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ObjectiveBacterial vaginosis is a disease caused by vaginal microecology disorder, which seriously affects female health. At present, there are many drugs to treat BV, and this study aims to compare the efficacy and safety of multiple drugs for BV through a network meta-analysis (NMA).MethodsAll studies were sourced from PubMed and Embase databases from the establishment date to April 13, 2023. We evaluated the clinical cure success rate and adverse effects (abnormal increase in vaginal discharge, external genital irritation, and vulvar itching) and performed subgroup analyses of the clinical cure success rate for different modes of administration. All statistical analyses were performed using R and STATA 14.0 software for network meta-analysis.ResultsWe included 42 studies that met the criteria, involving a total of 8382 patients. Network meta-analysis results showed that metronidazole and secnidazole had a higher rate of adverse reactions than placebo (RR 7.06; 95%-CI 2.61-19.10, RR 4.03; 95%-CI 1.63-9.98), the adverse reaction rate of probiotics group was lower than that of metronidazole group (RR 0.44; 95%-CI 0.21-0.93). The clinical cure rate of oral ornidazole was better than clindamycin (RR 16.08; 95%-CI 1.72-150.47), Secnidazole (RR 8.17; 95%-CI 1.66-40.25) and probiotics. Direct meta-analysis results showed that ornidazole had a better clinical cure rate than Secnidazole (RR 1.22; 95%-CI 1.10-1.34), oral ornidazole had a better clinical cure rate than Secnidazole (RR 1.23; 95%-CI 1.11-1.36). The clinical cure rate of vaginal application of sucrose was better than metronidazole (RR 1.12; 95%-CI 1.03-1.21) and metronidazole had a lower clinical cure rate than probiotics (RR 0.68; 95%-CI 0.52-0.88).ConclusionsThe results of this systematic review and network meta-analysis suggest that ornidazole may be an effective alternative for the treatment of BV, and that sucrose and probiotics are potential BV treatments that need to be validated by more high-quality clinical studies in the future.

Abstract Cistrome‐wide association studies (CWAS) are pivotal for identifying genetic determinants of diseases by correlating genetically regulated cistrome states with phenotypes. Traditional CWAS typically develops a model based on cistrome and genotype data to associate predicted cistrome states with phenotypes. The random effect cistrome‐wide association study (RECWAS), reevaluates the necessity of cistrome state prediction in CWAS. RECWAS utilizes either a linear model or marginal effect for initial feature selection, followed by kernel‐based feature aggregation for association testing is introduced. Through simulations and analysis of prostate cancer data, a thorough evaluation of CWAS and RECWAS is conducted. The results suggest that RECWAS offers improved power compared to traditional CWAS, identifying additional genomic regions associated with prostate cancer. CWAS identified 102 significant regions, while RECWAS found 50 additional significant regions compared to CWAS, many of which are validated. Validation encompassed a range of biological evidence, including risk signals from the GWAS catalog, susceptibility genes from the DisGeNET database, and enhancer‐domain scores. RECWAS consistently demonstrated improved performance over traditional CWAS in identifying genomic regions associated with prostate cancer. These findings demonstrate the benefits of incorporating kernel methods into CWAS and provide new insights for genetic discovery in complex diseases.

Anisodus tanguticus (Maxim.) Pascher, a distinctive medicinal plant native to the Qinghai-Tibet Plateau, China, has garnered attention due to increasing market demand. This study explores the impact of environmental factors on the distribution and levels of active compounds namely anisodamine, anisodine, and atropine within A. tanguticus. Our goal was to identify suitable cultivation areas for this plant. This study employs the maximum entropy model to simulate the suitable area of A. tanguticus under current conditions and three climate change scenarios during the 2050s and 2070s. The finding revealed that altitude, precipitation in the warmest season (Bio 18), the average annual temperature (Bio 1) exerted significant influences on the distribution of A. tanguticus. Among the environmental factors considered, temperature difference between day and night (Bio 2) had the most substantial impact on the distribution of anisodamine, temperature seasonal variation variance (Bio 4) predominantly influenced anisodine distribution, and Bio 1 had the greatest effected on the distribution of atropine. The suitable areas primarily exist in the eastern Qinghai-Tibet Plateau in China, encompassing a total area of 30.78 × 104 km2. Under the climate scenarios for the future, the suitable areas exhibit increasing trends of approximately 30.2%, 30.3%, and 39.8% by the 2050s, and 25.1%, 48.8%, and 60.1% by the 2070s. This research would provide theoretical suggestions for the protection, and cultivation management of A. tanguticus resources to face the challenge of global climate change.

Abstract Predators significantly impact the development process and subsequently influence the metamorphic decisions of amphibian larvae. Larvae often exhibit induced growth and metamorphic plasticity in response to the presence of predators. However, growth and development rates are not always perfectly correlated, growth responses can vary throughout ontogeny. It is crucial to consider the stage‐specific growth responses induced by predators. Here, we employ a critical windows experimental design and examine development‐related growth and metamorphic responses to predators in the endangered Chinhai spiny newt (Echinotriton chinhaiensis). Our findings reveal that predators constrain the development process of spiny newt larvae and also impact survival to metamorphosis. Inducible plasticity predominantly exhibits in the early and middle stages of larval development. Our results also suggest that diverse developmental plasticity has been adopted by larvae in response to predators. The presence of predators during early stage induces larvae to exhibit a same size at metamorphosis but a prolonged time to metamorphosis, while predators present during middle stage induce larvae to exhibit a large size at metamorphosis but a same time to metamorphosis. The presence of predators at the late developmental stage does not induce any plasticity in larval growth and metamorphosis. Moreover, these results also suggest that several stages of larval development are likely critical developmental windows for spiny newt larvae. This study not only provides basic biological information on predator‐induced developmental plasticity of the endangered Chinhai spiny newt but also likely provides biological insights for the implementation of in situ conservation and preservation efforts for endangered species.

Abstract Background Although it is well recognized that core root microorganisms contribute to plant health and productivity, little is known about their role to the accumulation of secondary metabolites. The roots of Anisodus tanguticus, a traditional herbal medication utilized by Tibetan medicine, are rich in tropane alkaloids. We collected wild A. tanguticus populations throughout a 1500 km transect on the Qinghai-Tibetan Plateau. Results Our results showed that despite sampling at a distance of 1500 km, the root of A. tanguticus selectively recruits core root bacteria. We obtained 102 root bacterial core OTUs, and although their number only accounted for 2.99% of the total, their relative abundance accounted for 73% of the total. Spearman correlation and random forest analyses revealed that the composition of core root microbiomes was related to anisodine contents, aboveground biomass and nitrogen contents of Anisodus tanguticus. Among them, the main role is played by Rhizobacter, Variovorax, Polaromonas, and Mycobacterium genus that are significantly enriched in roots. Functional prediction by FAPROTAX showed that nitrogen-cycling microorganisms and pathogenic bacteria are strongly associated with anisodine contents, aboveground biomass and nitrogen contents of Anisodus tanguticus. Conclusions Our findings show that the root selectively recruits core root bacteria and revealed that the core microbiomes and microbial functions potentially contributed to the anisodine contents, aboveground biomass and nitrogen contents of the plant. This work may increase our understanding of the interactions between microorganisms and plants and improve our ability to manage root microbiota to promote sustainable production of herbal medicines.

Hynobius amjiensis, also known as the Anji salamander, is an amphibian species currently categorized as endangered due to its limited geographical distribution, primarily in China. To address the critical conservation status of this species, artificial breeding is essential for population expansion. However, progress in artificial breeding efforts has been hindered by the scarcity of research on the reproductive biology of the Anji salamander. In this study, we identified 25 distinct early stages of embryo development. Additionally, we observed that Anji salamander embryos contain a lesser amount of yolk compared to other salamanders or frogs. We further discovered that the Anji salamander employs a highly competitive reproductive strategy, producing a smaller number of high-quality offspring. This strategy aims to generate adaptive individuals through intense intraspecific competition, driven by three factors: extremely confined breeding habitats, a substantial number of eggs, and a reduced yolk content. We introduce the term “mass escape” to describe this strategy, which provides a novel perspective on cannibalization, focusing on the consumption of specific body parts rather than a single-individual activity. This study offers valuable insights into artificial breeding techniques designed to mitigate inherent intraspecific competitive pressure, thereby improving metamorphosis and survival rates. Additionally, it provides a comprehensive table detailing the pre-embryonic developmental stages of the Anji salamander.

Abstract The relationship between spatial distribution and phylogeny has been widely debated in recent decades. To understand biogeographic and evolutionary history relationships and to explore the interspecific similarities and phylogenetic correlations of niche characteristics, we collected and recorded all distribution points for eight species of rhubarb on the Qinghai‐Tibet Plateau, used different methods to describe the ecological niche, and explored the relationship between phylogeny, ecological niche, and distribution range. The results reveal that: (1) the ranges of optimal environmental variables for species with close kinship are not exactly the same, ecologically similar species are not necessarily sister species, and the overlap of rhubarb has no significant correlation with phylogeny. Therefore, the impact of ecological dimensions on species formation is greater than that of geographical latitude for the eight species of rhubarb. (2) Among the eight species of rhubarb, the breadth of ecological niche is positively correlated with the current suitable habitat area and negatively correlated with fluctuations in future suitable habitat area. In the future, except for Rheum tanguticum and Rheum palmatum, the suitable planting areas for the other six species of rhubarb will decrease as greenhouse gas emissions concentrations and time increase. Therefore, species with smaller ecological niches are at a greater risk of habitat loss compared to species with larger ecological niches. (3) In both existing and future distribution prediction models of rhubarb, we observed that both the widely distributed Rheum spiciforme and the niche narrow Rheum nobile, all eight species of rhubarb are present in the Hengduan Mountains, based on our analysis, we propose that the Hengduan Mountains should be regarded as a priority conservation area for rhubarb, to preserve the species' biodiversity. Our study lays the groundwork for identifying evolutionary trends in ecological specialization.

Anisodus tanguticus (Maxinowicz) Pascher (Solanaceae) is a traditional Chinese herb that is widely used in folklore and clinical practice. In recent years, wild populations have been severely impacted to the point of extinction due to over-harvesting and reclamation. Therefore, artificial cultivation is important to relieve the pressure of market demand and protect wild plant resources. Using a “3414” fertilization design, i.e., 3 factors (N, P, and K), 4 levels, and 14 fertilization treatments, with 3 replicates and a total of 42 experimental plots, A. tanguticus was harvested in October 2020, June 2021, August 2021, and October 2021, and the yield and alkaloid content were determined. The study aimed to provide a theoretical basis and technical reference for the standardization of A. tanguticus cultivation. Biomass accumulation and alkaloid content showed a trend of increasing and then decreasing with the application of nitrogen, phosphorus, and potassium, and the biomass accumulation was the highest at the application levels of nitrogen and phosphorus in T6 and T9 and at the application levels of medium and low potassium. The alkaloid content showed an increasing trend between October of the first year and June of the second year and a decreasing trend in the second year with the increase in the harvesting period. Yield and alkaloid yield showed a decreasing trend between October of the first year and June of the second year and an increasing trend in the second year with the increase in the harvesting period. The recommended application rates are 225–300 kg/ha2 for nitrogen, 850–960 kg/ha2 for phosphorus, and 65–85 kg/ha2 for potassium.

Anisodus tanguticus (Maxim.) Pascher, a medicinal plant growing in the Tibetan Plateau region with various medicinal values, is mainly used for the extraction of tropane alkaloids (TAs), and the increased demand for A. tanguticus has triggered its overexploitation. The cultivation of this plant is necessary for the quality control and conservation of wild resources. During 2020 and 2021, a split-plot experiment with three replicates was used to study different planting densities (D1: 30 × 50 cm; D2: 40 × 50 cm; D3: 50 × 50 cm; D4: 60 × 50 cm) and different growth periods (first withering period: October 2020; greening period: June 2021; growth period: August 2021; second withering period: October 2021) on the yield and alkaloid content (atropine, scopolamine, anisodamine, anisodine) of A. tanguticus. The results showed that the mass per plant of A. tanguticus was higher at low density, while the yield per unit area of the underground parts (25288.89 kg/ha) was greater at high density, and the mass of the aboveground parts (14933.33 kg/ha) was higher at low density. The anisodamine (0.0467%) and anisodine (0.1201%) content of D2 (40 cm × 50 cm) was significantly higher than that of the other densities during the green period. The content of all four alkaloids was highest during the greening period, and the scopolamine, anisodamine, and anisodine content was higher in the aboveground parts than in the underground parts. The total alkaloid accumulation per unit area of the whole plant reached its maximum value (1.08%, 139.48 kg/ha) in the growth period of D2; therefore, for economic efficiency and the selection of the best overall quality, it was concluded that the aboveground parts also had medicinal value, the growth period was the best harvesting period, and D2 (40 cm × 50 cm) was the best planting density for A. tanguticus.

Navigation, environment perception and localization are important capabilities of intelligent vehicles. In this paper, environmental perception and localization from binocular vision are studied. First, an outdoor feature point extraction algorithm that uses a local adaptive threshold is proposed to acquire environmental information. The algorithm filters feature points by setting adaptive parameters and calculating each pixel threshold with a dynamic local threshold. Second, an accurate method for feature point tracking is proposed for localization. We present exhaustive evaluation in 4 major scenarios from the most popular datasets. Evaluating the proposed method with traditional and state-of-the-art extraction methods and experimental results demonstrates that when the brightness decreases or increases, the performance of the proposed method is stable in terms of the number of feature points, the calculation speed and the overall repetition rate. Our proposed tracking method outperforms state-of-the-art tracking methods in terms of the root mean square error (RMSE) and the errors in the dimensions in the scenarios.

As an important Tibetan medicine and a secondary protected plant in China, Pomatosace filicula is endemic to the country and is mainly distributed in the Qinghai–Tibet Plateau (QTP). However, global climate change caused by greenhouse gas emissions might lead to the extinction of P. filicula. To understand the potential spatial distribution of P. filicula in future global warming scenarios, we used the MaxEnt model to simulate changes in its suitable habitat that would occur by 2050 and 2070 using four representative concentration pathway (RCP) scenarios and five global climate models. The results showed that the QTP currently contains a suitable habitat for P. filicula and will continue to do so in the future. Under the RCP2.6 scenario, the suitable habitat area would increase by 2050 but shrink slightly by 2070, with an average reduction of 2.7%. However, under the RCP8.5 scenario, the area of unsuitable habitat would expand by an average of 54.65% and 68.20% by 2050 and 2070, respectively. The changes in the area of suitable habitat under the RCP4.5 and RCP6.0 scenarios were similar, with the unsuitable area increasing by approximately 20% by 2050 and 2070. Under these two moderate RCPs, the total suitable area in 2070 would be greater than that in 2050. The top three environmental factors impacting the habitat distribution were altitude, annual precipitation (BIO12) and annual temperature range (BIO7). The cumulative contribution rate of these three factors was as high as 82.8%, indicating that they were the key factors affecting the distribution and adaptability of P. filicula, P. filicula grows well in damp and cold environments. Due to global warming, the QTP will become warmer and drier; thus, the growing area of P. filicula will move toward higher elevations and areas that are humid and cold. These areas are mainly found near the Three-River Region. Future climate change will aggravate the deterioration of the P. filicula habitat and increase the species’ survival risk. This study describes the distribution of P. filicula and provides a basis for the protection of endangered plants in the QTP.

The Anji Salamander, Hynobius amjiensis Gu, 1992, is a critically endangered amphibian only known from a few mountain tops in the Zhejiang and Anhui Provinces of China. Along with tremendous efforts to breed this species in captivity, there have been attempts to understand the causes for its endangered status from a genetic perspective, which was limited to a few markers from earlier studies. Here we used next-generation sequencing technology on the DNASEQ platform to investigate the characteristics of the salamander’s genome. Based on k-mer analysis, the 19-mer frequency distribution yielded the optimal estimation that suggested a genome size of ~17.54 Gb, 70.77% of which consist of repetitive sequences. Filtered sequences were assembled in 8,852,165 contigs with N50 at 1052 bp; GC rate was 45.3%. We identified 1,441,045 microsatellite loci across the assembled partial genome. Mono-nucleotide microsatellites accounted for 61.4% of all loci, and 2 to 6-base repeat motifs are present at a frequency of 19.59.67.91.5and 0.06%, respectively. PCR primers were developed for 98 microsatellite loci with 2 to 6-base motifs. Our work provides an overview of the genome characteristics of H. amjiensis that can serve subsequent studies on the evolutionary history of this endangered salamander. [ABSTRACT FROM AUTHOR]

The computer-assisted inverse design of photonic computing, especially by leveraging artificial intelligence algorithms, offers great convenience to accelerate the speed of development and improve calculation accuracy. However, traditional thickness-based modulation methods are hindered by large volume and difficult fabrication process, making it hard to meet the data-driven requirements of flexible light modulation. Here, we propose a diffractive deep neural network (D2NN) framework based on a three-layer all-dielectric phased transmitarray as hidden layers, which can perform the classification of handwritten digits. By tailoring the radius of a silicon nanodisk of a meta-atom, the metasurface can realize the phase profile calculated by D2NN and maintain a relative high transmittance of 0.9 at a wavelength of 600 nm. The designed image classifier consists of three layers of phase-only metasurfaces, each of which contains 1024 units, mimicking a fully connected neural network through the diffraction of light fields. The classification task of handwriting digits from the ‘0’ to ‘5’ dataset is verified, with an accuracy of over 90% on the blind test dataset, as well as demonstrated by the full-wave simulation. Furthermore, the performance of the more complex animal image classification task is also validated by increasing the number of neurons to enhance the connectivity of the neural network. This study may provide a possible solution for practical applications such as biomedical detection, image processing, and machine vision based on all-optical computing.

Abstract Lipophilicity is a fundamental physical property that significantly affects various aspects of drug behavior, including solubility, permeability, metabolism, distribution, protein binding, and toxicity. Accurate prediction of lipophilicity, measured by the logD7.4 value (the distribution coefficient between n-octanol and buffer at physiological pH 7.4), is crucial for successful drug discovery and design. However, the limited availability of data for logD modeling poses a significant challenge to achieving satisfactory generalization capability. To address this challenge, we have developed a novel logD7.4 prediction model called RTlogD, which leverages knowledge from multiple sources. RTlogD combines pre-training on a chromatographic retention time (RT) dataset since the RT is influenced by lipophilicity. Additionally, microscopic pKa values are incorporated as atomic features, providing valuable insights into ionizable sites and ionization capacity. Furthermore, logP is integrated as an auxiliary task within a multitask learning framework. We conducted ablation studies and presented a detailed analysis, showcasing the effectiveness and interpretability of RT, pKa, and logP in the RTlogD model. Notably, our RTlogD model demonstrated superior performance compared to commonly used algorithms and prediction tools. These results underscore the potential of the RTlogD model to improve the accuracy and generalization of logD prediction in drug discovery and design. In summary, the RTlogD model addresses the challenge of limited data availability in logD modeling by leveraging knowledge from RT, microscopic pKa, and logP. Incorporating these factors enhances the predictive capabilities of our model, and it holds promise for real-world applications in drug discovery and design scenarios. Graphical Abstract

Abstract Three-dimensional (3D) conformations of a small molecule profoundly affect its binding to the target of interest, the resulting biological effects, and its disposition in living organisms, but it is challenging to accurately characterize the conformational ensemble experimentally. Here, we proposed an autoregressive torsion angle prediction model Tora3D for molecular 3D conformer generation. Rather than directly predicting the conformations in an end-to-end way, Tora3D predicts a set of torsion angles of rotatable bonds by an interpretable autoregressive method and reconstructs the 3D conformations from them, which keeps structural validity during reconstruction. Another advancement of our method over other conformational generation methods is the ability to use energy to guide the conformation generation. In addition, we propose a new message-passing mechanism that applies the Transformer to the graph to solve the difficulty of remote message passing. Tora3D shows superior performance to prior computational models in the trade-off between accuracy and efficiency, and ensures conformational validity, accuracy, and diversity in an interpretable way. Overall, Tora3D can be used for the quick generation of diverse molecular conformations and 3D-based molecular representation, contributing to a wide range of downstream drug design tasks. Graphical Abstract

Synthetic lethal (SL) pairs are pairs of genes whose simultaneous loss-of-function results in cell death, while a damaging mutation of either gene alone does not affect the cell’s survival. This makes SL pairs attractive targets for precision cancer therapies, as targeting the unimpaired gene of the SL pair can selectively kill cancer cells that already harbor the impaired gene. Limited by the difficulty of finding true SL pairs, especially on specific cell types, current computational approaches provide only limited insights because of overlooking the crucial aspects of cellular context dependency and mechanistic understanding of SL pairs. As a result, the identification of SL targets still relies on expensive, time-consuming experimental approaches. In this work, we applied cell-line specific multi-omics data to a specially designed deep learning model to predict cell-line specific SL pairs. Through incorporating multiple types of cell-specific omics data with a self-attention module, we represent gene relationships as graphs. Our approach achieves the prediction of SL pairs in a cell-specific manner and demonstrates the potential to facilitate the discovery of cell-specific SL targets for cancer therapeutics, providing a tool to unearth mechanisms underlying the origin of SL in cancer biology. The code and data of our approach can be found at https://github.com/promethiume/SLwise

Parity-time (PT) symmetric photonic systems have attracted much attention due to their intriguing properties and asymmetric behaviors. In this paper, we propose a plasmonic nanoantenna with PT-symmetric potential for unidirectional scattering functionality. The studied plasmonic nanoantenna is comprised of three metallic layers separated by two dielectric layers. Such kind of system, with the same coefficient κ of loss and gain in each of the two dielectric layers, holds the characteristic of PT symmetry. We show that the unidirectional scattering is obtained for the passive structure (i.e., κ = 0), and the switching between forward and backward directionality can be achieved with a single structure by changing the excitation wavelength, when the induced electric dipole (ED) and magnetic dipole (MD) modes satisfy the first or second Kerker conditions, respectively. In addition, we find that the forward-to-backward ratio spectra can be strongly affected by the non-Hermiticity parameter κ. In particular, it is possible to reverse the radiation direction at the same wavelength in a wide spectra band by adjusting κ. Moreover, putting the nanoantennas in an array of transverse configuration can efficiently narrow the main lobe angular beam width to be

In this paper, we propose a hybrid metallo-dielectric core-shell nanorod for the Kerker-type effect at two different frequencies. The effect arises from the interference of the scattering waves of the nanorod, which are generated by the magnetic dipole moment (MD) of the high-index hollow particle and the electric dipole moment (ED) induced in both metallic and dielectric particles. Interestingly, we find that such kind of unidirectional radiation properties, (i.e., zero back scattering occurring at dual frequencies) can be sustained with a single nanorod, which usually being equivalent to a local electric dipole source. The effect of substrate is also considered to investigate the typical experimental realization for the dual-frequency unidirectionalities of the nanoantenna. Furthermore, the unidirectionality can be further improved by the design of one-dimensional array of the hybrid nanoantenna. Our results could provide an additional degree of freedom for light scattering manipulation, and widen the versatile applications in nanoantennas, optical sensor, light emitters, as well as photovoltaic devices.

Recently, the study of analog optical computing raised renewed interest due to its natural advantages of parallel, high speed and low energy consumption over conventional digital counterpart, particularly in applications of big data and high-throughput image processing. The emergence of metamaterials or metasurfaces in the last decades offered unprecedented opportunities to arbitrarily manipulate the light waves within subwavelength scale. Metamaterials and metasurfaces with freely controlled optical properties have accelerated the progress of wave-based analog computing and are emerging as a practical, easy-integration platform for optical analog computing. In this review, the recent progress of metamaterial-based spatial analog optical computing is briefly reviewed. We first survey the implementation of classical mathematical operations followed by two fundamental approaches (metasurface approach and Green’s function approach). Then, we discuss recent developments based on different physical mechanisms and the classical optical simulating of quantum algorithms are investigated, which may lead to a new way for high-efficiency signal processing by exploiting quantum behaviors. The challenges and future opportunities in the booming research field are discussed.