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Text summarization on non-factoid question answering (NQA) aims at identifying the core information of redundant answer guidance using questions, which can dramatically improve answer readability and comprehensibility. Most existing approaches focus on extracting query-related sentences to construct a summary, where the logical connection of natural language and the hierarchical interpretable semantic association are often neglected, thus degrading performance. To address these issues, we propose a novel question-driven abstractive answer summarization model, called the H ierarchical S liding I nference G enerator (HSIG), to form inferable and interpretable summaries by explicitly introducing hierarchical information reasoning between questions and corresponding answers. Specifically, we first apply an elaborately designed hierarchical sliding fusion inference model to determine the most relevant question sentence-level representation that provides a deeper interpretable basis for sentence selection in summarization, which further increases computational performance on the premise of following the semantic inheritance structure. Additionally, to improve summary fluency, we construct a double-driven selective generator to integrate various semantic information from two mutual question-and-answer perspectives. Experimental results illustrate that compared with state-of-the-art baselines, our model achieves remarkable improvement on two benchmark datasets and specifically improves the 2.46 ROUGE-1 points on PubMedQA, which demonstrates the superiority of our model on abstractive summarization with hierarchical sequential reasoning.

(1) Background: This study aimed to conduct a NMA and CEA combined study to compare the effectiveness and cost-effectiveness of different CDK4/6 inhibitors (Abem, Palbo, and Ribo) plus NSAI with placebo plus NSAI in the first-line treatment of postmenopausal women with HR+/HER2− ABC from the perspective of payers in China. (2) Methods: Studies which evaluated CDK4/6 inhibitors plus NSAI for HR+/HER2− ABC were searched. A Bayesian NMA was carried out and the main outcomes were the hazard ratios (HRs) of overall survival (OS) and progression-free survival (PFS). The costs and efficacy of first-line therapies for HR+/HER2− ABC were evaluated using the Markov model. The main outcomes in the CEA were incremental cost–utility ratios (ICURs), incremental monetary benefit (INMB), and incremental net-health benefit (INHB). The robustness of the model was assessed by one-way, three-way, and probabilistic sensitivity analyses. Then, we further simulated the impact of different prices of CDK4/6 inhibitors on the results. (3) Results: Seven studies involving 5347 patients were included in the NMA. The three first-line CDK4/6 inhibitors plus NSAI groups provided significant PFS and OS superiority to NSAI alone. Abem + NSAI represented a significant statistical advantage onPFS (HR 0.74, 95% CI 0.61–0.90, p = 0.009) and indicated a trend of being the best OS benefit compared to the placebo + NSAI group (HR 0.89, 95% CI 0.72–1.08). The Abem + NSAI, Palbo + NSAI, and Ribo + NSAI groups resulted in additional costs of $12,602, $20,391, and $81,258, with additional effects of 0.38, 0.31, and 0.30 QALYs, respectively, leading to an ICUR of $33,163/QALY, $65,777/QALY, and $270,860/QALY. Additional pairwise comparisons showed that Abem + NSAI was the only cost-effective option in three CDK4/6 inhibitors plus NSAI groups at a willingness-to-pay (WTP) of $38,029/QALY. The sensitivity analyses showed that the proportion of receiving subsequent CDK4/6 inhibitors and the cost of Abem significantly influenced the results of Abem + NSAI compared with placebo + NSAI. (4) Conclusion: From the perspective of Chinese payers, Abem + NSAI was a cost-effective treatment option compared with placebo + NSAI at the WTP of $38,029/QALY, since only the ICUR of $33,163/QALY of Abem + NSAI was lower than the WTP of $38,029/QALY in China (2022). The Palbo + NSAI and Ribo + NSAI groups were not cost-effective unless drug prices were adjusted to 50% or 10% of current prices ($320.67 per cycle or $264.60 per cycle). (5) Others: We have prospectively registered the study with the PROSPERO, and the PROSPERO registration number is CRD42023399342.

A shortwave infrared Ge–Si photodetector will become the core device of the LiDAR optical receiver. In order to meet the urgent demand for photodetectors in the LiDAR field, we designed and produced a 32 × 32-pixel Ge–Si photodetector array, which was proposed and developed to meet the performance requirements of the detector array. A dark current detection system for fast scanning and detecting large-scale Ge–Si detector arrays was proposed and developed to achieve the rapid detection of dark current in each detector pixel, with a detection accuracy of less than 1 nA. The system validated the primary performance indicators of the detector array we designed, achieving rapid discrimination of the array performance and rapid localization of damaged pixels. The scanning test results showed that the average dark current of the designed detector array chip was on the nanoampere level, and the proportion of bad points was less than 1%. The consistency of the array chip was high, which meets the requirements of light detection at the receiving end of LiDAR. This work laid the foundation for our subsequent development of a LiDAR prototype system.

The shortwave infrared Ge-Si photodetector will become the core device of the LiDAR optical receiver. In order to meet the urgent demand for photodetectors in the LiDAR field, we have designed and produced a 32×32 pixel Ge-Si photodetector array proposed and developed to meet the performance requirements of the detector array. A dark current detection system for fast scanning and detecting large-scale Ge-Si detector arrays is proposed and developed to achieve rapid detection of dark current in each pixel of the detector. The system was used to validate the main performance indicators of the detector array we designed, achieving rapid discrimination of array performance and rapid localization of damaged pixels. The scanning test results show that the average dark current of the detector array chip we designed is at the nano ampere level, and the proportion of bad points is less than 1%. The consistency of the array chip is high, which can meet the requirements of light detection at the receiving end of the LiDAR. This work laid the foundation for our subsequent development of a LiDAR prototype system.

Context Maternal thyroid hormone trajectories are a better predictor of offspring’s neurodevelopment than hormone levels in single trimester of pregnancy. Programming effect of uterine hormonal environment on offspring’s health is usually sex-specific. Objective To examine the sex-specific effect of thyroid hormone trajectories on preschoolers’ behavioral development. Design Based on Ma’ anshan Birth Cohort in China, pregnant women were recruited at their first antenatal checkup from May 2013 to September 2014. Setting Ma’ anshan Maternal and Child Health Hospital in China. Patients or Other Participants 1860 mother-child pairs were included in the analysis. Children were followed up at age of 4. Main Outcome Measures Maternal thyroid hormones [thyroid-stimulating hormone (TSH), free thyroxine (FT4)] and thyroid peroxidase antibody in the first, second, and third trimesters of pregnancy were retrospectively assayed. Preschoolers’ behavioral development was assessed by Achenbach Child Behavior Checklist/1.5~5. Results Maternal TSH and FT4 levels were respectively fitted into high, moderate, and low trajectories. In boys, maternal high TSH trajectory was related to withdrawn [odds ratio (OR) = 2.01, 95% CI: 1.16, 3.50) and externalizing problems (OR = 2.69, 95% CI: 1.22, 5.92), and moderate TSH trajectory was associated with aggressive behavior (OR = 3.76, 95% CI: 1.16, 12.23). Maternal high FT4 trajectory was associated with anxious/depressed (OR = 2.22, 95% CI: 1.08, 4.56) and total problems (OR = 1.74, 95% CI: 1.13, 2.66), and low FT4 trajectory was associated with aggressive behavior (OR = 4.17, 95% CI: 1.22, 14.24). Conclusions Maternal thyroid hormone trajectories impact preschool boys’ behavioral development.

Purpose Recent research has found that patients who receive aspirin might have a reduced risk of breast cancer. However, how aspirin influences cancer remains controversial. Ferroptosis is an iron- and reactive oxygen species (ROS)-dependent form of regulated cell death (RCD), and it is crucial for the suppression of tumors. Herein, we investigated the mechanism of aspirin as a novel ferroptosis inducer in the antitumor effect of triple-negative breast cancer (TNBC). Methods We performed cell proliferation, ferroptosis-related and xenograft assays to determine the function and mechanism of aspirin in TNBC. Additionally, we investigated the transcriptomic profiles in TNBC tissues and normal tissues by RNA-seq. Results Our present study revealed that aspirin not only significantly accelerated ferroptosis but also inhibited the growth of TNBC cells. Intriguingly, aspirin, similar to the ferroptosis activator erastin, promoted ferroptosis and inhibited cell proliferation; however, the additional ferroptosis suppressor ferrostatin reversed the function of aspirin in ferroptosis and cell proliferation. Mechanistically, these results indicated that aspirin attenuated the level of Nrf2 protein and enhanced Keap1, mainly through the Keap1-Nrf2 pathway, in TNBC cells. Meanwhile, aspirin could also suppress key ferroptosis factors, such as GPX4 and xCT. Importantly, restoring Nrf2 signaling reversed aspirin-mediated ferroptosis. Furthermore, we found that oxidative stress and the Keap1-Nrf2 pathway were significantly changed. Conclusion Overall, our research demonstrates a novel role of aspirin in inhibiting Keap1-Nrf2 signaling to accelerate ferroptosis, which leads to the inhibition of cell proliferation in TNBC. Aspirin may present as a potential preventive strategy against the development of TNBC.

The backpropagation neural network (BPNN) algorithm of artificial intelligence (AI) is utilized to predict A+H shares price for helping investors reduce the risk of stock investment. First, the genetic algorithm (GA) is used to optimize BPNN, and a model that can predict multi-day stock prices is established. Then, the Principal Component Analysis (PCA) algorithm is introduced to improve the GA-BP model, aiming to provide a practical approach for analyzing the market risks of the A+H shares. The experimental results show that for A shares, the model has the best prediction effect on the price of Bank of China (BC), and the average prediction errors of opening price, maximum price, minimum price, as well as closing price are 0.0236, 0.0262, 0.0294 and 0.0339, respectively. For H shares, the model constructed has the best effect on the price prediction of China Merchants Bank (CMB). The average prediction errors of opening price, maximum price, minimum price and closing price are 0.0276, 0.0422, 0.0194 and 0.0619, respectively.

Background A growing body of evidence shows that E2F transcription factors play a significant role in the tumorigenesis of prostate cancer. However, their functional and prognostic value has not been fully illustrated. Therefore, we used bioinformatics methods to further analyze the possible roles of E2F transcription factors in the development and progression of prostate cancer. Methods We explored the expression levels of E2F transcription factors using data from The Cancer Genome Atlas (TCGA) and Oncomine database in paired and unpaired samples. The clinical correlation and prognostic value of E2F transcription factors were assessed. Using the R package “pROC”, we judged the diagnostic value of E2F transcription factors. The online website tool cBioPortal was also employed to find possible gene alterations of E2F transcription factors in samples from TCGA. The R package “clusterprofiler” was used to conduct functional analysis. Moreover, we also used the Tumor Immune Estimation Resource to search for the associations between E2F transcription factors and the infiltration levels of 6 kinds of immune cells. Finally, quantitative real-time polymerase chain reaction (PCR) was conducted to validate the expression levels of E2F transcription factors in human paired prostate tissues. Results E2F1/2/3/5 messenger RNA (mRNA) expression levels were higher in prostate cancer tissues than in normal tissues, while E2F4 and E2F6 mRNA expression levels were lower (P

Energy efficiency (EE) is a significant performance indicator in unmanned aerial vehicle (UAV)-assisted communication networks for providing a balance between power consumption minimization and transmission rate maximization. However, most of the current works focus on the transmission rate maximization under perfect channel state information (CSI) and exact coordinate information, which is too ideal in practical systems due to channel estimation errors and coordinate estimation errors. Thus, robust resource allocation algorithms with imperfect CSI and coordinate information are critically important to reduce users’ outages and improve system robustness. In this article, a robust EE maximization problem with channel uncertainties and coordinate uncertainties is formulated for an energy harvesting-based device-to-device (D2D) communication underlaying UAV-assisted network under some necessary constraints, which involve the outage probability constraints of ground terminals, the flight altitude constraint of the UAV, the minimum harvested energy constraints of D2D users, and the transmission time constraint. Both radio resource allocation and the flight altitude are jointly optimized based on the worst case approach. The considered nonconvex problem is transformed into a convex one by exploiting variable relaxation and variable substitution approaches. The Lagrange dual theory is used to derive the closed-form expressions of robust resource allocation. Simulation results demonstrate the effectiveness of the proposed algorithm by comparing it with the benchmark algorithms in terms of EE and robustness.

Secondary bacterial infection greatly increased the morbidity and mortality of influenza virus infection. To investigate the underlying mechanism by which influenza impairs the pulmonary defense against secondary Pseudomonas aeruginosa ( P. aeruginosa ) infection, we established a lethal mouse model in which to study secondary P. aeruginosa infection after influenza virus infection. We found a significant increase in host susceptibility to a secondary infection with P. aeruginosa in mice after an influenza virus infection, and this was accompanied by severe immunopathology and pulmonary inflammation. Importantly, we demonstrated that neutrophils were essential for P. aeruginosa clearance in secondarily infected mice. Further, we revealed that influenza impaired the phagocytosis and digestion functions of pulmonary neutrophils for P. aeruginosa clearance. We identified that the activity of reactive oxygen species (ROS) and the myeloperoxidase (MPO) activity of neutrophils in the lungs played an important role in antibacterial host defense in influenza-infected lungs. Hereby, influenza virus infection causes deficient MPO activity in neutrophils, and this contributes to the increased susceptibility to secondary P. aeruginosa infection. Treatment with Bacillus Calmette-Guerin polysaccharide nucleic acid (BCG-PSN) prior to secondary P. aeruginosa infection may improve the function of neutrophils, resulting in significantly reduced lethality during secondary P. aeruginosa infection. We also demonstrated that treatment with anti-influenza immune serum during the early stage of an influenza virus infection could decrease the disease severity of secondary P. aeruginosa infection. Our findings suggest that improving the MPO activity of neutrophils may provide a therapeutic strategy for viral-bacterial coinfection. IMPORTANCE A secondary bacterial infection, such as that of P. aeruginosa , often occurs after a pulmonary virus infection and contributes to severe disease. However, the underlying mechanisms responsible for viral-bacterial synergy in the lung remain largely unknown. In this study, we reported that influenza virus infection increases a host’s susceptibility to secondary infection by P. aeruginosa by reducing the MPO activity of neutrophils. We also demonstrated that treatment with BCG-PSN or anti-influenza immune serum prior to secondary P. aeruginosa infection can reduce the disease severity. Our findings suggest that improving the MPO activity of neutrophils may provide a therapeutic strategy for viral-bacterial coinfection.

In a variety of waste heat utilization technologies, absorption refrigeration can be driven by low-grade heat to provide cooling capacity, which is suitable for situations with both waste heat supply and refrigeration demand. In this paper, an ammonia-water absorption refrigeration prototype with a new generator structure is experimentally studied. Its economic analysis is carried out for pre-cooling in a liquefied natural gas plant. It is investigated that 1.8 kW cooling capacity at −10 °C is obtained, COP maintains between 0.29 and 0.35, and waste heat recovery ratio is improved by 150%. The proposed system is applied to a 30,000 Nm3 d−1 liquefied natural gas plant to replace the conventional compression refrigerator as the pre-cooling stage, and waste heat from exhaust gas and jacket coolant is recovered in the reboiler and stripping section, respectively, in order to provide cooling capacity for pre-cooling of both natural gas and refrigerant. Economic analysis shows that specific power consumption of the modified system is reduced by 30%, from 0.40 to 0.28 kWh Nm−3. Consequently, the annual natural gas consumption and operating costs are reduced by 17.3% and 9.4%, respectively, and the payback period is 2.2 years compared to conventional systems with compressor-based pre-cooling stages.

Flexible microelectronics capable of straightforward implantation, remotely controlled navigation, and stable long-term recording hold great promise in diverse medical applications, particularly in deciphering complex functions of neural circuits in the brain. Existing flexible electronics, however, are often limited in bending and buckling during implantation, and unable to access a large brain region. Here, an injectable class of electronics with stable recording, omnidirectional steering, and precise navigating capabilities based on magnetic actuation is presented. After simple transcriptional injection, the rigid coatings are biodegraded quickly and the bundles of magnetic-nanoparticles-coated microelectrodes become separated, ultra-flexible, and magnetic actuated for further minimally invasive three-dimensional interpenetration in the brain. As proof of concept, this paradigm-shifting approach is demonstrated for selective and multiplexed neural activities recording across distant regions in the deep rodent brains. Coupling with optogenetic neural stimulation, the unique capabilities of this platform in electrophysiological readouts of projection dynamics in vivo are also demonstrated. The ability of these miniaturized, remotely controllable, and biocompatible ferromagnetic flexible electronics to afford minimally invasive manipulations in the soft tissues of the mammalian brain foreshadows applications in other organ systems, with great potential for broad utility in biomedical science and engineering.

Prolonged infection and possible evolution of SARS-CoV-2 in patients living with uncontrolled HIV-1 infection highlight the importance of an effective vaccination regimen, yet the immunogenicity of COVID-19 vaccines and predictive immune biomarkers have not been well investigated. Herein, we report that the magnitude and persistence of antibody and cell-mediated immunity (CMI) elicited by an Ad5-vectored COVID-19 vaccine are impaired in SIV-infected macaques with high viral loads (10

Background This study aimed to determine the effect of height and weight on heel fat pad thickness between microchamber and macrochamber layers during loading-unloading cycles. Methods The subjects performed loading-unloading movements, and the thickness change of the heel fat pad was measured. We examined the relationship between height and weight and the rate of change in the thickness of the microchamber and macrochamber layers of the heel fat pad when 0–100% load was applied. Results Significant changes were observed in the macrochamber layer. The thicknesses of the microchamber and macrochamber layers of the heel fat pad increased with increasing height and weight. Conclusions Function may differ between the microchamber and macrochamber layers of the heel fat pad. With increasing height and weight, the thickness of the microchamber and macrochamber layers increased, but the thickness change of the macrochamber layers decreased.

The serine/arginine-rich splicing factors (SRSF)-mediated alternative splicing plays an essential role in the occurrence and progression of hepatocellular carcinoma (HCC). However, the SRSF-based signature that can predict the prognosis and therapy efficiency is yet to be investigated in HCC. Here, we comprehensively assessed the landscape and prognostic significance of the SRSF family genes in HCC. Then, we screened the SRSF family-related genes for signature construction and explored their biological characteristics. We further established an SRSF score consisting of 18 SRSF-associated genes and evaluated its correlation with prognosis and drug sensitivity in HCC. The predictive power of the SRSF score was validated in independent HCC cohorts and different HCC subgroups. Moreover, we further investigated that knockdown of SRSF11, a pivotal gene in the SRSF score, inhibited CDK1-dependent proliferation and enhanced the drug sensitivity of HCC cells. Overall, our study identified a novel SRSF family-based predictive model, and we demonstrated that SRSF11 is a promising therapeutic target for HCC, which enhances our understanding of the SRSF family genes and provides valuable insights into the clinical treatment and molecular mechanisms of HCC.