fungicidal mechanism of j11, which mainly impeded the infection of M. oryzae by decreasing sporulation, killing a small portion of conidia and interfering with the accumulation of turgor pressure in appressoria. Thus, in this study, a novel fungicide candidate with a unique mechanism targeting MoTPS1 was screened and discovered.

Cross-Domain Facial Expression Recognition via Contrastive Warm up and Complexity-Aware Self-Training.

Unsupervised cross-domain Facial Expression Recognition (FER) aims to transfer the knowledge from a labeled source domain to an unlabeled target domain. Existing methods strive to reduce the discrepancy between source and target domain, but cannot effectively explore the abundant semantic information of the target domain due to the absence of target labels. To this end, we propose a novel framework via Contrastive Warm up and Complexity-aware Self-Training (namely CWCST), which facilitates source knowledge transfer and target semantic learning jointly. Specifically, we formulate a contrastive warm up strategy via features, momentum features, and learnable category centers to concurrently learn discriminative representations and narrow the domain gap, which benefits domain adaptation by generating more accurate target pseudo labels. Moreover, to deal with the inevitable noise in pseudo labels, we develop complexity-aware self-training with a label selection module based on prediction entropy, which iteratively generates pseudo labels and adaptively chooses the reliable ones for training, ultimately yielding effective target semantics exploration. Furthermore, by jointly using the two mentioned components, our framework enables to effectively utilize the source knowledge and target semantic information by source-target co- training. In addition, our framework can be easily incorporated into other baselines with consistent performance improvements. Extensive experimental results on seven databases show the superior performance of the proposed method against various baselines.

Cost-Effectiveness Analysis of Risk Factor-Based Lung Cancer Screening Program by Low-Dose Computer Tomography in Current Smokers in China.

Although the effectiveness of lung cancer screening by low-dose computed tomography (LDCT) could be shown in China, there could be variation in the evidence concerning the economic impact. Our study explores the cost-effectiveness of lung cancer screening and optimizes the best definition of a high-risk population. A Markov model consisting of the natural history and post-diagnosis states was constructed to estimate the costs and quality-adjusted life years (QALYs) of LDCT screening compared with no screening. A total of 36 distinct risk factor-based screening strategies were assessed by incorporating starting ages of 40, 45, 50, 55, 60 and 65 years, stopping ages of 69, 74 and 79 years as well as smoking eligibility criteria. Screening data came from community-based mass screening with LDCT for lung cancer in Guangzhou. Compared with no screening, all screening scenarios led to incremental costs and QALYs. When the willingness-to-pay (WTP) threshold was USD37,653, three times the gross domestic product (GDP) per capita in China, six of nine strategies on the efficiency frontier may be cost-effective. Annual screening between 55 and 79 years of age for those who smoked more than 20 pack-years, which yielded an incremental cost-effectiveness ratio (ICER) of USD35,000.00 per QALY gained, was considered optimal. In sensitivity analyses, the result was stable in most cases. The trends of the results are roughly the same in scenario analyses. According to the WTP threshold of different regions, the optimal screening strategies were annual screening for those who smoked more than 20 pack-years, between 50 and 79 years of age in Zhejiang province, 55-79 years in Guangdong province and 65-74 years in Yunnan province. However, annual screening was unlikely to be cost-effective in Heilongjiang province under our modelling assumptions, indicating that tailored screening policies should be made regionally according to the local epidemiological and economic situation.

Potential role of the gut microbiota of bumblebee Bombus pyrosoma in adaptation to high-altitude habitats.

The gut microbiota affects the health and overall fitness of bumblebees. It can enhance the host's ecological range by leveraging their metabolic capacities. However, the diversity of the gut microbiota and adaptive functional evolution in high-altitude regions remain unclear. To explore how the gut microbiota helps the host adapt to high-altitude environments, we analyzed the differences in diversity and function of the gut microbiota between high- and low-altitude regions through full-length 16S rRNA sequencing. Our results show that high-altitude regions have a lower abundance of Fructobacillus and Saccharibacter compared to low-altitude regions. Additionally, some individuals in low-altitude regions were invaded by opportunistic pathogens. The gut microbiota in high-altitude regions has a greater number of pathways involved in "Protein digestion and absorption" and "Biosynthesis of amino acids," while fewer carbohydrate pathways are involved in "digestion and absorption" and "Salmonella infection." Our finding suggests that plateau hosts typically reduce energy metabolism and enhance immunity in response to adverse environments. Correspondingly, the gut microbiota also makes changes, such as reducing carbohydrate degradation and increasing protein utilization in response to the host. Additionally, the gut microbiota regulates their abundance and function to help the host adapt to adverse high-altitude environments.

Periodic Mesoporous Organosilica as a Nanoadjuvant for Subunit Vaccines Elicits Potent Antigen-Specific Germinal Center Responses by Activating Naive B Cells.

Infection diseases such as AIDS and COVID-19 remain challenging in regard to protective vaccine design, while adjuvants are critical for subunit vaccines to induce strong, broad, and durable immune responses against variable pathogens. Here, we demonstrate that periodic mesoporous organosilica (PMO) acts as a multifunctional nanoadjuvant by adsorbing recombinant protein antigens. It can effectively deliver antigens to lymph nodes (LNs), prolong antigen exposure, and rapidly elicit germinal center (GC) responses by directly activating naive B cells via the C-type lectin receptor signaling pathway. In mice, both the gp120 trimer (HIV-1 antigen) and the receptor-binding domain (SARS-CoV-2 antigen) with the PMO nanoadjuvant elicit potent and durable antibodies that neutralize heterologous virus strains. LN immune cells analysis shows that PMO helps to effectively activate the T-follicular helper cells, GC B cells, and memory B cells and eventually develop broad and durable humoral responses. Moreover, the PMO nanoadjuvant elicits a strong cellular immune response and shapes this immune response by eliciting high levels of effector T helper cell cytokines. This study identifies a promising nanoadjuvant for subunit vaccines against multiple pathogens.

Divergence and convergence of gut microbiomes of wild insect pollinators.

Pollination services provided by wild insect pollinators are critical to natural ecosystems and crops around the world. There is an increasing appreciation that the gut microbiota of these insects influences their health and consequently their services. However, pollinator gut microbiota studies have focused on well-described social bees, but rarely include other, more phylogenetically divergent insect pollinators. To expand our understanding, we explored the insect pollinator microbiomes across three insect orders through two DNA sequencing approaches. First, in an exploratory 16S amplicon sequencing analysis of taxonomic community assemblages, we found lineage-specific divergences of dominant microbial genera and microbiota community composition across divergent insect pollinator genera. However, we found no evidence for a strong broad-scale phylogenetic signal, which we see for community relatedness at finer scales. Subsequently, we utilized metagenomic shotgun sequencing to obtain metagenome-assembled genomes and assess the functionality of the microbiota from pollinating flies and social wasps. We uncover a novel gut microbe from pollinating flies in the family Orbaceae that is closely related to Gilliamella spp. from social bees but with divergent functions. We propose this novel species be named Candidatus Gilliamella eristali. Further metagenomes of dominant fly and wasp microbiome members suggest that they are largely not host-insect adapted and instead may be environmentally derived. Overall, this study suggests selective processes involving ecology or physiology, or neutral processes determining microbe colonization may predominate in the turnover of lineages in insect pollinators broadly, while evolution with hosts may occur only under certain circumstances and on smaller phylogenetic scales. IMPORTANCE Wild insect pollinators provide many key ecosystem services, and the microbes associated with these insect pollinators may influence their health. Therefore, understanding the diversity in microbiota structure and function, along with the potential mechanisms shaping the microbiota across diverse insect pollinators, is critical. Our study expands beyond existing knowledge of well-studied social bees, like honey bees, including members from other bee, wasp, butterfly, and fly pollinators. We infer ecological and evolutionary factors that may influence microbiome structure across diverse insect pollinator hosts and the functions that microbiota members may play. We highlight significant differentiation of microbiomes among diverse pollinators. Closer analysis suggests that dominant members may show varying levels of host association and functions, even in a comparison of closely related microbes found in bees and flies. This work suggests varied importance of ecological, physiological, and non-evolutionary filters in determining structure and function across largely divergent wild insect pollinator microbiomes.

Enhancing Spns2/S1P in macrophages alleviates hyperinflammation and prevents immunosuppression in sepsis.

Sepsis is a leading cause of in-hospital mortality resulting from a dysregulated response to infection. Novel immunomodulatory therapies targeting macrophage metabolism have emerged as an important focus for current sepsis research. However, understanding the mechanisms underlying macrophage metabolic reprogramming and how they impact immune response requires further investigation. Here, we identify macrophage-expressed Spinster homolog 2 (Spns2), a major transporter of sphingosine-1-phosphate (S1P), as a crucial metabolic mediator that regulates inflammation through the lactate-reactive oxygen species (ROS) axis. Spns2 deficiency in macrophages significantly enhances glycolysis, thereby increasing intracellular lactate production. As a key effector, intracellular lactate promotes pro-inflammatory response by increasing ROS generation. The overactivity of the lactate-ROS axis drives lethal hyperinflammation during the early phase of sepsis. Furthermore, diminished Spns2/S1P signaling impairs the ability of macrophages to sustain an antibacterial response, leading to significant innate immunosuppression in the late stage of infection. Notably, reinforcing Spns2/S1P signaling contributes to balancing the immune response during sepsis, preventing both early hyperinflammation and later immunosuppression, making it a promising therapeutic target for sepsis.

Unsupervised Point Cloud Representation Learning With Deep Neural Networks: A Survey.

Point cloud data have been widely explored due to its superior accuracy and robustness under various adverse situations. Meanwhile, deep neural networks (DNNs) have achieved very impressive success in various applications such as surveillance and autonomous driving. The convergence of point cloud and DNNs has led to many deep point cloud models, largely trained under the supervision of large-scale and densely-labelled point cloud data. Unsupervised point cloud representation learning, which aims to learn general and useful point cloud representations from unlabelled point cloud data, has recently attracted increasing attention due to the constraint in large-scale point cloud labelling. This paper provides a comprehensive review of unsupervised point cloud representation learning using DNNs. It first describes the motivation, general pipelines as well as terminologies of the recent studies. Relevant background including widely adopted point cloud datasets and DNN architectures is then briefly presented. This is followed by an extensive discussion of existing unsupervised point cloud representation learning methods according to their technical approaches. We also quantitatively benchmark and discuss the reviewed methods over multiple widely adopted point cloud datasets. Finally, we share our humble opinion about several challenges and problems that could be pursued in the future research in unsupervised point cloud representation learning.

Effects of Low-Temperature Acclimation on Nutrients of Bumble Bee Bombus terrestris Queens during Prediapause and Diapause.

A queen's diapause is a key period of the bumble bee life cycle that enables them to survive under unfavorable conditions. During diapause, queens fast, and nutritional reserves depend on the accumulation of nutrients during the prediapause period. Temperature is one of the most important factors affecting queens' nutrient accumulation during prediapause and nutrient consumption during diapause. Here, we used a 6-day-old mated queen of the bumble bee Bombus terrestris to evaluate the effect of temperature (10, 15, and 25 °C) and time (3, 6, and 9 days) on free water, protein, lipids, and total sugars during prediapause and at the end of 3 months of diapause. Stepwise regression analysis revealed that total sugars, free water, and lipids were much more affected by temperature than protein (p < 0.05). Lower temperature acclimation significantly increased (p < 0.05) free water and lipid accumulation by queens during prediapause. In contrast, higher temperature acclimation significantly increased (p < 0.05) protein and total sugar accumulation by queens during prediapause. The effect of temperature acclimation on the queen survival rate was not significantly different (p > 0.05) after 3 months of diapause. Moreover, lower temperature acclimation reduced protein, lipid, and total sugar consumption by queens during diapause. In conclusion, low-temperature acclimation increases queens' lipid accumulation during prediapause and reduces the nutritional consumption of queens during diapause. Low-temperature acclimation during prediapause could benefit queens by improving cold resistance and increasing reserves of major nutrient lipids during diapause.