Genomic variation in montane bumblebees in Scandinavia: High levels of intraspecific diversity despite population vulnerability.

Populations of many bumblebee species are declining, with distributions shifting northwards to track suitable climates. Climate change is considered a major contributing factor. Arctic species are particularly vulnerable as they cannot shift further north, making assessment of their population viability important. Analysis of levels of whole-genome variation is a powerful way to analyse population declines and fragmentation. Here, we use genome sequencing to analyse genetic variation in seven species of bumblebee from the Scandinavian mountains, including two classified as vulnerable. We sequenced 333 samples from across the ranges of these species in Sweden. Estimates of effective population size (NE ) vary from ~55,000 for species with restricted high alpine distributions to 220,000 for more widespread species. Population fragmentation is generally very low or undetectable over large distances in the mountains, suggesting an absence of barriers to gene flow. The relatively high NE and low population structure indicate that none of the species are at immediate risk of negative genetic effects caused by high levels of genetic drift. However, reconstruction of historical fluctuations in NE indicates that the arctic specialist species Bombus hyperboreus has experienced population declines since the last ice age and we detected one highly inbred diploid male of this species close to the southern limit of its range, potentially indicating elevated genetic load. Although the levels of genetic variation in montane bumblebee populations are currently relatively high, their ranges are predicted to shrink drastically due to the effects of climate change and monitoring is essential to detect future population declines.

Deep learning to assist composition classification and thyroid solid nodule diagnosis: a multicenter diagnostic study.

OBJECTIVES: This study aimed to propose a deep learning (DL)-based framework for identifying the composition of thyroid nodules and assessing their malignancy risk. METHODS: We conducted a retrospective multicenter study using ultrasound images from four hospitals. Convolutional neural network (CNN) models were constructed to classify ultrasound images of thyroid nodules into solid and non-solid, as well as benign and malignant. A total of 11,201 images of 6784 nodules were used for training, validation, and testing. The area under the receiver-operating characteristic curve (AUC) was employed as the primary evaluation index. RESULTS: The models had AUCs higher than 0.91 in the benign and malignant grading of solid thyroid nodules, with the Inception-ResNet AUC being the highest at 0.94. In the test set, the best algorithm for identifying benign and malignant thyroid nodules had a sensitivity of 0.88, and a specificity of 0.86. In the human vs. DL test set, the best algorithm had a sensitivity of 0.93, and a specificity of 0.86. The Inception-ResNet model performed better than the senior physicians (p < 0.001). The sensitivity and specificity of the optimal model based on the external test set were 0.90 and 0.75, respectively. CONCLUSIONS: This research demonstrates that CNNs can assist thyroid nodule diagnosis and reduce the rate of unnecessary fine-needle aspiration (FNA). CLINICAL RELEVANCE STATEMENT: High-resolution ultrasound has led to increased detection of thyroid nodules. This results in unnecessary fine-needle aspiration and anxiety for patients whose nodules are benign. Deep learning can solve these problems to some extent. KEY POINTS: • Thyroid solid nodules have a high probability of malignancy. • Our models can improve the differentiation between benign and malignant solid thyroid nodules. • The differential performance of one model was superior to that of senior radiologists. Applying this could reduce the rate of unnecessary fine-needle aspiration of solid thyroid nodules.

Deep learning approaches for differentiating thyroid nodules with calcification: a two-center study.

BACKGROUND: Calcification is a common phenomenon in both benign and malignant thyroid nodules. However, the clinical significance of calcification remains unclear. Therefore, we explored a more objective method for distinguishing between benign and malignant thyroid calcified nodules. METHODS: This retrospective study, conducted at two centers, involved a total of 631 thyroid nodules, all of which were pathologically confirmed. Ultrasound image sets were employed for analysis. The primary evaluation index was the area under the receiver-operator characteristic curve (AUROC). We compared the diagnostic performance of deep learning (DL) methods with that of radiologists and determined whether DL could enhance the diagnostic capabilities of radiologists. RESULTS: The Xception classification model exhibited the highest performance, achieving an AUROC of up to 0.970, followed by the DenseNet169 model, which attained an AUROC of up to 0.959. Notably, both DL models outperformed radiologists (P < 0.05). The success of the Xception model can be attributed to its incorporation of deep separable convolution, which effectively reduces the model's parameter count. This feature enables the model to capture features more effectively during the feature extraction process, resulting in superior performance, particularly when dealing with limited data. CONCLUSIONS: This study conclusively demonstrated that DL outperformed radiologists in differentiating between benign and malignant calcified thyroid nodules. Additionally, the diagnostic capabilities of radiologists could be enhanced with the aid of DL.

Methyltransferases of gentamicin biosynthesis.

Gentamicin C complex from Micromonospora echinospora remains a globally important antibiotic, and there is revived interest in the semisynthesis of analogs that might show improved therapeutic properties. The complex consists of five components differing in their methylation pattern at one or more sites in the molecule. We show here, using specific gene deletion and chemical complementation, that the gentamicin pathway up to the branch point is defined by the selectivity of the methyltransferases GenN, GenD1, and GenK. Unexpectedly, they comprise a methylation network in which early intermediates are ectopically modified. Using whole-genome sequence, we have also discovered the terminal 6'-N-methyltransfer required to produce gentamicin C2b from C1a or gentamicin C1 from C2, an example of an essential biosynthetic enzyme being located not in the biosynthetic gene cluster but far removed on the chromosome. These findings fully account for the methylation pattern in gentamicins and open the way to production of individual gentamicins by fermentation, as starting materials for semisynthesis.

Two New Nonenolides from Diaporthe sp. SXZ-19, an Endophytic Fungus of Camptotheca Acuminata.

Two new nonenolides named diaportheolides A (1) and B (2) were isolated from the endophytic fungus Diaporthe sp. SXZ-19 of Camptotheca acuminata. The chemical structures of 1 and 2 were elucidated by spectroscopic analyses, including 1D- and 2D-NMR experiments and HR-ESI-MS data analysis. Their in vitro antibacterial activities are established to be insignificant.

Production of 3-desmethyl protostreptovaricin I from the genetically engineered Streptomyces spectabilis CCTCC M2017417.

A new streptovaricin analogue, namely 3-desmethyl protostreptovaricin I (1), was isolated from the culture of the genetically engineered strain ΔstvM2 derived from Streptomyces spectabilis CCTCC M2017417. Its structure was elucidated on the basis of extensive spectroscopic analyses, including 1D and 2D NMR tests, and high resolution mass spectrometry analysis. Compound 1 is the first example of 3-desmethyl streptovaricin analogues reported so far, however, it showed no antibacterial activities against Staphylococcus aureus ATCC 29213.

Ansavaricin J, a New Heterocyclic Ring-Fused Streptovaricin from Gene stvP5-Deleted Mutant of Streptomyces spectabilis CCTCC M2017417.

A new ring-fused streptovaricin analogue, named ansavaricin J, was unprecedently isolated from the culture of the genetically modified strains ΔstvP5 which derived from Streptomyces spectabilis CCTCC M2017417. Its structure was elucidated via comprehensive spectroscopic analyses, including 1D- and 2D-NMR tests, and HR-ESI-MS data analysis. Notably, ansavaricin J and E represent the only two reported examples of heterocyclic ring-fused streptovaricins thus far, however, it only showed insignificant antibacterial activities against Staphylococcus aureus.

Behavioral Acoustic Emanations: Attack and Verification of PIN Entry Using Keypress Sounds.

This paper explores the security vulnerability of Personal Identification Number (PIN) or numeric passwords. Entry Device (PEDs) that use small strings of data (PINs, keys or passwords) as means of verifying the legitimacy of a user. Today, PEDs are commonly used by personnel in different industrial and consumer electronic applications, such as entry at security checkpoints, ATMs and customer kiosks, etc. In this paper, we propose a side-channel attack on a 4-6 digit random PIN key, and a PIN key user verification method. The intervals between two keystrokes are extracted from the acoustic emanation and used as features to train machine-learning models. The attack model has a 60% chance to recover the PIN key. The verification model has an 88% accuracy on identifying the user. Our attack methods can perform key recovery by using the acoustic side-channel at low cost. As a countermeasure, our verification method can improve the security of PIN entry devices.

Gene Expression and Functional Analyses of Odorant Receptors in Small Hive Beetles (Aethina tumida).

Olfaction is key to many insects. Odorant receptors (ORs) stand among the key chemosensory receptors mediating the detection of pheromones and kairomones. Small hive beetles (SHBs), Aethina tumida, are parasites of social bee colonies and olfactory cues are especially important for host finding. However, how interactions with their hosts may have shaped the evolution of ORs in the SHB remains poorly understood. Here, for the first time, we analyzed the evolution of SHB ORs through phylogenetic and positive selection analyses. We then tested the expression of selected OR genes in antennae, heads, and abdomens in four groups of adult SHBs: colony odor-experienced/-naive males and females. The results show that SHBs experienced both OR gene losses and duplications, thereby providing a first understanding of the evolution of SHB ORs. Additionally, three candidate ORs potentially involved in host finding and/or chemical communication were identified. Significantly different downregulations of ORs between the abdomens of male and female SHBs exposed to colony odors may reflect that these expression patterns might also reflect other internal events, e.g., oviposition. Altogether, these results provide novel insights into the evolution of SHB ORs and provide a valuable resource for analyzing the function of key genes, e.g., for developing biological control. These results will also help in understanding the chemosensory system in SHBs and other beetles.

A dramatic response to a single dose of infliximab in a patient with prolonged pustular psoriasis derived from inverse psoriasis.

We report a case of a 25-year-old Chinese man with an exceptionally prolonged history of pustular psoriasis derived from inverse psoriasis who was unsatisfied with conventional treatment and was successfully treated with a single dose of infliximab without noticeable adverse effects. No recurrence or flaring was observed after 3 months of follow-up. This case illustrates that infliximab may be an effective and safe therapeutic option for patients with refractory pustular psoriasis derived from inverse psoriasis.

An Iterative Module in the Azalomycin†F Polyketide Synthase Contains a Switchable Enoylreductase Domain.

Detailed analysis of the modular Type I polyketide synthase (PKS) involved in the biosynthesis of the marginolactone azalomycin F in mangrove Streptomyces sp. 211726 has shown that only nineteen extension modules are required to accomplish twenty cycles of polyketide chain elongation. Analysis of the products of a PKS mutant specifically inactivated in the dehydratase domain of extension-module 1 showed that this module catalyzes two successive elongations with different outcomes. Strikingly, the enoylreductase domain of this module can apparently be "toggled" off and on : it functions in only the second of these two cycles. This novel mechanism expands our understanding of PKS assembly-line catalysis and may explain examples of apparent non-colinearity in other modular PKS systems.

Studies on transition metal-quercetin complexes using electrospray ionization tandem mass spectrometry.

To systematically study the effects of the number of d electrons of the first transition metal ions (Fe, Co, Ni, Cu and Zn) on the formation and stability of metal flavonoid complexes, we took the quercetin/M2+ complex as a model system to investigate the structures and properties of these complexes. Based on considerable structural information obtained through ESI-MSn, all of the first transition metal ions (Fe2+, Co2+, Ni2+, Cu2+ and Zn2+) were found to form different complexes with quercetin, while with the number of chelating flavonoids decreasing along with the reduction of the metal ionic radius. Quercetin forms different complexes with the above metal divalent ions through its 5-OH and 4-carbonyl groups; the complex stability is highly dependent on both the metallic ion and the flavonoid chelator itself. As for the central ion (M2+), when chelated with quercetin to form the complex, the stability of the complex decreased in the following order: Cu2+ > Ni2+ > Co2+ > Fe2+ > Zn2+. With flavonoid: metal stoichiometries at 2:1, the complexes formed between quercetin and metal ions (Fe2+, Ni2+, Co2+ and Zn2+) have the similar fragmentation mechanism, while Cu2+ displayed different fragmentation mechanism due to the concurrent oxidation.

Chemical proteomic strategies for the discovery and development of anticancer drugs.

Cancer is one of the leading causes of death globally. Drug discovery and development against cancer is thus among the most pursuing goals nowadays. Although the majority of anticancer drugs targeted on proteins, the identification and validation of drug targets and their regulated pathways remain a bottleneck in the drug R&D processes. Fortunately, chemical proteomic strategies based on the perfect combination of various targeted affinity chromatography and high-throughput MS analysis have emerged as a powerful tool for the large-scale identification of proteome-wide drug-protein interactions, and demonstrated great promise in elucidating complex underlying mechanisms of drug action against cancers. In this context, an updated overview of the chemical proteomic strategies, such as activity-based protein profiling (ABPP), compound-centric chemical proteomics (CCCP), and other targeted affinity chromatographic approaches for modern anticancer drug discovery and development will be provided. Some most recent successful applications in this area will be highlighted. Future perspectives on this subject will also be discussed with a particular emphasis on small molecule natural products and their derivatives.

Mental health status and influencing factors of retired teachers.

Introduction: The wellbeing of retired teachers is often easily overlooked. This study aims to explore the mental health status and influencing factors of retired teachers. Method: From October to December 2022, a convenient sampling survey was conducted on retired teachers using the Symptom Checklist 90 (SCL-90), mainly using the χ2-test and logistic regression analysis. Results: A sampling survey was conducted on 353 retired teachers, with an overall positive detection rate of 16.1%. The five factors with the highest positive detection rate were found to be obsessive-compulsive disorder (30.3%), interpersonal sensitivity (21.5%), paranoia (20.1%), anxiety (19.3%), and others (19.3%). The detection rates for the five factors, namely psychosis, depression, hostility, terror, and somatization, are all below 19%. The data on sex (χ2 = 4.626, P = 0.043), professional title (χ2 = 17.670, P = 0.003), income (χ2 = 9.960, P = 0.041), life satisfaction (χ2 = 27.348, P = 0.000), family relationships (χ2 = 51.451, P = 0.000), and physical health status (χ2 = 50.361, P = 0.000) show that the difference in mental health among retired teachers is statistically significant. The multivariate binary logistic regression analysis revealed that family relationships, life satisfaction, and physical health were important factors leading to mental health problems among retired teachers. Discussion: Retired teachers should cultivate a wide range of interests and hobbies, engage in regular physical exercise, develop healthy living habits, foster a positive family atmosphere, establish harmonious family relationships, promote community cultural construction, strengthen psychological intervention, and prevent psychological diseases.

Bi-Directional and Operand-Controllable In-Memory Computing for Boolean Logic and Search Operations with Row and Column Directional SRAM (RC-SRAM).

The von Neumann architecture is no longer sufficient for handling large-scale data. In-memory computing has emerged as the potent method for breaking through the memory bottleneck. A new 10T SRAM bitcell with row and column control lines called RC-SRAM is proposed in this article. The architecture based on RC-SRAM can achieve bi-directional and operand-controllable logic-in-memory and search operations through different signal configurations, which can comprehensively respond to various occasions and needs. Moreover, we propose threshold-controlled logic gates for sensing, which effectively reduces the circuit area and improves accuracy. We validate the RC-SRAM with a 28 nm CMOS technology, and the results show that the circuits are not only full featured and flexible for customization but also have a significant increase in the working frequency. At VDD = 0.9 V and T = 25 °C, the bi-directional search frequency is up to 775 MHz and 567 MHz, and the speeds for row and column Boolean logic reach 759 MHz and 683 MHz.

Sanghuangporus vaninii extract ameliorates hyperlipidemia in rats by mechanisms identified with transcriptome analysis.

The increasing incidence of hyperlipidemia is a serious threat to public health. The development of effective and safe lipid-lowering drugs with few side effects is necessary. The purpose of this study was to assess the lipid-lowering activity of Sanghuangporus vaninii extract (SVE) in rat experiments and reveal the molecular mechanism by transcriptome analysis. Hyperlipidemia was induced in the animals using a high-fat diet for 4 weeks. At the end of the 4th week, hyperlipidemic rats were assigned into two control groups (model and positive simvastatin control) and three treatment groups that received SVE at 200, 400, or 800 mg kg-1 day-1 for another 4 weeks. A last control group comprised normal chow-fed rats. At the end of the 8th week, rats were sacrificed and lipid serum levels, histopathology, and liver transcriptome profiles were determined. SVE was demonstrated to relieve the lipid disorder and improve histopathological liver changes in a dose-dependent manner. The transcriptomic analysis identified changes in hepatocyte gene activity for major pathways including steroid biosynthesis, bile secretion, cholesterol metabolism, AMPK signaling, thyroid hormone signaling, and glucagon signaling. The changed expression of crucial genes in the different groups was confirmed by qPCR. Collectively, this study revealed that SVE could relieve hyperlipidemia in rats, the molecular mechanism might be to promote the metabolism of lipids and the excretion of cholesterol, inhibit the biosynthesis of cholesterol by activating the AMPK signaling pathway, the thyroid hormone signaling pathway, and the glucagon signaling pathway.

Transcriptome analysis revealing the effect of Bupleurum scorzonerifolium Willd association with endophytic fungi CHS3 on the production of saikosaponin D.

Saikosaponin D (SSd) is a naturally active product with strong pharmacological activity found in Bupleurum scorzonerifolium Willd. Studies have shown that endophytic fungi have great potential as sources of natural medicines. Fusarium acuminatum (CHS3), an SSd-producing endophytic fungus, was isolated from B. scorzonerifolium. To elucidate the effect of host plants on the production of SSd in CHS3, CHS3 was co-cultured with suspension cells of B. scorzonerifolium and SSd was detected using high-performance liquid chromatography (HPLC). Transcriptome sequencing (RNA-Seq) of CHS3 before and after co-culture was performed using an Illumina HiSeq 2500 platform. The results indicated that the content of SSd synthesised by CHS3 increased after co-culture with suspension cells of B. scorzonerifolium. Transcriptome analysis of CHS3 with differentially expressed genes (DEGs) showed that 1202 and 1049 genes were upregulated and downregulated, respectively, after co-culture. Thirty genes associated with SSd synthesis and 11 genes related to terpene backbone biosynthesis were annotated to the Kyoto Encyclopaedia of Genes and Genomes (KEGG). Combined with transcriptome data, it was speculated that the mevalonate (MVA) pathway is a possible pathway for SSd synthesis in CHS3, and the expression of key enzyme genes (HMGR, HMGCS, GGPS1, MVK, FDFT1, FNTB) was validated by qRT-PCR. In conclusion, the endophytic fungus CHS3 can form an interactive relationship with its host, thereby promoting SSd biosynthesis and accumulation by upregulating the expression of key enzyme genes in the biosynthesis pathway.

Transcriptome analysis of the mechanism of endophytic fungus CHS3 promoting saikosaponin d synthesis in Bupleurum scorzonerifolium Willd. suspension cells.

Saikosaponin d (SSd) is the main component of Bupleuri Radix, a famous traditional Chinese herbal medicine, with high medicinal value. An endophytic fungus (CHS3) was isolated from Bupleurum scorzonerifolium Willd. in the early stage of our research, and we found that CHS3 could promote the accumulation of SSd in Bupleurum scorzonerifolium Willd. suspension cells (BSS cells). It is of practical significance to identify the mechanism that CHS3 promoted the accumulation of SSd and increased the production of SSd in suspension cells. To search the influence of CHS3 on SSd synthesis in the BSS cells, we co-cultured CHS3 with the BSS cells and compared the SSd content in BSS cells before and after co-culture using high-performance liquid chromatography (HPLC). Then the Illumina HiSeq 2500 was performed to detect the transcriptome of the BSS cells before and after co-culture and analyzed for the KEGG enrichment. The expression of genes involved in SSd synthesis was finally corroborated by qPCR analysis. Among which 11 key genes in connection with SSd synthesis were increased in BSS cells of co-cultured group compared with the BSS cells of the control group. In conclusion, CHS3 could promote the accumulation of SSd in BSS cells, and the molecular mechanism was related to its ability to regulate the MVA pathway, the calcium signaling pathway, and the AMPK signaling pathway by upregulating the expressions of ANT, CypD, CaM, AMPK, AATC, HMGS, HMGR, MVK, MVD, SS, and SE.

Pd@Pt Core-Shell Nanocrystal-Decorated ZnO Nanosheets for ppt-Level NO2 Detection.

Bimetallic nanocrystals (NCs) have obtained significant attention due to their unique advantages of the intrinsic properties of individual metals and synergistic enhancements resulting from the electronic coupling between two constituent metals. In this work, Pd@Pt core-shell NCs were prepared through a facile one-pot solution-phase method, which had excellent dispersion and uniform size. Concurrently, ZnO nanosheets were prepared via a hydrothermal method. To explore their potential in nitrogen dioxide (NO2) gas sensing applications, sensitive materials based on ZnO nanosheets with varying mass percentages of Pd@Pt NCs were generated through an impregnation process. The sensor based on 0.3 wt % Pd@Pt-ZnO exhibited remarkable performance, demonstrating a substantial response (Rg/Ra = 60.3) to 50 ppb of NO2 at a low operating temperature of 80 °C. Notably, this sensor reached an outstanding low detection limit of 300 ppt. The enhancement in gas sensing capabilities can be attributed to the sensitization and synergistic effects imparted by the exceptional catalytic activity of Pd@Pt NCs, which significantly promoted the reaction. This research introduces a novel approach for the utilization of core-shell structured bimetallic nanocrystals as modifiers in metal-oxide-semiconductor (MOS) materials for NO2 detection.

Deep learning-assisted distinguishing breast phyllodes tumours from fibroadenomas based on ultrasound images: a diagnostic study.

OBJECTIVES: To evaluate the performance of ultrasound-based deep learning (DL) models in distinguishing breast phyllodes tumours (PTs) from fibroadenomas (FAs) and their clinical utility in assisting radiologists with varying diagnostic experiences. METHODS: We retrospectively collected 1180 ultrasound images from 539 patients (247 PTs and 292 FAs). Five DL network models with different structures were trained and validated using nodule regions annotated by radiologists on breast ultrasound images. DL models were trained using the methods of transfer learning and 3-fold cross-validation. The model demonstrated the best evaluation index in the 3-fold cross-validation was selected for comparison with radiologists' diagnostic decisions. Two-round reader studies were conducted to investigate the value of DL model in assisting 6 radiologists with different levels of experience. RESULTS: Upon testing, Xception model demonstrated the best diagnostic performance (area under the receiver-operating characteristic curve: 0.87; 95% CI, 0.81-0.92), outperforming all radiologists (all P < .05). Additionally, the DL model enhanced the diagnostic performance of radiologists. Accuracy demonstrated improvements of 4%, 4%, and 3% for senior, intermediate, and junior radiologists, respectively. CONCLUSIONS: The DL models showed superior predictive abilities compared to experienced radiologists in distinguishing breast PTs from FAs. Utilizing the model led to improved efficiency and diagnostic performance for radiologists with different levels of experience (6-25 years of work). ADVANCES IN KNOWLEDGE: We developed and validated a DL model based on the largest available dataset to assist in diagnosing PTs. This model has the potential to allow radiologists to discriminate 2 types of breast tumours which are challenging to identify with precision and accuracy, and subsequently to make more informed decisions about surgical plans.