Motif-Aware miRNA-Disease Association Prediction Via Hierarchical Attention Network.

As post-transcriptional regulators of gene expression, micro-ribonucleic acids (miRNAs) are regarded as potential biomarkers for a variety of diseases. Hence, the prediction of miRNA-disease associations (MDAs) is of great significance for an in-depth understanding of disease pathogenesis and progression. Existing prediction models are mainly concentrated on incorporating different sources of biological information to perform the MDA prediction task while failing to consider the fully potential utility of MDA network information at the motif-level. To overcome this problem, we propose a novel motif-aware MDA prediction model, namely MotifMDA, by fusing a variety of high- and low-order structural information. In particular, we first design several motifs of interest considering their ability to characterize how miRNAs are associated with diseases through different network structural patterns. Then, MotifMDA adopts a two-layer hierarchical attention to identify novel MDAs. Specifically, the first attention layer learns high-order motif preferences based on their occurrences in the given MDA network, while the second one learns the final embeddings of miRNAs and diseases through coupling high- and low-order preferences. Experimental results on two benchmark datasets have demonstrated the superior performance of MotifMDA over several state-of-the-art prediction models. This strongly indicates that accurate MDA prediction can be achieved by relying solely on MDA network information. Furthermore, our case studies indicate that the incorporation of motif-level structure information allows MotifMDA to discover novel MDAs from different perspectives. The data and codes are available at https://github.com/stevejobws/MotifMDA.

Giant unruptured sinus of Valsalva aneurysms causing angina pectoris.

BACKGROUND: Sinus of Valsalva aneurysm (SVA) is a rare cardiac anomaly which can be congenital or acquired. Patients with SVA are commonly asymptomatic when the occupying effect of SVA is insignificant, while ruptured SVA usually causes severe symptoms including heart failure and myocardial ischemia. CASE PRESENTATION: We present an unusual case of a 64-year-old female manifesting with exertional dyspnea as well as angina pectoris for three months. Echocardiography and cardiac computed tomographic angiography confirmed unruptured left-coronary and non-coronary SVAs. The left anterior descending artery and left circumflex artery were stretched and compressed by the SVA which causing myocardial ischemia. The patient finally received aortic root replacement (Bentall procedure) and got symptom relieved. CONCLUSIONS: Giant unruptured SVA originating from left coronary sinus is extremely rare. Our case highlights that giant SVA should be considered in cases with angina pectoris. Echocardiography and coronary computed tomographic angiography are useful and important for diagnosis. Surgery is highly recommended in patients with SVA.

TNF-α: A serological marker for evaluating the severity of hippocampal sclerosis in medial temporal lobe epilepsy?

OBJECTIVE: By analysing the difference in TNF-α levels in the peripheral blood of patients with medial temporal lobe epilepsy (mTLE) with or without hippocampal sclerosis and the correlation between TNF-α and N-acetylaspartate levels in the hippocampus, we explored the relationship between TNF-α and the degree of damage to hippocampal sclerosis neurons in medial temporal lobe epilepsy. METHODS: This is a prospective, population-based study. A total of 71 Patients with medial temporal lobe epilepsy diagnosed by clinical seizures, video-EEG, epileptic sequence MRI, and other imaging examinations were recruited from October 2020 to July 2022 in the Department of Neurology, Affiliated Hospital of Xuzhou Medical University. Twenty age-matched healthy subjects were selected as the control group. The patients were divided into two groups: the medial temporal epilepsy with hippocampal sclerosis group (positive group, mTLE-HS-P group) and the medial temporal epilepsy without hippocampal sclerosis group (negative group, mTLE-HS-N group). The levels of IL-1ß, IL-5, IL-6, IL-8, IL-17, IFN-γ and TNF-α in the peripheral blood of the patients in the three groups were detected by multimicrosphere flow immunofluorescence assay. The level of N-acetylaspartate (NAA) in the hippocampus was measured by 1H-MRS. The differences in cytokine levels among the three groups were analysed, and the correlation between cytokine and NAA levels was analysed. RESULTS: The level of TNF-α in the peripheral blood of the patients in the mTLE-HS-P group was significantly higher than that of the patients in the mTLE-HS-N and healthy control groups, and the level of TNF-α in the patients in the mTLE-HS-N group was significantly higher than that of the patients in the healthy control group. The NAA level in mTLE-HS-P group patients was significantly lower than that of mTLE-HS-N patients and healthy controls, but there was no significant difference between mTLE-HS-N patients and healthy controls (P > 0.05). Spearman correlation analysis showed that TNF-α level (rs = -0.437, P < 0.05) and the longest duration of a single seizure (rs = -0.398, P < 0.05) were negatively correlated with NAA level. Logistic regression analysis showed that there was no significant correlation between the longest duration of a single seizure and hippocampal sclerosis, but TNF-α level was closely related to hippocampal sclerosis in patients with mTLE (OR = 1.315, 95 % CI 1.084-1.595, P = 0.005). CONCLUSION: The level of TNF-α in the peripheral blood of patients with medial temporal lobe epilepsy with hippocampal sclerosis was higher, and it was correlated with NAA and hippocampal sclerosis. The high expression of TNF-α may be of important value in the evaluation of hippocampal sclerosis patients.

Nitrate transformation and source tracking of Yarlung Tsangpo River using a multi-tracer approach combined with Bayesian stable isotope mixing model.

Excessive levels of nitrate nitrogen (NO3--N) could lead to ecological issues, particularly in the Yarlung Tsangpo River (YTR) region located on the Qinghai Tibet Plateau. Therefore, it is crucial to understand the fate and sources of nitrogen to facilitate pollution mitigation efforts. Herein, multiple isotopes and source resolution models were applied to analyze key transformation processes and quantify the sources of NO3-. The δ15N-NO3- and δ18O-NO3- isotopic compositions in the YTR varied between 1.23‰ and 13.64‰ and -7.88‰-11.19‰, respectively. The NO3--N concentrations varied from 0.08 to -0.86 mg/L in the dry season and 0.20-1.19 mg/L during the wet season. Nitrification remained the primary process for nitrogen transformation in both seasons. However, the wet season had a widespread effect on increasing nitrate levels, while denitrification had a limited ability to reduce nitrate. The elevated nitrate concentrations during the flood season were caused by increased release of NO3- from manure & sewage (M&S) and chemical fertilizers (CF). Future endeavors should prioritize enhancing management strategies to improve the utilization efficiency of CF and hinder the direct entry of untreated sewage into the water system.

Quantification of the aromatase inhibitor letrozole and its carbinol metabolite in mouse plasma by UHPLC-MS/MS.

A liquid chromatography - electrospray ionization-mass spectrometry (LC-ESI-MS) method was developed for the quantification of letrozole, a third-generation aromatase inhibitor, and its main carbinol metabolite (CM) in support of murine pharmacokinetic studies. Using polarity switching, simultaneous ESI-MS measurement of letrozole and CM was achieved in positive and negative mode, respectively. The assay procedure involved a one-step protein precipitation and extraction of all analytes from mouse plasma requiring only 5 µL of sample. Separation was optimized on an Accucore aQ column with gradient elution at a flow rate of 0.4 mL/min in 5 min. Two calibration curves per day over four consecutive measurement days showed satisfactory linear responses (r2 > 0.99) over concentration ranges of 5-1000 ng/mL and 20-2000 ng/mL for letrozole and CM, respectively. No matrix effect was found, and the mean extraction recoveries were 103-108 % for letrozole and 99.8-107 % for CM. Precision and accuracy within a single run and over four consecutive measurement days were verified to be within acceptable limits. Application of the developed method to preclinical pharmacokinetic studies in mice receiving oral letrozole at a dose 1 or 10 mg/kg revealed that the systemic exposure to letrozole was dose-, formulation-, and strain-dependent. These findings may inform the future design of preclinical studies aimed at refining the pharmacological profile of this clinically important drug.

vEpiNet: A multimodal interictal epileptiform discharge detection method based on video and electroencephalogram data.

To enhance deep learning-based automated interictal epileptiform discharge (IED) detection, this study proposes a multimodal method, vEpiNet, that leverages video and electroencephalogram (EEG) data. Datasets comprise 24 931 IED (from 484 patients) and 166 094 non-IED 4-second video-EEG segments. The video data is processed by the proposed patient detection method, with frame difference and Simple Keypoints (SKPS) capturing patients' movements. EEG data is processed with EfficientNetV2. The video and EEG features are fused via a multilayer perceptron. We developed a comparative model, termed nEpiNet, to test the effectiveness of the video feature in vEpiNet. The 10-fold cross-validation was used for testing. The 10-fold cross-validation showed high areas under the receiver operating characteristic curve (AUROC) in both models, with a slightly superior AUROC (0.9902) in vEpiNet compared to nEpiNet (0.9878). Moreover, to test the model performance in real-world scenarios, we set a prospective test dataset, containing 215 h of raw video-EEG data from 50 patients. The result shows that the vEpiNet achieves an area under the precision-recall curve (AUPRC) of 0.8623, surpassing nEpiNet's 0.8316. Incorporating video data raises precision from 70% (95% CI, 69.8%-70.2%) to 76.6% (95% CI, 74.9%-78.2%) at 80% sensitivity and reduces false positives by nearly a third, with vEpiNet processing one-hour video-EEG data in 5.7 min on average. Our findings indicate that video data can significantly improve the performance and precision of IED detection, especially in prospective real clinic testing. It suggests that vEpiNet is a clinically viable and effective tool for IED analysis in real-world applications.

An improvement method for pancreas CT segmentation using superpixel-based active contour.

Pancreas is one of the most challenging organs for CT image automatic segmentation due to its complex shapes and fuzzy edges. It is simple and universal to use the traditional segmentation method as a post-processor of deep learning method for segmentation accuracy improvement. As the most suitable traditional segmentation method for pancreatic segmentation, the active contour model(ACM), still suffers from the problems of weak boundary leakage and slow contour evolution speed. Therefore, a convenient post-processor for any deep learning methods using superpixel-based active contour model(SbACM) is proposed to improve the segmentation accuracy. Firstly, the superpixels with strong adhesion to edges are used to guide the design of narrowband and energy function. A multi-scale evolution strategy is also proposed to reduce the weak boundary leakage and comprehensively improve the evolution speed. Secondly, using the original image and the coarse segmentation results obtained from deep learning methods as inputs, the proposed SbACM method is used as a post-processor for fine segmentation. Finally, the pancreatic segmentation public dataset TCIA from the National Institutes of Health(NIH, USA) is used for evaluation, and the Wilcoxon Test confirmed that the improvement of proposed method is statistically significant. The results show that: (1) The superpixel-based narrowband shape and dynamic edge energy of the proposed SbACM work for boundary leakage reduction, as well as the multi-scale evolution strategy and dynamic narrowband width for the evolution speed improvement; (2)As a post-processor, SbACM can increase the Dice similarity coefficients(DSC) of five typical UNet-based models, including UNet, SS-UNet, PBR UNet, ResDSN, and nnUNet, 2.35% in average and 9.04% in maximum. (3)Based on the best backbone nnUNet, the proposed post-processor performs better than either adding edge awareness or adding edge loss in segmentation enhancement without increasing the complexity and training time of deep learning models.

An Innovative and Efficient Fluorescent Detection Technique for Salmonella in Animal-Derived Foods Using the CRISPR/Cas12a-HCR System Combined with PCR/RAA.

Here, we present a method for Salmonella detection using clustered regularly interspaced short palindromic repeats associated with the CRISPR-associated protein 12a-hybridization chain reaction (CRISPR/Cas12a-HCR) system combined with polymerase chain reaction/recombinase-assisted amplification (PCR/RAA) technology. The approach relies on the Salmonella invA gene as a biorecognition element and its amplification through PCR and RAA. In the presence of the target gene, Cas12a, guided by crRNA, recognizes and cleaves the amplification product, initiating the HCR. Fluorescently labeled single-stranded DNA (ssDNA) H1 and H2 were introduced, and the Salmonella concentration was determined based on the fluorescence intensity from the triggered HCR. Both assays demonstrate high specificity, sensitivity, simplicity, and rapidity. The detection range was 2 × 101-2 × 109 CFU/mL, with an LOD of 20 CFU/mL, and the entire process enabled specific and rapid Salmonella detection within 85-105 min. Field-incurred spiked recovery tests were conducted in mutton and beef samples using both assays, demonstrating satisfactory recovery and accuracy in animal-derived foods. By combining CRISPR/Cas12a with hybridization chain reaction technology, this study presents a rapid and sensitive Salmonella detection method that is crucial for identifying pathogenic bacteria and monitoring food safety.

To characterize small renal cell carcinoma using diffusion relaxation correlation spectroscopic imaging and apparent diffusion coefficient based histogram analysis: a preliminary study.

PURPOSE: To study the capability of diffusion-relaxation correlation spectroscopic imaging (DR-CSI) on subtype classification and grade differentiation for small renal cell carcinoma (RCC). Histogram analysis for apparent diffusion coefficient (ADC) was studied for comparison. MATERIALS AND METHODS: A total of 61 patients with small RCC (< 4 cm) were included in the retrospective study. MRI data were reviewed, including a multi-b (0-1500 s/mm2) multi-TE (51-200 ms) diffusion weighted imaging (DWI) sequence. Region of interest (ROI) was delineated manually on DWI to include solid tumor. For each patient, a D-T2 spectrum was fitted and segmented into 5 compartments, and the volume fractions VA, VB, VC, VD, VE were obtained. ADC mapping was calculated, and histogram parameters ADC 90th, 10th, median, standard deviation, skewness and kurtosis were obtained. All MRI metrices were compared between clear cell RCC (ccRCC) and non-ccRCC group, and between high-grade and low-grade group. Receiver operator curve analysis was used to assess the corresponding diagnostic performance. RESULTS: Significantly higher ADC 90th, ADC 10th and ADC median, and significantly lower DR-CSI VB was found for ccRCC compared to non-ccRCC. Significantly lower ADC 90th, ADC median and significantly higher VB was found for high-grade RCC compared to low-grade. For identifying ccRCC from non-ccRCC, VB showed the highest area under curve (AUC, 0.861) and specificity (0.882). For differentiating high- from low-grade, ADC 90th showed the highest AUC (0.726) and specificity (0.786), while VB also displayed a moderate AUC (0.715). CONCLUSION: DR-CSI may offer improved accuracy in subtype identification for small RCC, while do not show better performance for small RCC grading compared to ADC histogram.

Efficacy and safety of GST-HG171 in adult patients with mild to moderate COVID-19: a randomised, double-blind, placebo-controlled phase 2/3 trial.

Background: GST-HG171 is a potent, broad-spectrum, orally bioavailable small-molecule 3C like protease inhibitor that has demonstrated greater potency and efficacy compared to Nirmatrelvir in pre-clinical studies. We aimed to evaluate the efficacy and safety of orally administered GST-HG171 plus Ritonavir in patients with coronavirus disease 2019 (COVID-19) infected with emerging XBB and non-XBB variants. Methods: This randomised, double-blind, placebo-controlled phase 2/3 trial was conducted in 47 sites in China among adult patients with mild-to-moderate COVID-19 with symptoms onset ≤72 h. Eligible patients were randomised 1:1 to receive GST-HG171 (150 mg) plus Ritonavir (100 mg) or corresponding placebo tablets twice daily for 5 days, with stratification factors including the risk level of disease progression and vaccination status. The primary efficacy endpoint was time to sustained recovery of clinical symptoms within 28 days, defined as a score of 0 for 11 COVID-19-related target symptoms for 2 consecutive days, assessed in the modified intention-to-treat (mITT) population. This trial was registered at ClinicalTrials.gov (NCT05656443) and Chinese Clinical Trial Registry (ChiCTR2200067088). Findings: Between Dec 19, 2022, and May 4, 2023, 1525 patients were screened. Among 1246 patients who underwent randomisation, most completed basic (21.2%) or booster (74.9%) COVID-19 immunization, and most had a low risk of disease progression at baseline. 610 of 617 who received GST-HG171 plus Ritonavir and 603 of 610 who received placebo were included in the mITT population. Patients who received GST-HG171 plus Ritonavir showed shortened median time to sustained recovery of clinical symptoms compared to the placebo group (13.0 days [95.45% confidence interval 12.0-15.0] vs. 15.0 days [14.0-15.0], P = 0.031). Consistent results were observed in both SARS-CoV-2 XBB (45.7%, 481/1053 of mITT population) and non-XBB variants (54.3%, 572/1053 of mITT population) subgroups. Incidence of adverse events was similar in the GST-HG171 plus Ritonavir (320/617, 51.9%) and placebo group (298/610, 48.9%). The most common adverse events in both placebo and treatment groups were hypertriglyceridaemia (10.0% vs. 14.7%). No deaths occurred. Interpretation: Treatment with GST-HG171 plus Ritonavir has demonstrated benefits in symptom recovery and viral clearance among low-risk vaccinated adult patients with COVID-19, without apparent safety concerns. As most patients were treated within 2 days after symptom onset in our study, confirming the potential benefits of symptom recovery for patients with a longer duration between symptom onset and treatment initiation will require real-world studies. Funding: Fujian Akeylink Biotechnology Co., Ltd.

Intermittent hypoxic pretreatment exacerbates house dust mite-induced asthma airway inflammation.

BACKGROUND: Asthma is widely recognized as an inflammatory disorder. In the context of this inflammatory microenvironment, the involvement of hypoxia and its impact on related pathways have drawn considerable attention. However, the exact role of hypoxia, a prevalent environmental factor, in the development and progression of asthma remains poorly understood. METHODS: Mice were treated with house dust mite (HDM) extracts for 23 days to induce asthma. Mice were divided into room air (RA) group and intermittent hypoxic (IH) group by exposing to different conditions and IH preconditioning (IHP) were underwent to the above groups before the hypoxic regimen. Airway inflammation in mice was evaluated by airway hyperresponsiveness, excessive mucus secretion, and recruitment of inflammatory cells. Immunohistochemistry was employed to quantify the expression levels of NF-κB. Subsequently, the dose of allergen was modified to investigate whether the impact of hypoxia on asthma is affected by different doses of allergens. RESULT: Compared to the RA and IH groups, HDM-treated mice in the IHP group exhibited aggravated inflammatory cell infiltration and airway hyperresponsiveness (p＜.05). Moreover, there was an increased release of inflammatory mediators and higher expression levels of NF-κB (p＜.05). Importantly, the impact ia on asthma was found to be influenced by high dose of allergen (p＜.05). CONCLUSION: IHP treatment potentially exacerbates HDM-induced airway inflammation in asthma, with the involvement of NF-κB, particularly under high-dose allergen stimulation.

Recurrent neural network-based simultaneous cardiac T1, T2, and T1ρ mapping.

The purpose of the current study was to explore the feasibility of training a deep neural network to accelerate the process of generating T1, T2, and T1ρ maps for a recently proposed free-breathing cardiac multiparametric mapping technique, where a recurrent neural network (RNN) was utilized to exploit the temporal correlation among the multicontrast images. The RNN-based model was developed for rapid and accurate T1, T2, and T1ρ estimation. Bloch simulation was performed to simulate a dataset of more than 10 million signals and time correspondences with different noise levels for network training. The proposed RNN-based method was compared with a dictionary-matching method and a conventional mapping method to evaluate the model's effectiveness in phantom and in vivo studies at 3 T, respectively. In phantom studies, the RNN-based method and the dictionary-matching method achieved similar accuracy and precision in T1, T2, and T1ρ estimations. In in vivo studies, the estimated T1, T2, and T1ρ values obtained by the two methods achieved similar accuracy and precision for 10 healthy volunteers (T1: 1228.70 ± 53.80 vs. 1228.34 ± 52.91 ms, p > 0.1; T2: 40.70 ± 2.89 vs. 41.19 ± 2.91 ms, p > 0.1; T1ρ: 45.09 ± 4.47 vs. 45.23 ± 4.65 ms, p > 0.1). The RNN-based method can generate cardiac multiparameter quantitative maps simultaneously in just 2 s, achieving 60-fold acceleration compared with the dictionary-matching method. The RNN-accelerated method offers an almost instantaneous approach for reconstructing accurate T1, T2, and T1ρ maps, being much more efficient than the dictionary-matching method for the free-breathing multiparametric cardiac mapping technique, which may pave the way for inline mapping in clinical applications.

Investigation into the Dissolution Kinetics of Different MgO Desulfurizers in Flue Gas Desulfurization.

The paper introduced hydrophilic functional groups on the surface of the MgO desulfurizer to improve its dispersion and hydrophilicity on the basis of reducing the particle size of the MgO desulfurizer to the nanometer level. Mechanical grinding technology was used to improve the traditional two-step method to lay the foundation for its large-scale production. The stability test showed that the ζ potential of the 5 wt % modified MgO desulfurizer was greater than 50 mV with 30 days of storage, and the sedimentation rate was not more than 7%. The dissolution reactivity and kinetics experiments showed that the decrease of particle size and the increase of hydrophilicity and dispersion were conducive to accelerating the dissolution rate of the MgO desulfurizer and reducing the apparent activation energy. Meanwhile, the good dissolution rate of the modified MgO nanofluids prepared by the improved method could reduce the liquid film mass transfer resistance and prolonged the penetration time.

Clinical characteristics and immunogenicity after Omicron breakthrough infection in patients with chronic hepatitis B infection: A longitudinal observational study.

The clinical and immunological features after breakthrough infection (BTI) during Omicron wave in patients with chronic hepatitis B virus infection (CHB) are still unclear. A total of 101 patients with CHB from our previous coronavirus disease 2019 (COVID-19) vaccination cohort (NCT05007665), were continued to be followed up at the Second Affiliated Hospital of Chongqing Medical University after BTI, while an additional 39 healthcare workers after BTI were recruited as healthy controls (HCs). Clinical data were collected using questionnaire survey and electronic medical record. Blood samples were used to determine the antibody responses, as well as B and T cell responses. After BTI, the clinical symptoms of COVID-19 were mild to moderate in patients with CHB, with a median duration of 5 days. Compared with HCs, patients with CHB were more susceptible to develop moderate COVID-19. The liver function was not significantly damaged, and HBV-DNA was not activated in patients with CHB after BTI. Patients with CHB could elicit robust antibody responses after BTI (NAbs 13.0-fold, BA.5 IgG: 24.2-fold, respectively), which was also significantly higher than that in every period after vaccination (all p < 0.001), and compared to that in HCs after BTI. The CD4+, cTfh, and CD8+ T cell responses were also augmented in patients with CHB after BTI, while exhibiting comparability to those observed in HCs. In patients with CHB after BTI, the immune imprint was observed in B cell responses, rather than in T cell responses. In conclusion, Omicron breakthrough infection induced mild to moderate COVID-19 symptoms in patients with CHB, without exacerbating the progress of liver diseases. Meanwhile, BTI demonstrated the ability to induce robust antibody and T cell responses in patients with CHB, which was comparable to those observed in HCs.

Darolutamide does not interfere with OATP-mediated uptake of docetaxel.

The addition of darolutamide, an androgen receptor signalling inhibitor, to therapy with docetaxel has recently been approved as a strategy to treat metastatic prostate cancer. OATP1B3 is an SLC transporter that is highly expressed in prostate cancer and is responsible for the accumulation of substrates, including docetaxel, into tumours. Given that darolutamide inhibits OATP1B3 in vitro, we sought to characterise the impact of darolutamide on docetaxel pharmacokinetics. We investigated the influence of darolutamide on OATP1B3 transport using in vitro and in vivo models. We assessed the impact of darolutamide on the tumour accumulation of docetaxel in a patient-derived xenograft (PDX) model and on an OATP1B biomarker in patients. Darolutamide inhibited OATP1B3 in vitro at concentrations higher than the reported Cmax . Consistent with these findings, in vivo studies revealed that darolutamide does not influence the pharmacokinetics of Oatp1b substrates, including docetaxel. Docetaxel accumulation in PDX tumours was not decreased in the presence of darolutamide. Metastatic prostate cancer patients had similar levels of OATP1B biomarkers, regardless of treatment with darolutamide. Consistent with a low potential to inhibit OATP1B3-mediated transport in vitro, darolutamide does not significantly impede the transport of Oatp1b substrates in vivo or in patients. Our findings support combined treatment with docetaxel and darolutamide, as no OATP1B3 transporter based drug-drug interaction was identified.

Cross-Modal Retrieval With Noisy Correspondence via Consistency Refining and Mining.

The success of existing cross-modal retrieval (CMR) methods heavily rely on the assumption that the annotated cross-modal correspondence is faultless. In practice, however, the correspondence of some pairs would be inevitably contaminated during data collection or annotation, thus leading to the so-called Noisy Correspondence (NC) problem. To alleviate the influence of NC, we propose a novel method termed Consistency REfining And Mining (CREAM) by revealing and exploiting the difference between correspondence and consistency. Specifically, the correspondence and the consistency only be coincident for true positive and true negative pairs, while being distinct for false positive and false negative pairs. Based on the observation, CREAM employs a collaborative learning paradigm to detect and rectify the correspondence of positives, and a negative mining approach to explore and utilize the consistency. Thanks to the consistency refining and mining strategy of CREAM, the overfitting on the false positives could be prevented and the consistency rooted in the false negatives could be exploited, thus leading to a robust CMR method. Extensive experiments verify the effectiveness of our method on three image-text benchmarks including Flickr30K, MS-COCO, and Conceptual Captions. Furthermore, we adopt our method into the graph matching task and the results demonstrate the robustness of our method against fine-grained NC problem. The code is available on https://github.com/XLearning-SCU/2024-TIP-CREAM.

A handheld isothermal fluorescence detector for duplex visualization of aquatic pathogens via enhanced one-pot LAMP-PfAgo assay.

The expansion of large-scale aquaculture has exacerbated the challenge of aquatic diseases, resulting in substantial economic losses annually. Currently, traditional laboratory-based diagnostic methods are time-consuming and costly, hindering on-site testing for individual farmers. We address this issue by developing a state-of-the-art handheld isothermal nucleic acid amplification device (WeD-1) capable of fluorescence tracking of reactions and integrating it with an enhanced one-pot Prokaryotic Argonaute based nucleic acid detection method, enabling duplex visual detection of aquatic pathogens. WeD-1 is portable, reusable, user-friendly, and cost-effective, offering real-time smartphone interaction and enabling real-time fluorescence observation during the reaction. The enhanced one-pot Loop-Mediated Isothermal Amplification (LAMP)-PfAgo method, incorporating paraffin-encapsulated lyophilized PfAgo protein, achieves precise target-specific cleavage, significantly enhancing multiplex nucleic acid detection. This innovation streamlines on-site testing, negating the need for specialized laboratory conditions while ensuring an aerosol-free system. With newly developed and highly sensitive LAMP primer sets, our compact WeD-1/LAMP-PfAgo nucleic acid rapid testing system exhibits remarkable sensitivity, readily detecting aquatic pathogens with naked eyes from rapidly prepared fish and shrimp samples within 40 min, even when the Ct values are as high as 34.

Research progress on natural preservatives of meat and meat products: classifications, mechanisms and applications.

Meat and meat products are highly susceptible to contamination by microorganisms and foodborne pathogens, which cause serious economic losses and health hazards. The large consumption and waste of meat and meat products means that there is a need for safe and effective preservation methods. Furthermore, toxicological aspects of chemical preservation techniques related to major health problems have sparked controversies and have prompted consumers and producers to turn to natural preservatives. Consequently, natural preservatives are being increasingly used to ensure the safety and quality of meat products as a result of customer preferences and biological efficacy. However, information on the current status of these preservatives is scattered and a comprehensive review is lacking. Here, we review current knowledge on the classification, mechanisms of natural preservatives and their applications in the preservation of meat and meat products, and also discuss the potential of natural preservatives to improve the safety of meat and meat products. The current status and the current research gaps in the extraction, application and controlled-release of natural antibacterial agents for meat preservation are also discussed in detail. This review may be useful to the development of efficient food preservation techniques in the meat industry. © 2024 Society of Chemical Industry.

Clinical and immunological features of COVID-19 in patients with anti-MDA5 dermatomyositis during the omicron wave in Chongqing, China.

Patients with anti-melanoma differentiation-associated gene 5 (anti-MDA5) dermatomyositis (DM) have a higher risk of coronavirus disease 2019 (COVID-19) infection. In this longitudinal observational study, we aimed to investigate the clinical and immunological features of these patients after COVID-19 infection. A total of 73 patients with anti-MDA5 DM were recruited from the Second Affiliated Hospital of Chongqing Medical University during the Omicron wave epidemic. Clinical data were collected by questionnaire survey and electronic medical records. Blood samples were used to determine the immunity responses. From December 9, 2022 to March 31, 2023, 67 patients were eligible for final analysis; 68.7% of them were infected with COVID-19. The most common symptoms observed in COVID-19 were upper respiratory symptoms, most cases were mild or moderate (97.8%). The clinical laboratory indexes were relativity stable in patients after infection (all p > 0.05). Vaccination is not a protective factor against the Omicron infection (odds ratio: 2.69, 95% confidence interval: 0.81-8.93, p = 0.105). Both wildtype (WT) neutralizing antibodies titer and BA.5-specific immunoglobulin G titer were significantly enhanced after infection (all p < 0.01), which was as high as healthy controls (HCs). The memory B-cell responses were similar between the patients with anti-MDA5 DM and HCs (p > 0.05). However, both the WT-specific CD8+ T cells and CD4+ T cells were reduced in patients with anti-MDA5 DM (all p < 0.05). In conclusion, patients with anti-MDA5 DM did not deteriorate the COVID-19, in turn, COVID-19 infection did not increase the risk of anti-MDA5 DM exacerbation. The humoral responses were robust but the cellular responses were weakened after COVID-19 infection.