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Image denoising is regarded as an ill-posed problem in computer vision tasks that removes additive noise from imaging sensors. Recently, several convolution neural network-based image-denoising methods have achieved remarkable advances. However, it is difficult for a simple denoising network to recover aesthetically pleasing images owing to the complexity of image content. Therefore, this study proposes a multi-branch network to improve the performance of the denoising method. First, the proposed network is designed based on a conventional autoencoder to learn multi-level contextual features from input images. Subsequently, we integrate two modules into the network, including the Pyramid Context Module (PCM) and the Residual Bottleneck Attention Module (RBAM), to extract salient information for the training process. More specifically, PCM is applied at the beginning of the network to enlarge the receptive field and successfully address the loss of global information using dilated convolution. Meanwhile, RBAM is inserted into the middle of the encoder and decoder to eliminate degraded features and reduce undesired artifacts. Finally, extensive experimental results prove the superiority of the proposed method over state-of-the-art deep-learning methods in terms of objective and subjective performances.

The length of the G1 phase in the cell cycle shows significant variability in different cell types and tissue types. To gain insights into the control of G1 length, we generated an E2F activity reporter that captures free E2F activity after dissociation from Rb sequestration and followed its kinetics of activation at the single-cell level, in real time. Our results demonstrate that its activity is precisely coordinated with S phase progression. Quantitative analysis indicates that there is a pre-S phase delay between E2F transcriptional dynamic and activity dynamics. This delay is variable among different cell types and is strongly modulated by the cyclin D/CDK4/6 complex activity through Rb phosphorylation. Our findings suggest that the main function of this complex is to regulate the appropriate timing of G1 length.

This study quantifies the projected impacts of climate change on crop yields across temperature rise regimes and climatic zones, using the latest global dataset of site-level process-model simulations of crop responses to climate scenarios. We employed a threshold regression technique to identify and estimate temperature change thresholds and used linear mixed-effects models to assess the climate impacts on crop yields across different levels of temperature rise. The results indicated that warmer temperatures are detrimental to crop yields across countries, with negative impacts exacerbated when temperature increase exceeds threshold values. For instance, for wheat, a 1 °C temperature increase would result in a 6.1% yield loss when the temperature rise is below 2.38 °C; however, when it exceeds 2.38 °C, yield loss would rise to 8.2% per 1 °C warming. Similarly, the loss in rice yields for each °C increase in temperature would increase from 1.1 to 7.1% per °C when the temperature rise surpasses the 3.13 °C threshold. For maize, no threshold effect is found; instead, temperature increase would reduce yields by an average of 4.03% per °C. We also conducted impact assessments by climate zone, categorizing studied sites according to the Köppen climate classification system. We found that crop yields in arid regions are most adversely affected by global warming compared to other zones, while adaptive potential is higher for rice and wheat in temperate zones and for maize in continental zones. This study highlights the existence of threshold effects of temperature rise on crop yields and the varying yield impacts among climate zones, informing effective adaptation strategies to enhance global food security.

Diabetes mellitus remains a major global health issue, and great attention is directed at natural therapeutics. This systematic review aimed to assess the potential of flavonoids as antidiabetic agents by investigating their inhibitory effects on α-glucosidase and α-amylase, two key enzymes involved in starch digestion. Six scientific databases (PubMed, Virtual Health Library, EMBASE, SCOPUS, Web of Science, and WHO Global Index Medicus) were searched until August 21, 2022, for in vitro studies reporting IC 50 values of purified flavonoids on α-amylase and α-glucosidase, along with corresponding data for acarbose as a positive control. A total of 339 eligible articles were analyzed, resulting in the retrieval of 1643 flavonoid structures. These structures were rigorously standardized and curated, yielding 974 unique compounds, among which 177 flavonoids exhibited inhibition of both α-glucosidase and α-amylase are presented. Quality assessment utilizing a modified CONSORT checklist and structure–activity relationship (SAR) analysis were performed, revealing crucial features for the simultaneous inhibition of flavonoids against both enzymes. Moreover, the review also addressed several limitations in the current research landscape and proposed potential solutions. The curated datasets are available online at https://github.com/MedChemUMP/FDIGA . Graphical Abstract

Xpert MTB/RIF Ultra (Xpert Ultra) might have higher sensitivity than its predecessor, Xpert MTB/RIF (Xpert), but its role in tuberculous meningitis diagnosis is uncertain. We aimed to compare Xpert Ultra with Xpert for the diagnosis of tuberculous meningitis in HIV-uninfected and HIV-infected adults. In this prospective, randomised, diagnostic accuracy study, adults (≥16 years) with suspected tuberculous meningitis from a single centre in Vietnam were randomly assigned to cerebrospinal fluid testing by either Xpert Ultra or Xpert at baseline and, if treated for tuberculous meningitis, after 3–4 weeks of treatment. Test performance (sensitivity, specificity, and positive and negative predictive values) was calculated for Xpert Ultra and Xpert and compared against clinical and mycobacterial culture reference standards. Analyses were done for all patients and by HIV status. Between Oct 16, 2017, and Feb 10, 2019, 205 patients were randomly assigned to Xpert Ultra (n=103) or Xpert (n=102). The sensitivities of Xpert Ultra and Xpert for tuberculous meningitis diagnosis against a reference standard of definite, probable, and possible tuberculous meningitis were 47·2% (95% CI 34·4–60·3; 25 of 53 patients) for Xpert Ultra and 39·6% (27·6–53·1; 21 of 53) for Xpert (p=0·56); specificities were 100·0% (95% CI 92·0–100·0; 44 of 44) and 100·0% (92·6–100·0; 48 of 48), respectively. In HIV-negative patients, the sensitivity of Xpert Ultra was 38·9% (24·8–55·1; 14 of 36) versus 22·9% (12·1–39·0; eight of 35) by Xpert (p=0·23). In HIV co-infected patients, the sensitivities were 64·3% (38·8–83·7; nine of 14) for Xpert Ultra and 76·9% (49·7–91·8; ten of 13) for Xpert (p=0·77). Negative predictive values were 61·1% (49·6–71·5) for Xpert Ultra and 60·0% (49·0–70·0) for Xpert. Against a reference standard of mycobacterial culture, sensitivities were 90·9% (72·2–97·5; 20 of 22 patients) for Xpert Ultra and 81·8% (61·5–92·7; 18 of 22) for Xpert (p=0·66); specificities were 93·9% (85·4–97·6; 62 of 66) and 96·9% (89·5–91·2; 63 of 65), respectively. Six (22%) of 27 patients had a positive test by Xpert Ultra after 4 weeks of treatment versus two (9%) of 22 patients by Xpert. Xpert Ultra was not statistically superior to Xpert for the diagnosis of tuberculous meningitis in HIV-uninfected and HIV-infected adults. A negative Xpert Ultra or Xpert test does not rule out tuberculous meningitis. New diagnostic strategies are urgently required. Wellcome Trust and the Foundation for Innovative New Diagnostics.

The World Health Organization declared monkeypox a global public health emergency on 23 July 2022. This disease was caused by the monkeypox virus (MPXV), which was first identified in 1958 in Denmark. The MPXV is a member of the Poxviridae family, the Chordopoxvirinae subfamily, and the genus Orthopoxvirus, which share high similarities with the vaccinia virus (the virus used to produce the smallpox vaccine). For the initial stage of infection, the MPXV needs to attach to the human cell surface glycosaminoglycan (GAG) adhesion molecules using its E8 protein. However, up until now, neither a structure for the MPXV E8 protein nor a specific cure for the MPXV exists. This study aimed to search for small molecules that inhibit the MPXV E8 protein, using computational approaches. In this study, a high-quality three-dimensional structure of the MPXV E8 protein was retrieved by homology modeling using the AlphaFold deep learning server. Subsequent molecular docking and molecular dynamics simulations (MDs) for a cumulative duration of 2.1 microseconds revealed that ZINC003977803 (Diosmin) and ZINC008215434 (Flavin adenine dinucleotide-FAD) could be potential inhibitors against the E8 protein with the MM/GBSA binding free energies of −38.19 ± 9.69 and −35.59 ± 7.65 kcal·mol−1, respectively.

This paper examines the effects of three distinct groups of uncertainties on market return and volatility in the Asia-Pacific countries, including (i) the country-specific and US geopolitical risks; (ii) the US economic policy uncertainty; and (iii) the US stock market volatility (using the VIX and SKEW indices). Our sample includes 11 Asia-Pacific countries for the 1985–2022 period. We employ the nonlinear autoregressive distributed lag approach (ARDL) estimation technique to capture the asymmetric effects of uncertainties on market return and volatility, which are documented in the literature. Some findings are documented as follows. First, we find that US uncertainty indices, including US geopolitical risk, US economic policy uncertainty, and US VIX, significantly impact Asia-Pacific stock markets, while the impacts of domestic geopolitical risk and the US skewness index (SKEW) are relatively weak. Second, Asia-Pacific stock markets tend to overreact to uncertainty shocks stemming from US economic policy uncertainty and US geopolitical risk. Third, US economic policy uncertainty has more significant effects than the US geopolitical risk. Finally, our research documents that Asia-Pacific stock markets react heterogeneously to good and bad news from US VIX. Specifically, an increase in US VIX (bad news) has a stronger impact than a decrease in US VIX (good news). Policy implications have emerged based on the findings of this study.

Object detection plays a significant role in various industrial and scientific domains, particularly in autonomous driving. It enables vehicles to detect surrounding objects, construct spatial maps, and facilitate safe navigation. To accomplish these tasks, a variety of sensors have been employed, including LiDAR, radar, RGB cameras, and ultrasonic sensors. Among these, LiDAR and RGB cameras are frequently utilized due to their advantages. RGB cameras offer high-resolution images with rich color and texture information but tend to underperform in low light or adverse weather conditions. In contrast, LiDAR provides precise 3D geometric data irrespective of lighting conditions, although it lacks the high spatial resolution of cameras. Recently, thermal cameras have gained significant attention in both standalone applications and in combination with RGB cameras. They offer strong perception capabilities under low-visibility conditions or adverse weather conditions. Multimodal sensor fusion effectively overcomes individual sensor limitations. In this paper, we propose a novel multimodal fusion method that integrates LiDAR, a 360 RGB camera, and a 360 thermal camera to fully leverage the strengths of each modality. Our method employs a feature-level fusion strategy that temporally accumulates and synchronizes multiple LiDAR frames. This design not only improves the detection accuracy but also enhances the spatial coverage and robustness. The use of 360 images significantly reduces blind spots and provides comprehensive environmental awareness, which is especially beneficial in complex or dynamic scenes.

The human gut microbiome is a dynamic and densely populated microbial community that can provide important benefits to its host. Cooperation and competition for nutrients among its constituents only partially explain community composition and interpersonal variation. Notably, certain human-associated Bacteroidetes—one of two major phyla in the gut—also encode machinery for contact-dependent interbacterial antagonism, but its impact within gut microbial communities remains unknown. Here we report that prominent human gut symbionts persist in the gut through continuous attack on their immediate neighbors. Our analysis of just one of the hundreds of species in these communities reveals 12 candidate antibacterial effector loci that can exist in 32 combinations. Through the use of secretome studies, in vitro bacterial interaction assays and multiple mouse models, we uncover strain-specific effector/immunity repertoires that can predict interbacterial interactions in vitro and in vivo, and find that some of these strains avoid contact-dependent killing by accumulating immunity genes to effectors that they do not encode. Effector transmission rates in live animals can exceed 1 billion events per minute per gram of colonic contents, and multiphylum communities of human gut commensals can partially protect sensitive strains from these attacks. Together, these results suggest that gut microbes can determine their interactions through direct contact. An understanding of the strategies human gut symbionts have evolved to target other members of this community may provide new approaches for microbiome manipulation.

This study examines the market return spillovers from the US market to 10 Asia-Pacific stock markets, accounting for approximately 91 per cent of the region’s GDP from 1991 to 2022. Our findings indicate an increased return spillover from the US stock market to the Asia-Pacific stock market over time, particularly after major global events such as the 1997 Asian and the 2008 global financial crises, the 2015 China stock market crash, and the COVID-19 pandemic. The 2008 global financial crisis had the most substantial impact on these events. In addition, the findings also indicate that US economic policy uncertainty and US geopolitical risk significantly affect spillovers from the US to the Asia-Pacific markets. In contrast, the geopolitical risk of Asia-Pacific countries reduces these spillovers. The study also highlights the significant impact of information and communication technologies (ICT) on these spillovers. Given the increasing integration of global financial markets, the findings of this research are expected to provide valuable policy implications for investors and policymakers.