Misdiagnosis of a Drain-site Hernia Containing Fallopian Tube Fimbria on 18F-FDG PET/CT.

In a 55-year-old woman with sigmoid colon cancer, a subcutaneous mass in the left lower abdomen was incidentally found and gradually enlarged. For further diagnosis and staging, an 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography scan was performed, which revealed a subcutaneous mass in the left lower abdomen with mild uptake of 18F-FDG, suggesting the possibility of metastasis. However, post-surgery and pathological confirmation, this mass was diagnosed as a drain-site hernia containing fallopian tube fimbria, which is extremely rare but should be considered in the differential diagnosis of subcutaneous mass in the lower abdomen.

Characterization of zoonotic hepatitis E virus in domestic pigs and wild boar in Vietnam: Implications for public health.

Vietnam's unprecedented demand for meat from livestock, including pigs and farmed wildlife, underscores the importance of understanding zoonotic reservoirs for hepatitis E virus (HEV). This study aimed to identify and characterize circulating zoonotic HEV in domestic pigs and wild boar to understand genotype frequencies, transmission dynamics, and associated human health burdens. Rectal swabs, feces, and liver samples from 415 pigs and 102 wild boars were collected across various farms and slaughterhouses in central and southern Vietnam and screened for HEV RNA using nested PCR. HEV RNA-positive samples underwent sanger sequencing and genotyping. Overall, 10% (n = 54/517) of samples were HEV RNA-positive, with wild boars exhibiting the highest HEV positivity rate at 25%, followed by domestic pigs at 7%. Southern Vietnam showed a higher HEV RNA positivity rate (20%) compared to central Vietnam (7%). Notably, rectal swabs demonstrated the highest positivity rate (15%), followed by feces (8%) and liver (4%). HEV-3a was the predominant genotype at 85%, followed by HEV-4b at 9% and HEV-3f at 6%. While HEV-3a was distributed across both central and southern Vietnam, HEV-3f was exclusively detected in central Vietnam, and HEV-4b was identified in wild boar in southern Vietnam. These findings underscore the substantial prevalence of HEV in wild boars, emphasizing their potential as crucial zoonotic reservoirs alongside domestic pigs. Further investigations involving occupationally exposed individuals in high-prevalence areas are warranted to evaluate the human health impact of zoonotic hepatitis E and inform preventive measures. Regular epidemiological studies are imperative for assessing the prevalence and transmission of zoonotic HEV infections among common reservoirs, thereby aiding in the prevention of spillover events within the community.

Evaluation of screening algorithms to detect rectal colonization with carbapenemase-producing Enterobacterales in a resource-limited setting.

Objectives: To improve and rationalize the detection of carbapenemase-producing Enterobacterales (CPE) in rectal swabs in a high-prevalence and resource-constrained setting, addressing surveillance challenges typically encountered in laboratories with limited resources. Methods: A point prevalence survey (PPS) was conducted on 15 August 2022, in a provincial children's hospital in northern Vietnam. Rectal swab samples of all admitted children were collected and plated on a selective medium for carbapenem-resistant Enterobacterales (CRE). Species identification and antimicrobial susceptibility testing (AST) were performed by MALDI-TOF, and VITEK2 XL and interpreted according to CLSI breakpoints (2022). Carbapenemases were detected by the carbapenem inactivation method (CIM) and quantitative real-time PCR (qRT-PCR). Results: Rectal swab samples were obtained from 376 patients. Of 178 isolates growing on the CRE screening agar, 140 isolates were confirmed as Enterobacterales of which 118 (84.3%) isolates were resistant to meropenem and/or ertapenem. CIM and PCR showed that 90/118 (76.3%) were carbapenemase producers. Overall, 83/367 (22.6%) were colonized by CPE. Klebsiella pneumoniae, Escherichia coli and Enterobacter cloacae complex were the most common CPE detected, with NDM as the predominant carbapenemase (78/90; 86.7%). Phenotypic resistance to meropenem was the best predictor of CPE production (sensitivity 85.6%, specificity 100%) compared with ertapenem resistance (95.6% sensitivity, 36% specificity). CIM was 100% concordant with PCR in detecting carbapenemases. Conclusions: These findings underscore the effectiveness of meropenem resistance as a robust indicator of the production of carbapenemases and the reliability of the CIM method to detect such carbapenemases in resource-limited settings where the performance of molecular methods is not possible.

AttentionPert: accurately modeling multiplexed genetic perturbations with multi-scale effects.

MOTIVATION: Genetic perturbations (e.g. knockouts, variants) have laid the foundation for our understanding of many diseases, implicating pathogenic mechanisms and indicating therapeutic targets. However, experimental assays are fundamentally limited by the number of measurable perturbations. Computational methods can fill this gap by predicting perturbation effects under novel conditions, but accurately predicting the transcriptional responses of cells to unseen perturbations remains a significant challenge. RESULTS: We address this by developing a novel attention-based neural network, AttentionPert, which accurately predicts gene expression under multiplexed perturbations and generalizes to unseen conditions. AttentionPert integrates global and local effects in a multi-scale model, representing both the nonuniform system-wide impact of the genetic perturbation and the localized disturbance in a network of gene-gene similarities, enhancing its ability to predict nuanced transcriptional responses to both single and multi-gene perturbations. In comprehensive experiments, AttentionPert demonstrates superior performance across multiple datasets outperforming the state-of-the-art method in predicting differential gene expressions and revealing novel gene regulations. AttentionPert marks a significant improvement over current methods, particularly in handling the diversity of gene perturbations and in predicting out-of-distribution scenarios. AVAILABILITY AND IMPLEMENTATION: Code is available at https://github.com/BaiDing1234/AttentionPert.

Large-scale foundation model on single-cell transcriptomics.

Large pretrained models have become foundation models leading to breakthroughs in natural language processing and related fields. Developing foundation models for deciphering the 'languages' of cells and facilitating biomedical research is promising yet challenging. Here we developed a large pretrained model scFoundation, also named 'xTrimoscFoundationα', with 100 million parameters covering about 20,000 genes, pretrained on over 50 million human single-cell transcriptomic profiles. scFoundation is a large-scale model in terms of the size of trainable parameters, dimensionality of genes and volume of training data. Its asymmetric transformer-like architecture and pretraining task design empower effectively capturing complex context relations among genes in a variety of cell types and states. Experiments showed its merit as a foundation model that achieved state-of-the-art performances in a diverse array of single-cell analysis tasks such as gene expression enhancement, tissue drug response prediction, single-cell drug response classification, single-cell perturbation prediction, cell type annotation and gene module inference.

Bioactive metabolite profiles and quality of Rosa rugosa during its growing and flower-drying process.

Rosa rugosa is extensively cultivated in China for its remarkable fragrance and flavor, however, the metabolic changes in roses during growth and drying remain unclear. Our results revealed significant variations in phenol and flavonoid contents and antioxidant capacity in roses (Rosa rugosa f. plena (Regel) Byhouwer) under different conditions. Phenol contents were positively correlated with antioxidant capacity, with phytochemicals being most prominent in unfolded petals. The highest antioxidant capacity and phenol and flavonoid contents were observed in April. Considering their greater consumption value, whole flowers were more suitable than petals alone. Furthermore, considerable sensory and nutritional differences were observed in dried roses. Different drying methods increased their total phenol content of roses by 4.2-5.4 times and the antioxidant capacity by 2.9 times. Metabolomics revealed the altered contents of flavonoids, anthocyanins, lipids, amino acids, and saccharides. This study provides baseline data for the potential of roses as a natural source of antioxidants in the food and pharmaceutical industries.

An isothermal CRISPR- based lateral flow assay for detection of Neisseria meningitidis.

BACKGROUND: Neisseria meningitidis can cause life-threatening meningococcal meningitis and meningococcemia. Old standard microbiological results from CSF/blood cultures are time consuming. This study aimed to combine the sensitivity of loop-mediated isothermal nucleic acid amplification (LAMP) with the specificity of CRISPR/Cas12a cleavage to demonstrate a reliable diagnostic assay for rapid detection of N. meningitidis. METHODS: A total of n = 139 samples were collected from patients with suspected meningococcal disease and were used for evaluation. The extracted DNA was subjected to qualitative real-time PCR, targeting capsular transporter gene (ctrA) of N. meningitidis. LAMP-specific primer pairs, also targeting the ctrA, were designed and the LAMP products were subjected to CRISPR/Cas12 cleavage reaction. the readout was on a lateral flow strip. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of LAMP-CRISPR/Cas was compared with real-time PCR assays. The limit of detection (LOD) was established with serial dilutions of the target N. meningitidis DNA and calculated by Probit regression analysis. RESULTS: Six LAMP assay-specific primers were developed targeting the ctrA gene of N. meningitidis, which is conserved in all meningococcal serogroups. The LAMP primers did not amplify DNA from other bacterial DNA tested, showing 100% specificity. The use of 0.4 M betaine increased the sensitivity and stability of the reaction. LAMP-CRISPR/Cas detected meningococcal serogroups (B, C, W). The assay showed no cross-reactivity and was specific for N. meningitidis. The LOD was 74 (95% CI: 47-311) N. meningitidis copies. The LAMP-CRISPR/Cas performed well compared to the gold standard. In the 139 samples from suspected patients, the sensitivity and specificity of the test were 91% and 99% respectively. CONCLUSION: This developed and optimized method can complement for the available gold standard for the timely diagnosis of meningococcal meningitis and meningococcemia.

Increased Prostate-Specific Membrane Antigen Uptake in a Gallbladder Stone.

ABSTRACT: An Al 18F-prostate-specific membrane antigen (PSMA) Q PET/CT scan was performed in a 67-year-old man to identify any potential recurrent prostate cancer lesions, which revealed no recurrent or metastatic lesions. However, a large gallbladder stone with increased PSMA uptake was incidentally detected, which could be a potential pitfall in the interpretation of PSMA PET imaging.

Supercritical CO2 fluid extract from Stellariae Radix ameliorates 2,4-dinitrochlorobenzene-induced atopic dermatitis by inhibit M1 macrophages polarization via AMPK activation.

Yin chai hu (Radix Stellariae) is a root medicine that is frequently used in Chinese traditional medicine to treat fever and malnutrition. In modern medicine, it has been discovered to have anti-inflammatory, anti-allergic, and anticancer properties. In a previous study, we were able to extract lipids from Stellariae Radix using supercritical CO2 extraction (SRE), and these sterol lipids accounted for up to 88.29% of the extract. However, the impact of SRE on the development of atopic dermatitis (AD) has not yet been investigated. This study investigates the inhibitory effects of SRE on AD development using a 2,4-dinitrochlorobenzene (DNCB)-induced AD mouse model. Treatment with SRE significantly reduced the dermatitis score and histopathological changes compared with the DNCB group. The study found that treatment with SRE resulted in a decrease of pro-inflammatory cytokines TNF-α, CXC-10, IL-12, and IL-1ß in skin lesions. Additionally, immunohistochemical analysis revealed that SRE effectively suppressed M1 macrophage infiltration into the AD lesion. Furthermore, the anti-inflammatory effect of SRE was evaluated in LPS + INF-γ induced bone marrow-derived macrophages (BMDMs) M1 polarization, SRE inhibited the production of TNF-α, CXC-10, IL-12, and IL-1ß and decreased the expression of NLRP3. Additionally, SRE was found to increase p-AMPKT172, but had no effect on total AMPK expression, after administration of the AMPK inhibitor Compound C, the inhibitory effect of SRE on M1 macrophages was partially reversed. The results indicate that SRE has an inhibitory effect on AD, making it a potential therapeutic agent for this atopic disorder.

On the Number of Linear Regions of Convolutional Neural Networks With Piecewise Linear Activations.

One fundamental problem in deep learning is understanding the excellent performance of deep Neural Networks (NNs) in practice. An explanation for the superiority of NNs is that they can realize a large family of complicated functions, i.e., they have powerful expressivity. The expressivity of a Neural Network with Piecewise Linear activations (PLNN) can be quantified by the maximal number of linear regions it can separate its input space into. In this paper, we provide several mathematical results needed for studying the linear regions of Convolutional Neural Networks with Piecewise Linear activations (PLCNNs), and use them to derive the maximal and average numbers of linear regions for one-layer PLCNNs. Furthermore, we obtain upper and lower bounds for the number of linear regions of multi-layer PLCNNs. Our results suggest that deeper PLCNNs have more powerful expressivity than shallow PLCNNs, while PLCNNs have more expressivity than fully-connected PLNNs per parameter, in terms of the number of linear regions.

Efficacy and safety of Ruxolitinib, Crisaborole, and Tapinarof for mild-to-moderate atopic dermatitis: a Bayesian network analysis of RCTs.

Given the lack of head-to-head studies of novel non-steroidal molecule topical therapies in mild-to-moderate atopic dermatitis (AD), network meta-analyses (NMAs) can provide comparative efficacy and safety data for clinical decision-making. In this NMA, we performed a literature search until 01 March 2023 for eligible studies written in English using databases, including PubMed, EMBASE, Cochrane Library, and ClinicalTrials.gov. Only double-blind randomized clinical trials (RCTs) with topical Ruxolitinib, Crisaborole, or Tapinarof versus vehicle for patients with mild-to-moderate AD were included. Baseline and follow-up data were extracted. Efficacy was evaluated using Investigator's Global Assessment (IGA) achieving "clear" or "almost clear," with 2 points or more improvement from baseline at the end of treatment, referred to as "IGA success." For binary outcomes, we analyzed in random-effects Bayesian NMA consistency models to compare the efficacy of these 3 topical therapies by odds ratio (OR) with 95% credibility interval (CrI). Overall, 10 phase 2 or phase 3 RCTs were identified, which included 4010 patients with mild to moderate AD. Compared with the topical vehicle control, all these 3 treatments had higher response rate of "IGA success" at the end of trial (Ruxolitinib 1.5% b.i.d: OR, 11.94; 95%CrI, 6.28-23.15; Crisaborole 2% b.i.d: OR, 2.08; 95%CrI, 1.46-3.52; Tapinarof 1% b.i.d: OR, 2.64; 95%CrI, 0.75-9.70). Notably, Ruxolitinib 1.5% b.i.d. had the highest probability of achieving "IGA success" in ranking analysis (Rank 1, SUCRA = 0.75) and lower risk of AE (Rank 8, SUCRA = 0.22). Besides, there was no difference in treatment-related adverse events between 3 therapies. Heterogeneity was not significant across studies.

Markers of prolonged hospitalisation in severe dengue.

BACKGROUND: Dengue is one of the most common diseases in the tropics and subtropics. Whilst mortality is a rare event when adequate supportive care can be provided, a large number of patients get hospitalised with dengue every year that places a heavy burden on local health systems. A better understanding of the support required at the time of hospitalisation is therefore of critical importance for healthcare planning, especially when resources are limited during major outbreaks. METHODS: Here we performed a retrospective analysis of clinical data from over 1500 individuals hospitalised with dengue in Vietnam between 2017 and 2019. Using a broad panel of potential biomarkers, we sought to evaluate robust predictors of prolonged hospitalisation periods. RESULTS: Our analyses revealed a lead-time bias, whereby early admission to hospital correlates with longer hospital stays - irrespective of disease severity. Importantly, taking into account the symptom duration prior to hospitalisation significantly affects observed associations between hospitalisation length and previously reported risk markers of prolonged stays, which themselves showed marked inter-annual variations. Once corrected for symptom duration, age, temperature at admission and elevated neutrophil-to-lymphocyte ratio were found predictive of longer hospitalisation periods. CONCLUSION: This study demonstrates that the time since dengue symptom onset is one of the most significant predictors for the length of hospital stays, independent of the assigned severity score. Pre-hospital symptom durations need to be accounted for to evaluate clinically relevant biomarkers of dengue hospitalisation trajectories.

Protein Multiple Conformation Prediction Using Multi-Objective Evolution Algorithm.

The breakthrough of AlphaFold2 and the publication of AlphaFold DB represent a significant advance in the field of predicting static protein structures. However, AlphaFold2 models tend to represent a single static structure, and multiple-conformation prediction remains a challenge. In this work, we proposed a method named MultiSFold, which uses a distance-based multi-objective evolutionary algorithm to predict multiple conformations. To begin, multiple energy landscapes are constructed using different competing constraints generated by deep learning. Subsequently, an iterative modal exploration and exploitation strategy is designed to sample conformations, incorporating multi-objective optimization, geometric optimization and structural similarity clustering. Finally, the final population is generated using a loop-specific sampling strategy to adjust the spatial orientations. MultiSFold was evaluated against state-of-the-art methods using a benchmark set containing 80 protein targets, each characterized by two representative conformational states. Based on the proposed metric, MultiSFold achieves a remarkable success ratio of 56.25% in predicting multiple conformations, while AlphaFold2 only achieves 10.00%, which may indicate that conformational sampling combined with knowledge gained through deep learning has the potential to generate conformations spanning the range between different conformational states. In addition, MultiSFold was tested on 244 human proteins with low structural accuracy in AlphaFold DB to test whether it could further improve the accuracy of static structures. The experimental results demonstrate the performance of MultiSFold, with a TM-score better than that of AlphaFold2 by 2.97% and RoseTTAFold by 7.72%. The online server is at http://zhanglab-bioinf.com/MultiSFold .

Exploration of Sweeping Effect: Droplet Coalescence Jumping of a Rolling and Static Droplet.

The sweeping effect of merged droplets plays a key role in enhancing application performance due to the continuing coalescence caused by the horizontal jumping velocity. Most studies focused on static droplet coalescence jumping, while moving droplet coalescence is poorly understood. In this work, we experimentally and numerically study the coalescence of a rolling droplet and a static one. When the droplet radius ratio is larger than 0.8, as the dimensionless initial velocity increases and the vertical jumping velocity first decreases and then increases. The critical dimensionless initial velocity Vc* corresponding to the minimum vertical jumping velocity could be estimated as 0.9(rs2rm2). When the droplet radius ratio is smaller than 0.8, the dimensionless initial velocity has a positive effect on the vertical jumping velocity. The mechanism of the vertical jumping velocity can be attributed to two parts: liquid bridge impact and retraction of the merged droplet. The squeezing effect generated by the initial velocity between the two droplets promotes the growth of the liquid bridge and enhances the impact effect of the liquid bridge but weakens the upward velocity accumulation caused by the retraction of the merged droplets. However, different from the vertical jumping velocity, the horizontal jumping velocity is approximately proportional to the dimensionless initial velocity. The outcome of our work elucidates a fundamental understanding of a rolling droplet coalescing with a static one.

Novel antiviral activity of dialdehyde starch

A significant effort worldwide is being directed toward development of novel biocides against drug-resistant bacterial and viruses because of the significant potential human infection risks in the general population. We report here the discovery of a strong antiviral biocide, dialdheyde starch (DAS). Antiviral tests were carried out against three non-envelop viruses, including two bacterial viruses MS2 and PRD1, and one human virus Poliovirus. Dialdehyde starch aqueous suspensions were effective biocides against these three test viruses in a 1 hr exposure test. The antiviral activity was significantly enhanced in a four-hour exposure test, with maximum seven orders of magnitude reductions against MS2 and PRD1, and four-order reduction against Poliovirus. The antiviral activity of dialdehyde starch was found to be pH dependent, being more active in alkaline and acidic conditions than in neutral conditions.