Structurally Preserved Liquidambar Infructescences, Associated Pollen, and Leaves from the Late Oligocene of the Nanning Basin, South China.

Liquidambar L. is a significant constituent of the Cenozoic flora in the Northern Hemisphere. Currently, this genus exhibits a discontinuous distribution across Asia and North America, with the center of diversity being in southeastern Asia. This study presents the first occurrence of Liquidambar in the Oligocene of South China. Fossil sweetgum infructescences, associated pollen, and leaves have been found in the Nanning Basin, Guangxi. A new species, Liquidambar nanningensis sp. nov., is described based on the morphological and anatomical characteristics of three-dimensionally preserved infructescences. The Liquidambar fossils from the Nanning Basin show a combination of features indicative of the former genera of Altingiaceae, Altingia, Liquidambar s. str., and Semiliquidambar. The new occurrence expands the taxonomic and morphological diversity of the Paleogene Liquidambar species in South China.

Classification of five SARS-CoV-2 serotypes based on RBD antigenicities.

The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a significant number of variants, particularly with the emergence of Omicron with many sub-variants. These variants have exhibited increased immune escape, leading to reduced efficacy of existing vaccines and therapeutic antibodies. Given the diminished cross-neutralization observed among these variants, it is plausible that SARS-CoV-2 has developed multiple serotypes. As the major antigenic site, the receptor-binding domain (RBD) of viral spike (S) protein was chosen for serotyping. We selected 23 representative variants, including pre-Omicron variants and Omicron sub-variants, and classified them into five serotypes based on systematic evaluation of the antigenicities of their RBDs. Each serotype includes several genetically distinct variants. Serotype-I encompasses all pre-Omicron variants (with two subtypes), while the remaining four serotypes are all comprised of Omicron sub-variants at different stages of evolution. We propose that these serotypes can serve as a foundation for rapid classification of newly emerging SARS-CoV-2 variants, and guide the development of future broad-spectrum vaccines and neutralizing antibodies against the coronavirus disease 2019 (COVID-19).

Late Oligocene fossil acorns and nuts of Quercus section Cyclobalanopsis from the Nanning Basin, Guangxi, South China.

Quercus is the largest genus within the Fagaceae and has a rich fossil record. Most of the fossil material is attributed to the subgenus Quercus based on leaves, pollen or rarely acorns and nuts. Fossil records of Q. section Cyclobalanopsis characterized by ring-cupped acorns are relatively few and especially those described based on nuts are scant. In this study, we described four new species of Quercus section Cyclobalanopsis based on mummified acorns and nuts: Q. paleodisciformis X.Y. Liu et J.H. Jin sp. nov., Q. paleohui X.Y. Liu et J.H. Jin sp. nov., Q. nanningensis X.Y. Liu et J.H. Jin sp. nov. and Q. yongningensis X.Y. Liu et J.H. Jin sp. nov. These species closely resemble the extant species Q. disciformis, Q. hui, Q. kerrii, and Q. dinghuensis. The occurrence of Q. section Cyclobalanopsis in the Oligocene stratum of Guangxi, South China, suggests that the section has diversified within its extant distribution center since the Oligocene. By combining records from other areas, we propose that the section first appeared in the middle Eocene of East Asia (Sino-Japan), has diversified in situ with a few elements scattering into West Asia and southern Europe since the Oligocene and Pliocene, respectively, and finally became restricted in East Asia since the Pleistocene. This indicates that the section originated and diversified in East Asia, before spreading into West Asia no later than the Oligocene and into southern Europe by the Pliocene. Subsequently it disappeared from South Europe and West Asia due to the appearance of the (summer dry) Mediterranean climate and widespread cooling during the Pleistocene.

Optimization and Deoptimization of Codons in SARS-CoV-2 and Related Implications for Vaccine Development.

The spread of coronavirus disease 2019 (COVID-19), caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), has progressed into a global pandemic. To date, thousands of genetic variants have been identified among SARS-CoV-2 isolates collected from patients. Sequence analysis reveals that the codon adaptation index (CAI) values of viral sequences have decreased over time but with occasional fluctuations. Through evolution modeling, it is found that this phenomenon may result from the virus's mutation preference during transmission. Using dual-luciferase assays, it is further discovered that the deoptimization of codons in the viral sequence may weaken protein expression during virus evolution, indicating that codon usage may play an important role in virus fitness. Finally, given the importance of codon usage in protein expression and particularly for mRNA vaccines, it is designed several codon-optimized Omicron BA.2.12.1, BA.4/5, and XBB.1.5 spike mRNA vaccine candidates and experimentally validated their high levels of expression. This study highlights the importance of codon usage in virus evolution and provides guidelines for codon optimization in mRNA and DNA vaccine development.

Fertile Woodwardia from the middle Eocene of South China and its implications for palaeogeography and palaeoclimate.

The genus Woodwardia, which together with the genera Anchistea and Lorinseria comprise the subfamily Woodwardioideae of Blechnaceae, has a disjunct distribution across Central and North America, Europe and the temperate to tropical areas of Asia. Fossil records of Woodwardia occur throughout the Paleogene and Neogene of North America, Europe and Asia. However, well-preserved fertile pinna fossils of this genus have not yet been reported in South China. In this paper, a new species, W. changchangensis Naugolnykh et Song, sp. nov. is described from the middle Eocene of the Changchang Basin, Hainan Island, South China. Macromorphological and micromorphological features of the fertile pinna show a straight pinna rachis, alternate, subtriangular pinnules, acute pinnule apices, almost entire or slightly undulate pinnule margins, long-ovoid sori, stalked sporangia and spores with wing-like folds on the surface, which are characterised in detail. Overall, the present fossil is most similar to the extant species Woodwardia japonica, which mostly grows in warm and moist environments. The discovery of this new species from the Changchang Basin of Hainan Island indicates that this genus has been distributed in the low-latitude tropical regions of South China from as early as the middle Eocene. Based on this find, and previous studies of other ferns from the same site, we infer that the climate of the Palaeo-Hainan landscape during deposition of the Changchang Formation was warm and humid, similar to conditions prevailing today across this region.

Mummified fruits of Canarium from the upper Pleistocene of South China.

Canarium L. contains approximately 78 species distributed in low to middle altitudes of the Paleotropics and northern Australia. Canarium fruit fossils are known mainly from Paleogene to Neogene of North America, Africa, and Eurasia. Here, we described a new species Canarium maomingense sp. nov. from the upper Pleistocene of the Maoming Basin, Guangdong, South China. Similarly to extant Canarium species, each of three locules of C. maomingense possesses two ovules, but only one or two of six ovules develop into a seed, indicating that the ovules undeveloped into seeds in Canarium species have existed at least since the late Pleistocene. The natural habitats of extant relatives and associated fossil plants suggest subtropical evergreen broad-leaved and mixed forests in the late Pleistocene of this region. Some special damage traces are observed on pyrene surfaces, indicating possible plant interactions with animals and fungi.

An esterase-activatable prodrug formulated liposome strategy: potentiating the anticancer therapeutic efficacy and drug safety.

Liposomal nanomedicine represents a common and versatile carrier for the delivery of both lipophilic and hydrophilic drugs. However, the direct formulation of many chemotherapeutics into a liposomal system remains an enormous challenge. Using the topoisomerase I inhibitor 7-ethyl-10-hydroxycamptothecin (SN38) as a model drug, we combined lipophilic prodrug construction with subsequent integration into an exogenous liposomal scaffold to assemble a prodrug-formulated liposome for systemic administration. Reconstructing SN38 with lipid cholesterol via the esterase-activatable bond endows the resulting prodrug with elevated miscibility with liposomal compositions and esterase-responsive drug release in cancerous cells. The systemic administration of the prodrug-based nanoassemblies (Chol-SN38@LP) exhibited preferential accumulation of therapeutic payloads in tumor lesions. Compared to the SN38 clinical counterpart irinotecan, our prodrug-based nanoassemblies with adaptive features showed elevated therapeutic efficacy (∼1.5 times increase of tumor inhibition) in a preclinical A549 lung carcinoma cell-derived mouse model and improved drug tolerability (i.e., alleviated bloody diarrhea and liver damage) in multiple mice models. These results may be ascribed to extended systemic circulation and preferential tumor accumulation of our nanodrugs. Hence, our findings demonstrate that rational engineering of therapeutic nanomedicine is a promising approach for effective and safe delivery of antitumor chemotherapeutics, especially to rescue drug candidates that have failed in clinical trials owing to poor PK properties or severe toxicity in patients.

Fossil samaras of Ailanthus from South China and their phytogeographic implications.

Ailanthus Desf. (Simaroubaceae), now widespread in southern Asia to northern Australia, was widely distributed in the Northern Hemisphere during the Cenozoic, but has few fossil records at low latitudes. Here we report the fossil samaras of Ailanthus confucii Unger from South China and its occurrences indicate that this genus has been distributed in low latitude regions since the middle Eocene. According to the recent fossil records, Ailanthus is considered to have originated from the Indian subcontinent and dispersed rapidly to East Asia and western North America following the early Paleogene onset of the India-Eurasia collision. In the Eocene, Ailanthus became widespread across the Northern Hemisphere. Subsequent to global cooling, Ailanthus gradually disappeared in the mid-high latitudes and may have continued to spread southward from Asia to northern Australia following the Asia-Australia collision in the late Oligocene, thus forming its modern distribution pattern.

Determinants of genome-wide distribution and evolution of uORFs in eukaryotes.

Upstream open reading frames (uORFs) play widespread regulatory functions in modulating mRNA translation in eukaryotes, but the principles underlying the genomic distribution and evolution of uORFs remain poorly understood. Here, we analyze ~17 million putative canonical uORFs in 478 eukaryotic species that span most of the extant taxa of eukaryotes. We demonstrate how positive and purifying selection, coupled with differences in effective population size (Ne), has shaped the contents of uORFs in eukaryotes. Besides, gene expression level is important in influencing uORF occurrences across genes in a species. Our analyses suggest that most uORFs might play regulatory roles rather than encode functional peptides. We also show that the Kozak sequence context of uORFs has evolved across eukaryotic clades, and that noncanonical uORFs tend to have weaker suppressive effects than canonical uORFs in translation regulation. This study provides insights into the driving forces underlying uORF evolution in eukaryotes.

A Two-Stage Method for Target Searching in the Path Planning for Mobile Robots.

The path planning for target searching in mobile robots is critical for many applications, such as warehouse inspection and caring and surveillance for elderly people in the family scene. To ensure visual complete coverage from the camera equipped in robots is one of the most challenging tasks. To tackle this issue, we propose a two-stage optimization model to efficiently obtain an approximate optimal solution. In this model, we first develop a method to determine the key locations for visual complete coverage of a two-dimensional grid map, which is constructed by drawing lessons from the method of corner detection in the image processing. Then, we design a planning problem for searching the shortest path that passes all key locations considering the frequency of target occurrence. The testing results show that the proposed algorithm can achieve the significantly shorter search path length and the shorter target search time than the current Rule-based Algorithm and Genetic Algorithm (GA) in various simulation cases. Furthermore, the results show that the improved optimization algorithm with the priori known frequency of occurrence of the target can further improve the searching with shorter searching time. We also set up a test in a real environment to verify the feasibility of our algorithm.

On the origin and continuing evolution of SARS-CoV-2.

The SARS-CoV-2 epidemic started in late December 2019 in Wuhan, China, and has since impacted a large portion of China and raised major global concern. Herein, we investigated the extent of molecular divergence between SARS-CoV-2 and other related coronaviruses. Although we found only 4% variability in genomic nucleotides between SARS-CoV-2 and a bat SARS-related coronavirus (SARSr-CoV; RaTG13), the difference at neutral sites was 17%, suggesting the divergence between the two viruses is much larger than previously estimated. Our results suggest that the development of new variations in functional sites in the receptor-binding domain (RBD) of the spike seen in SARS-CoV-2 and viruses from pangolin SARSr-CoVs are likely caused by natural selection besides recombination. Population genetic analyses of 103 SARS-CoV-2 genomes indicated that these viruses had two major lineages (designated L and S), that are well defined by two different SNPs that show nearly complete linkage across the viral strains sequenced to date. We found that L lineage was more prevalent than the S lineage within the limited patient samples we examined. The implication of these evolutionary changes on disease etiology remains unclear. These findings strongly underscores the urgent need for further comprehensive studies that combine viral genomic data, with epidemiological studies of coronavirus disease 2019 (COVID-19).

A Dynamic Part-Attention Model for Person Re-Identification.

Person re-identification (ReID) is gaining more attention due to its important applications in pedestrian tracking and security prevention. Recently developed part-based methods have proven beneficial for stronger and explicit feature descriptions, but how to find real significant parts and reduce miscorrelation between images to improve accuracy of ReID still leaves much room to improve. In this paper, we propose a dynamic part-attention (DPA) method based on masks, which aims to improve the use of variable attention parts. Particularly, a two-branch network with a dynamic loss function is designed to extract features of the global image and the parts of the body separately. With the comprehensive but targeting learning strategy, the proposed method can capture discriminative features based, but not depending on, masks, which guides the whole network to focus on body features more consciously and achieves more robust performance. Our method achieves rank-1 accuracy of 91.68% on public dataset Market1501, and experimental results on three public datasets indicate that the proposed method is effective and achieves favorable accuracy when compared with the state-of-the-art methods.

Associations of urinary polycyclic aromatic hydrocarbons with bone mass density and osteoporosis in U.S. adults, NHANES 2005-2010.

Polycyclic aromatic hydrocarbons (PAHs) are environmental endocrine disruptors, which may modify the bone mineralization. However, epidemiological evidences on this issue were scant. We aimed to investigate the associations of PAHs with bone mass density (BMD) and osteoporosis based on a nationally-representative sample from general U.S. POPULATION: Data utilized were extracted from the 2005-2010 National Health and Nutrition Examination Survey (NHANES). Nine urinary PAHs (U-PAHs) metabolites were measured as exposure biomarkers. Associations of specific U-PAHs with BMD and osteoporosis were estimated by multivariable adjusted linear regression models and logistic regression models, respectively. Compared with women at the first tertiles, those at the third tertiles of 1-Hydroxynapthalene, 2-Hydroxyfluorene, 3-Hydroxyphenanthrene, 2-Hydroxyphenanthrene and 9-Hydroxyfluorene had significantly decreased BMD levels [coefficient (ß) = -0.023 to -0.014, p < 0.05] or increased likelihoods of osteoporosis [odds ratios (ORs) = 1.86 to 3.36, p < 0.05] at different bone sites. Whereas, elevated BMD levels (ß = 0.021, p < 0.05) at trochanter and decreased likelihoods of osteoporosis (OR = 0.33, p < 0.05) at intertrochanter were observed among women at the second tertiles of 1-Hydroxypyrene and 2-Hydroxynapthalene, respectively. Similar results were found for all the population, i.e., combination of men and women. Most of the significant associations disappeared among adult men only. Furthermore, Associations between U-PAHs and BMD were stronger for postmenopausal women when compared with premenopausal group. In conclusion, associations of U-PAHs with BMD and osteoporosis varied by specific U-PAHs and bone sites, as well as menopausal status and genders in U.S. adults.

Distinct effects of rs895819 on risk of different cancers: an update meta-analysis.

Previous studies have indicated an association between the genetic variant in pre-miR-27a rs895819 with A->G transition and cancer risk; however, the results remain inconsistent and somehow conflicting in different cancers. Therefore, to obtain a more reliable conclusion, we performed an update meta-analysis by searching PubMed database or other databases. Odds ratio (ORs) and 95% confidence interval (CIs) were calculated to evaluate cancer risk. A total of 34 case-control studies involving 15,388 cases and 18,704 controls were included. The results showed that rs895819 was associated with an increased cancer risk (GG vs. AA/AG: OR = 1.15, 95% CI = 1.02-1.29). Furthermore, stratification analyses revealed an association of rs895819 with increased cancer risk among Asians (GG vs. AA: OR = 1.17, 95% CI = 1.01-1.36; GG vs. AA/AG: OR = 1.18, 95% CI = 1.03-1.35), but not Caucasians. Interestingly, the [G] allele of rs895819 was significantly associated with decreased risk of breast cancer (G vs. A: OR = 0.91, 95% CI = 0.86-0.97). However, rs895819 was associated with increased risk of colorectal cancer (GG vs. AA: OR = 1.56, 95% CI = 1.31-1.85; GG vs. AA/AG: OR = 1.53, 95% CI = 1.30-1.79; G vs. A: OR = 1.19, 95% CI = 1.09-1.30) and lung cancer (GG vs. AA/AG: OR = 1.43, 95% CI = 1.00-2.04). In addition, no association was found between rs895819 and risk of gastric cancer or esophageal cancer. In conclusion, our findings suggest distinct effects of rs895819 on risk of different cancers, and future well-designed studies with large samples are required to further validate our results.

Estimation of red-light running frequency using high-resolution traffic and signal data.

Red-light-running (RLR) emerges as a major cause that may lead to intersection-related crashes and endanger intersection safety. To reduce RLR violations, it's critical to identify the influential factors associated with RLR and estimate RLR frequency. Without resorting to video camera recordings, this study investigates this important issue by utilizing high-resolution traffic and signal event data collected from loop detectors at five intersections on Trunk Highway 55, Minneapolis, MN. First, a simple method is proposed to identify RLR by fully utilizing the information obtained from stop bar detectors, downstream entrance detectors and advance detectors. Using 12 months of event data, a total of 6550 RLR cases were identified. According to a definition of RLR frequency as the conditional probability of RLR on a certain traffic or signal condition (veh/1000veh), the relationships between RLR frequency and some influential factors including arriving time at advance detector, approaching speed, headway, gap to the preceding vehicle on adjacent lane, cycle length, geometric characteristics and even snowing weather were empirically investigated. Statistical analysis shows good agreement with the traffic engineering practice, e.g., RLR is most likely to occur on weekdays during peak periods under large traffic demands and longer signal cycles, and a total of 95.24% RLR events occurred within the first 1.5s after the onset of red phase. The findings confirmed that vehicles tend to run the red light when they are close to intersection during phase transition, and the vehicles following the leading vehicle with short headways also likely run the red light. Last, a simplified nonlinear regression model is proposed to estimate RLR frequency based on the data from advance detector. The study is expected to helpbetter understand RLR occurrence and further contribute to the future improvement of intersection safety.

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

Influential factors of red-light running at signalized intersection and prediction using a rare events logistic regression model.

Red light running (RLR) has become a major safety concern at signalized intersection. To prevent RLR related crashes, it is critical to identify the factors that significantly impact the drivers' behaviors of RLR, and to predict potential RLR in real time. In this research, 9-month's RLR events extracted from high-resolution traffic data collected by loop detectors from three signalized intersections were applied to identify the factors that significantly affect RLR behaviors. The data analysis indicated that occupancy time, time gap, used yellow time, time left to yellow start, whether the preceding vehicle runs through the intersection during yellow, and whether there is a vehicle passing through the intersection on the adjacent lane were significantly factors for RLR behaviors. Furthermore, due to the rare events nature of RLR, a modified rare events logistic regression model was developed for RLR prediction. The rare events logistic regression method has been applied in many fields for rare events studies and shows impressive performance, but so far none of previous research has applied this method to study RLR. The results showed that the rare events logistic regression model performed significantly better than the standard logistic regression model. More importantly, the proposed RLR prediction method is purely based on loop detector data collected from a single advance loop detector located 400 feet away from stop-bar. This brings great potential for future field applications of the proposed method since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly.

Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery.

Driven by the prominent thermal signature of humans and following the growing availability of unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on the detection and tracking of pedestrians using thermal infrared images recorded from UAVs. However, pedestrian detection and tracking from the thermal images obtained from UAVs pose many challenges due to the low-resolution of imagery, platform motion, image instability and the relatively small size of the objects. This research tackles these challenges by proposing a pedestrian detection and tracking system. A two-stage blob-based approach is first developed for pedestrian detection. This approach first extracts pedestrian blobs using the regional gradient feature and geometric constraints filtering and then classifies the detected blobs by using a linear Support Vector Machine (SVM) with a hybrid descriptor, which sophisticatedly combines Histogram of Oriented Gradient (HOG) and Discrete Cosine Transform (DCT) features in order to achieve accurate detection. This research further proposes an approach for pedestrian tracking. This approach employs the feature tracker with the update of detected pedestrian location to track pedestrian objects from the registered videos and extracts the motion trajectory data. The proposed detection and tracking approaches have been evaluated by multiple different datasets, and the results illustrate the effectiveness of the proposed methods. This research is expected to significantly benefit many transportation applications, such as the multimodal traffic performance measure, pedestrian behavior study and pedestrian-vehicle crash analysis. Future work will focus on using fused thermal and visual images to further improve the detection efficiency and effectiveness.