Fauna, ecological properties, and zoogeographical composition of Mirinae (Hemiptera: Miridae) of the Hulunbuir region, Inner Mongolia of China

The fauna, ecological properties, and zoogeographical composition of Mirinae of the Hulunbuir region of China were studied and summarized. Atotal of 65 species belonging to 2 tribes and 19 genera were recorded. Among them, Charagochilus gyllenhalii (Fallén, 1807), Lygus poluensis (Wagner, 1967) and Phytocoris zhengi Nonnaizab & Jorigtoo, 1992 are new records for the Hulunbuir region and the former species is the first record also for the entire Inner Mongolia. In the Hulunbuir region, the highest number of Mirinae species (31) was collected from the Ewenki Autonomous Banner during July within the elevations of 601–750 m. From the perspective of zoogeographical composition, the Mirinae species found in Hulunbuir belong to faunae attributed to the Palaearctic, Oriental, and Nearctic regions with the Palaearctic dominating

Compact Binary Systems Waveform Generation with Generative Pre-trained Transformer

Space-based gravitational wave detection is one of the most anticipated gravitational wave (GW) detection projects in the next decade, which will detect abundant compact binary systems. However, the precise prediction of space GW waveforms remains unexplored. To solve the data processing difficulty in the increasing waveform complexity caused by detectors' response and second-generation time-delay interferometry (TDI 2.0), an interpretable pre-trained large model named CBS-GPT (Compact Binary Systems Waveform Generation with Generative Pre-trained Transformer) is proposed. For compact binary system waveforms, three models were trained to predict the waveforms of massive black hole binary (MBHB), extreme mass-ratio inspirals (EMRIs), and galactic binary (GB), achieving prediction accuracies of 98%, 91%, and 99%, respectively. The CBS-GPT model exhibits notable interpretability, with its hidden parameters effectively capturing the intricate information of waveforms, even with complex instrument response and a wide parameter range. Our research demonstrates the potential of large pre-trained models in gravitational wave data processing, opening up new opportunities for future tasks such as gap completion, GW signal detection, and signal noise reduction

Dawning of a New Era in Gravitational Wave Data Analysis: Unveiling Cosmic Mysteries via Artificial Intelligence -- A Systematic Review

Background: Artificial intelligence (AI), with its vast capabilities, has become an integral part of our daily interactions, particularly with the rise of sophisticated models like Large Language Models. These advancements have not only transformed human-machine interactions but have also paved the way for significant breakthroughs in various scientific domains. Aim of review: This review is centered on elucidating the profound impact of AI, especially deep learning, in the field of gravitational wave data analysis (GWDA). We aim to highlight the challenges faced by traditional GWDA methodologies and how AI emerges as a beacon of hope, promising enhanced accuracy, real-time processing, and adaptability. Key scientific concepts of review: Gravitational wave (GW) waveform modeling stands as a cornerstone in the realm of GW research, serving as a sophisticated method to simulate and interpret the intricate patterns and signatures of these cosmic phenomena. This modeling provides a deep understanding of the astrophysical events that produce gravitational waves. Next in line is GW signal detection, a refined technique that meticulously combs through extensive datasets, distinguishing genuine gravitational wave signals from the cacophony of background noise. This detection process is pivotal in ensuring the authenticity of observed events. Complementing this is the GW parameter estimation, a method intricately designed to decode the detected signals, extracting crucial parameters that offer insights into the properties and origins of the waves. Lastly, the integration of AI for GW science has emerged as a transformative force. AI methodologies harness vast computational power and advanced algorithms to enhance the efficiency, accuracy, and adaptability of data analysis in GW research, heralding a new era of innovation and discovery in the field

DECODE: DilatEd COnvolutional neural network for Detecting Extreme-mass-ratio inspirals

The detection of Extreme Mass Ratio Inspirals (EMRIs) is intricate due to their complex waveforms, extended duration, and low signal-to-noise ratio (SNR), making them more challenging to be identified compared to compact binary coalescences. While matched filtering-based techniques are known for their computational demands, existing deep learning-based methods primarily handle time-domain data and are often constrained by data duration and SNR. In addition, most existing work ignores time-delay interferometry (TDI) and applies the long-wavelength approximation in detector response calculations, thus limiting their ability to handle laser frequency noise. In this study, we introduce DECODE, an end-to-end model focusing on EMRI signal detection by sequence modeling in the frequency domain. Centered around a dilated causal convolutional neural network, trained on synthetic data considering TDI-1.5 detector response, DECODE can efficiently process a year's worth of multichannel TDI data with an SNR of around 50. We evaluate our model on 1-year data with accumulated SNR ranging from 50 to 120 and achieve a true positive rate of 96.3% at a false positive rate of 1%, keeping an inference time of less than 0.01 seconds. With the visualization of three showcased EMRI signals for interpretability and generalization, DECODE exhibits strong potential for future space-based gravitational wave data analyses.Comment: 13 pages, 5 figures, and 2 table

Targeting LIF-mediated paracrine interaction for pancreatic cancer therapy and monitoring.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis largely owing to inefficient diagnosis and tenacious drug resistance. Activation of pancreatic stellate cells (PSCs) and consequent development of dense stroma are prominent features accounting for this aggressive biology1,2. The reciprocal interplay between PSCs and pancreatic cancer cells (PCCs) not only enhances tumour progression and metastasis but also sustains their own activation, facilitating a vicious cycle to exacerbate tumorigenesis and drug resistance3-7. Furthermore, PSC activation occurs very early during PDAC tumorigenesis8-10, and activated PSCs comprise a substantial fraction of the tumour mass, providing a rich source of readily detectable factors. Therefore, we hypothesized that the communication between PSCs and PCCs could be an exploitable target to develop effective strategies for PDAC therapy and diagnosis. Here, starting with a systematic proteomic investigation of secreted disease mediators and underlying molecular mechanisms, we reveal that leukaemia inhibitory factor (LIF) is a key paracrine factor from activated PSCs acting on cancer cells. Both pharmacologic LIF blockade and genetic Lifr deletion markedly slow tumour progression and augment the efficacy of chemotherapy to prolong survival of PDAC mouse models, mainly by modulating cancer cell differentiation and epithelial-mesenchymal transition status. Moreover, in both mouse models and human PDAC, aberrant production of LIF in the pancreas is restricted to pathological conditions and correlates with PDAC pathogenesis, and changes in the levels of circulating LIF correlate well with tumour response to therapy. Collectively, these findings reveal a function of LIF in PDAC tumorigenesis, and suggest its translational potential as an attractive therapeutic target and circulating marker. Our studies underscore how a better understanding of cell-cell communication within the tumour microenvironment can suggest novel strategies for cancer therapy

The gut microbiome in atherosclerotic cardiovascular disease

The gut microbiota may play a role in cardiovascular diseases. Here, the authors perform a metagenome-wide association study on stools from individuals with atherosclerotic cardiovascular disease and healthy controls, identifying microbial strains and functions associated with the disease

Single nucleotide polymorphisms at the TRAF1/C5 locus are associated with rheumatoid arthritis in a Han Chinese population

<p>Abstract</p> <p>Background</p> <p>Genetic variants in <it>TRAF1C5 </it>and <it>PTPN22 </it>genes have been shown to be significantly associated with arthritis rheumatoid in Caucasian populations. This study investigated the association between single nucleotide polymorphisms (SNPs) in <it>TRAF1/C5 </it>and <it>PTPN22 </it>genes and rheumatoid arthritis (RA) in a Han Chinese population. We genotyped SNPs rs3761847 and rs7021206 at the <it>TRAF1/C5 </it>locus and rs2476601 SNP in the <it>PTPN22 </it>gene in a Han Chinese cohort composed of 576 patients with RA and 689 controls. The concentrations of anti-cyclic citrullinated peptide antibodies (CCP) and rheumatoid factor (RF) were determined for all affected patients. The difference between the cases and the controls was compared using <it>χ</it>²analysis.</p> <p>Results</p> <p>Significant differences in SNPs rs3761847 and rs7021206 at <it>TRAF1/C5 </it>were observed between the case and control groups in this cohort; the allelic p-value was 0.0018 with an odds ratio of 1.28 for rs3761847 and 0.005 with an odds ratio of 1.27 for rs7021206. This significant association between rs3761847 and RA was independent of the concentrations of anti-CCP and RF. No polymorphism of rs2476601 was observed in this cohort.</p> <p>Conclusions</p> <p>We first demonstrated that genetic variants at the <it>TRAF1/C5 </it>locus are significantly associated with RA in Han Chinese, suggesting that <it>TRAF1/C5 </it>may play a role in the development of RA in this population, which expands the pathogenesis role of <it>TRAF1/C5 </it>in a different ethnicity.</p

Staged induction of HIV-1 glycan–dependent broadly neutralizing antibodies

A preventive HIV-1 vaccine should induce HIV-1–specific broadly neutralizing antibodies (bnAbs). However, bnAbs generally require high levels of somatic hypermutation (SHM) to acquire breadth, and current vaccine strategies have not been successful in inducing bnAbs. Because bnAbs directed against a glycosylated site adjacent to the third variable loop (V3) of the HIV-1 envelope protein require limited SHM, the V3-glycan epitope is an attractive vaccine target. By studying the cooperation among multiple V3-glycan B cell lineages and their coevolution with autologous virus throughout 5 years of infection, we identify key events in the ontogeny of a V3-glycan bnAb. Two autologous neutralizing antibody lineages selected for virus escape mutations and consequently allowed initiation and affinity maturation of a V3-glycan bnAb lineage. The nucleotide substitution required to initiate the bnAb lineage occurred at a low-probability site for activation-induced cytidine deaminase activity. Cooperation of B cell lineages and an improbable mutation critical for bnAb activity defined the necessary events leading to breadth in this V3-glycan bnAb lineage. These findings may, in part, explain why initiation of V3-glycan bnAbs is rare, and suggest an immunization strategy for inducing similar V3-glycan bnAbs

Anti-phospholipid human monoclonal antibodies inhibit CCR5-tropic HIV-1 and induce β-chemokines

Traditional antibody-mediated neutralization of HIV-1 infection is thought to result from the binding of antibodies to virions, thus preventing virus entry. However, antibodies that broadly neutralize HIV-1 are rare and are not induced by current vaccines. We report that four human anti-phospholipid monoclonal antibodies (mAbs) (PGN632, P1, IS4, and CL1) inhibit HIV-1 CCR5-tropic (R5) primary isolate infection of peripheral blood mononuclear cells (PBMCs) with 80% inhibitory concentrations of <0.02 to ∼10 µg/ml. Anti-phospholipid mAbs inhibited PBMC HIV-1 infection in vitro by mechanisms involving binding to monocytes and triggering the release of MIP-1α and MIP-1β. The release of these β-chemokines explains both the specificity for R5 HIV-1 and the activity of these mAbs in PBMC cultures containing both primary lymphocytes and monocytes

Induction of Antibodies in Rhesus Macaques That Recognize a Fusion-Intermediate Conformation of HIV-1 gp41

A component to the problem of inducing broad neutralizing HIV-1 gp41 membrane proximal external region (MPER) antibodies is the need to focus the antibody response to the transiently exposed MPER pre-hairpin intermediate neutralization epitope. Here we describe a HIV-1 envelope (Env) gp140 oligomer prime followed by MPER peptide-liposomes boost strategy for eliciting serum antibody responses in rhesus macaques that bind to a gp41 fusion intermediate protein. This Env-liposome immunization strategy induced antibodies to the 2F5 neutralizing epitope 664DKW residues, and these antibodies preferentially bound to a gp41 fusion intermediate construct as well as to MPER scaffolds stabilized in the 2F5-bound conformation. However, no serum lipid binding activity was observed nor was serum neutralizing activity for HIV-1 pseudoviruses present. Nonetheless, the Env-liposome prime-boost immunization strategy induced antibodies that recognized a gp41 fusion intermediate protein and was successful in focusing the antibody response to the desired epitope