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Intravital imaging of translocated bacteria via fluorogenic labeling of gut microbiota in situ

The translocation of bacteria from intestinal tracts into blood vessels and distal organs plays pivotal roles in the pathogenesis of numerous severe diseases. Intravital monitoring of bacterial translocation, however, is not yet feasible, which greatly hinders us from comprehending this spatially and temporally dynamic process. Here we report an in vivo fluorogenic labeling method, which enables in situ imaging of mouse gut microbiota and real-time tracking of the translocated bacteria. By mimicking the peptidoglycan stem peptide in bacteria, a tetrapeptide probe composed of alternating D- and L-amino acids and separately equipped with a fluorophore and a quencher on the N- and C-terminal amino acid, is designed. Because of its resistance to host proteases, it can be directly used in gavage and achieves fluorogenic labeling of the microbiota in the gut via the functioning of the L,D-transpeptidases of the labeled bacteria. Using intravital two-photon microscopy, we then successfully visualize the translocation of gut bacteria into the bloodstream and liver in obesity mouse models. This technique can help further exploration into the spatiotemporal activities of gut microbiota in vivo, and be valuable in investigating the less understood pathogenicity of bacterial translocation in many severe diseases.

Examining isokinetic knee peak torque and time to peak torque as predictors of vertical jump height in division I men’s basketball players

The vertical jump (VJ) is one of the most important movements for basketball athletes and therefore determining modifiable predictors of the VJ would aid substantially in crafting more effective training regimens. The purpose of this study was to determine if isokinetic quadriceps strength and torque predict VJ height and which characteristics and testing speed is the strongest predictor of VJ height. Fifteen subjects (age: 18.5 ± 1.0 years, height: 195.9 ± 6.9 cm, weight: 96.2 ± 13.7 kg) from a single Division I men’s basketball team were recruited for this study. All participants performed a standing vertical jump with arm-swing to assess their maximum VJ height. Participants also completed an isokinetic knee extension strength protocol that included testing at multiple speeds. Pearson and Spearman tests found no significant correlation between jump height and peak torque at any of the speeds. Regression analysis showed a statistically significant relationship between time to peak torque at 300°/s and VJ height (R2 =  0.23, p =  0.04). These findings suggest that in a population of elite basketball players, the knee’s ability to rapidly generate torque likely plays a greater role in VJ performance than its ability to generate high magnitude of torque. This presents a potential benefit of explosive training regimens such as plyometrics for maximization of jump performance.

Kinetics of pIgR and IgM immune responses in snakehead (Channa argus) to inactivated Aeromonas hydrophila via immersion and intraperitoneal injection

Correction: Depression in the COVID-19 endemic era: Analysis of online self-disclosures by young South Koreans

Kinetic and isotherm studies of cr (VI) adsorption from aqueous media by using a synthetic chitosan-allophane nanocomposite

Mechanistic insights into dengue virus inhibition by a clinical trial compound NITD-688

Dengue, caused by the dengue virus (DENV), presents a significant public health challenge with limited effective treatments. NITD-688 is a potent panserotype DENV inhibitor currently in Phase II clinical trials. However, its mechanism of action is not fully understood. Here, we present the molecular details of how NITD-688 inhibits DENV. NITD-688 binds directly to the nonstructural protein 4B (NS4B) with nanomolar affinities across all four DENV serotypes and specifically disrupts the interaction between NS4B and nonstructural protein 3 (NS3) without significantly changing the interactions between NS4B and other viral or host proteins. NS4B mutations that confer resistance to NITD-688 reduce both NITD-688 binding to NS4B and disruption of the NS4B/NS3 interaction. Specifically, NITD-688 blocks the interaction of NS3 with a cytosolic loop within NS4B. This inhibits the formation of new NS4B/NS3 complexes and disrupts preexisting complexes in vitro and DENV-infected cells, ultimately inhibiting viral replication. Consistent with this mechanism, NITD-688 retains greater potency in cellular assays with delayed treatment compared to JNJ-1802, another NS4B inhibitor that has been studied in Phase II clinical trials. Together, these findings provide critical insights into the mechanism of action of NITD-688, facilitating the development of novel flavivirus NS4B inhibitors and informing future clinical interventions against DENV.

Extraction of total flavonoids from Chaenomeles speciosa (Sweet) Nakai and its antioxidant and lipoxygenase inhibition effects

Ultrasound-assisted extraction technology was utilized to extract total flavonoids from Chaenomeles speciosa (Sweet) Nakai, and response surface methodology was employed to optimize the extraction process. The anti-oxidant and lipoxygenase inhibitory activities were evaluated, along with an analysis of the type of inhibition. The results revealed that the optimal extraction conditions for total flavonoids from Chaenomeles speciosa (Sweet) Nakai were as follows: an ethanol concentration of 62%, a liquid-to-solid ratio of 15:1 mL/g, an ultrasonic temperature of 68°C, and an ultrasonic time of 40 min, resulting in a total flavonoid extraction rate of 10.18%. Antioxidant assays demonstrated that the Chaenomeles speciosa (Sweet) Nakai extract exhibited significant radical scavenging activities against 1,1-diphenyl-2-picrylhydrazyl radicals, 2,2’-azinobis (3-ethylbenzothiazoline-6-sulfonic acid ammonium salt) radicals, and hydroxyl radicals, with IC50 values of 582 µg/mL, 538 µg/mL, and 1709 µg/mL, respectively. Furthermore, enzyme inhibition assays indicated that the Chaenomeles speciosa (Sweet) Nakai extract possesses notable inhibitory activity against lipoxygenase, with an IC50 value of 2658 µg/mL. This inhibition is mediated through a mixed reversible inhibition mechanism.

USP4 promotes proliferation and metastasis in human lung adenocarcinoma

Discovery and functional characterization of a bombesin-type neuropeptide signaling system in an invertebrate

Neuropeptide signaling systems are key regulators of physiological and behavioral processes in animals. However, the evolutionary history of some neuropeptides originally discovered in vertebrates is unknown. The peptide bombesin (BN) was first isolated from the skin of the toad Bombina bombina and subsequently BN-related neuropeptides have been identified in other chordates, including gastrin-releasing peptide (GRP) and neuromedin B (NMB) in mammals, and a GRP-like peptide in the cephalochordate Branchiostoma japonicum . However, BN-type neuropeptides have hitherto not been identified in any nonchordate animals. Here, we report the discovery and functional characterization of a BN-type neuropeptide signaling system in an echinoderm—the starfish Asterias rubens . BN-type precursor proteins were identified in several echinoderm species based on their amino acid sequences and gene structures, and the mature structure of the A. rubens BN-type neuropeptide ArBN was determined using mass spectrometry. A protein related to vertebrate GRP/NMB-type G protein–coupled receptors was identified experimentally as the receptor for ArBN in A. rubens . Analysis of the distribution of the ArBN precursor in A. rubens using mRNA in situ hybridization and immunohistochemistry revealed a widespread pattern of expression in the central nervous system, digestive system, and locomotory organs. Moreover, effects of ArBN in A. rubens included contraction and retraction of the evertible stomach and inhibition of feeding behavior. Our findings show that the evolutionary history of BN-type neuropeptide signaling can be traced back to the deuterostome common ancestor of echinoderms and chordates. Furthermore, an ancient role of BN-type neuropeptides as regulators of feeding behavior has been revealed.

Explainable classification of goat vocalizations using convolutional neural networks

Efficient precision livestock farming relies on having timely access to data and information that accurately describes both the animals and their surrounding environment. This paper advances classification of goat vocalizations leveraging a publicly available dataset recorded at diverse farms breeding different species. We developed a Convolutional Neural Network (CNN) architecture tailored for classifying goat vocalizations, yielding an average classification rate of 95.8% in discriminating various goat emotional states. To this end, we suitably augmented the existing dataset using pitch shifting and time stretching techniques boosting the robustness of the trained model. After thoroughly demonstrating the superiority of the designed architecture over the contrasting approaches, we provide insights into the underlying mechanisms governing the proposed CNN by carrying out an extensive interpretation study. More specifically, we conducted an explainability analysis to identify the time-frequency content within goat vocalisations that significantly impacts the classification process. Such an XAI-driven validation not only provides transparency in the decision-making process of the CNN model but also sheds light on the acoustic features crucial for distinguishing the considered classes. Last but not least, the proposed solution encompasses an interactive scheme able to provide valuable information to animal scientists regarding the analysis performed by the model highlighting the distinctive components of the considered goat vocalizations. Our findings underline the effectiveness of data augmentation techniques in bolstering classification accuracy and highlight the significance of leveraging XAI methodologies for validating and interpreting complex machine learning models applied to animal vocalizations.

Source-specific fine particulates emission linked to prevalence of ophthalmic cases in India

Clinical breast cancer screening uptake and associated factors among reproductive age women in Kenya: further analysis of Kenyan Demographic and Health Survey 2022

Introduction Breast cancer is a global public health problem among reproductive-age women, with an estimated 670,000 deaths in 2022. It’s also a pressing health challenge in Sub-Saharan African countries, driven by late-stage diagnoses and limited healthcare access, underscoring the urgent need for early screening and treatment initiatives to combat this growing epidemic. In Kenya, the burden was also significant, and multilevel factors such as individual, household, and community level factors that influence screening uptake are undermined. Furthermore, there were no nationally representative studies. Therefore, this study aimed to assess clinical breast cancer screening uptake (CBCSU) and associated factors among reproductive-age women: further analysis of Kenyan demographic and health survey (KDHS) 2022. Methods This study used a weighted nationally representative sample of 16,649 women from the 2022 KDHS. A Multilevel mixed effects binary logistic regression analysis was performed and in the multivariable analysis, variables with a p-value less than 0.05 were considered statistically significant. The strength of the association was evaluated using Adjusted Odds Ratios (AOR) along with their corresponding 95% confidence intervals (CI). STATA version 17 software was to for data management and statistical analysis. Results The weighted prevalence of CBCSU in Kenya was 13.91% (95% CI: 13.33, 14.44). Besides, women aged 25 to 34 years (AOR =  1.86, 95% CI: 1.57, 2.21), and 35 to 49 years (AOR =  2.87, 95% CI: 2.40, 3.42) had higher odds of CBCSU. Women with primary education (AOR =  2.14, 95% CI: 1.56, 2.94) and those with secondary or higher education (AOR =  3.09, 95% CI: 2.23, 4.28) had higher odds of CBCSU. In addition, the odds of CBCSU were higher among women with a middle (AOR =  1.41, 95% CI: 1.19, 1.67) and a rich wealth index (AOR =  2.19, 95% CI: 1.84, 2.61). On the other hand, CBCSU was lower among non-contraceptive user women (AOR 0.78, 95% CI: 0.69, 0.87). Furthermore, women in communities with a high proportion of media exposure had higher CBCSU (AOR =  1.17, 95% CI: 1.04, 1.33). Conclusion In this study, the prevalence of CBCSU among reproductive-age women in Kenya was found to be low. Besides, factors such as age, educational status, wealth index, family planning utilization, and community media exposure were identified as significant contributors to screening uptake. Therefore, policymakers and stakeholders should design interventions that address factors contributing to low breast cancer screening uptake, particularly targeting women in areas with limited media exposure, to increase the uptake of clinical breast cancer screening.

Lipoic acid-plumbagin conjugate protects pancreatic beta cells against high glucose-induced toxicity

Retraction: Specific inhibition of tumor cells by oncogenic EGFR specific silencing by RNA interference

A population based study to analyse amyotrophic lateral sclerosis as a multi-step process

Dopaminergic neurons in the paraventricular hypothalamus extend the food consumption phase

Feeding behavior is controlled by various neural networks in the brain that are involved in different feeding phases: Food procurement, consumption, and termination. However, the specific neural circuits controlling the food consumption phase remain poorly understood. Here, we investigated the roles of dopaminergic neurons in the paraventricular nucleus of the hypothalamus (PVH) in the feeding behavior in mice. Our results indicated that the PVH dopaminergic neurons were critical for extending the food consumption phase and involved in the development of obesity through epigenetic mechanisms. These neurons synchronized with proopiomelanocortin neurons during consumption, were stimulated by proopiomelanocortin activation, and projected to the lateral habenula (LHb), where dopamine receptor D2 was involved in the increase in food consumption. In addition, upregulated tyrosine hydroxylase (TH) expression in PVH was associated with obesity and indispensable for obesity induction in mice lacking Dnmt3a . Taken together, our results highlight the roles of PVH dopaminergic neurons in promoting food consumption and obesity induction.

Colonization with extended-spectrum β-lactamase and carbapenemase-producing Enterobacterales in Ethiopia: A systematic review and meta-analysis

Background The human intestinal tract contains many commensals. However, during an imbalance of the normal microbiota following exposure to antibiotics, extended-spectrum β-lactamase- and carbapenemase-producing Enterobacterales emerge. Individuals colonized with these bacteria may develop subsequent infections themselves. Therefore, this review aimed to estimate the colonization rate of extended-spectrum β-lactamase- and carbapenemase-producing Enterobacterales in Ethiopia. Methods The protocol was registered (PROSPERO ID: CRD42024550137). A systematic literature search was conducted in electronic databases, including PubMed, Google Scholar, and Hinari, to retrieve potential studies. The quality of the included studies was assessed using the Joanna Briggs Institute critical appraisal tool. The data were extracted from the eligible studies using Microsoft Excel 2019 and analyzed using STATA version 11. Heterogeneity between studies was checked using I2 test statistics. Publication bias was assessed using funnel plots and Egger’s test. A random-effects model of DerSimonian-Laird method was employed to estimate the outcomes. Results A total of 15 studies with 4713 participants were included in the meta-analysis. The overall pooled colonization rates of extended-spectrum β-lactamase-producing and carbapenemase-producing Enterobacterales in Ethiopia were 28.5% (95% CI: 16.4-40.5%, I2 =  95.9%, p <  0.001) and 4.4% (95% CI: 0.9–7.9%, I2 =  0.0%, p =  0.64), respectively. The majority of the extended-spectrum β-lactamase producers were E. coli (20.6%, 95% CI: 9.3–31.9%, I2 =  94.4%, p < 0.001), followed by Klebsiella spp. (11.1%, 95% CI: 7.7–14.6%, I2 =  20.2%, p =  0.245). Similarly, the predominant carbapenemase producers were E. coli (2.7%, 95% CI: -1.3–6.7, I2 =  0.0%, p = 0.941) and Klebsiella spp. (2.1%, 95% CI: -1.7–5.9%, I2 =  0.0%, p = 0.999). Furthermore, the pooled estimate of multidrug resistance among extended-spectrum β-lactamase producers was 71.7% (95% CI: 55.25–88.05%, I2 =  92.9%, p < 0.001). Conclusion and recommendations Approximately one-quarter of Ethiopians are colonized with ESBL-PE, while about one in 25 is colonized with CPE. These findings were obtained from studies with a moderate-to-low risk of bias. However, the results for ESBL-PE showed significant variability, indicating high heterogeneity among the studies. This colonization may lead to subsequent extraintestinal infections. Therefore, proactive action from all stakeholders is required to combat the unrecognized spread of extended-spectrum β-lactamase- and carbapenemase-producing Enterobacterales in humans.

The regulatory effect of CoL10A1 to the intracranial vascular invasion and cell proliferation in breast cancer via EMT pathway

Linear Recursive Feature Machines provably recover low-rank matrices

A fundamental problem in machine learning is to understand how neural networks make accurate predictions, while seemingly bypassing the curse of dimensionality. A possible explanation is that common training algorithms for neural networks implicitly perform dimensionality reduction—a process called feature learning. Recent work [A. Radhakrishnan, D. Beaglehole, P. Pandit, M. Belkin, Science 383 , 1461–1467 (2024).] posited that the effects of feature learning can be elicited from a classical statistical estimator called the average gradient outer product (AGOP). The authors proposed Recursive Feature Machines (RFMs) as an algorithm that explicitly performs feature learning by alternating between 1) reweighting the feature vectors by the AGOP and 2) learning the prediction function in the transformed space. In this work, we develop theoretical guarantees for how RFM performs dimensionality reduction by focusing on the class of overparameterized problems arising in sparse linear regression and low-rank matrix recovery. Specifically, we show that RFM restricted to linear models (lin-RFM) reduces to a variant of the well-studied Iteratively Reweighted Least Squares (IRLS) algorithm. Furthermore, our results connect feature learning in neural networks and classical sparse recovery algorithms and shed light on how neural networks recover low rank structure from data. In addition, we provide an implementation of lin-RFM that scales to matrices with millions of missing entries. Our implementation is faster than the standard IRLS algorithms since it avoids forming singular value decompositions. It also outperforms deep linear networks for sparse linear regression and low-rank matrix completion.

Viral and host factors associated with SARS-CoV-2 disease severity in Georgia, USA

While SARS-CoV-2 vaccines have shown strong efficacy, the continued emergence of new viral variants raises concerns about the ongoing and future public health impact of COVID-19, especially in locations with suboptimal vaccination uptake. We investigated viral and host factors, including vaccination status, that were associated with SARS-CoV-2 disease severity in a setting with low vaccination rates. We analyzed clinical and demographic data from 1,957 individuals in the state of Georgia, USA, coupled with viral genome sequencing from 1,185 samples. We found no specific mutations associated with disease severity. Compared to those who were unvaccinated, vaccinated individuals experienced less severe SARS-CoV-2 disease, and the effect was similar for both variants. Vaccination within the prior 3-9 months was associated with decreased odds of moderate disease, severe disease, and death. Older age and underlying health conditions, especially immunosuppression and renal disease, were associated with increased disease severity. Overall, this study provides insights into the impact of vaccination status, variants/mutations, and clinical factors on disease severity in SARS-CoV-2 infection when vaccination rates are low. Understanding these associations will help refine and reinforce messaging around the crucial importance of vaccination in mitigating the severity of SARS-CoV-2 disease.