Bayesian hidden mark interaction model for detecting spatially variable genes in imaging-based spatially resolved transcriptomics data.

Recent technology breakthroughs in spatially resolved transcriptomics (SRT) have enabled the comprehensive molecular characterization of cells whilst preserving their spatial and gene expression contexts. One of the fundamental questions in analyzing SRT data is the identification of spatially variable genes whose expressions display spatially correlated patterns. Existing approaches are built upon either the Gaussian process-based model, which relies on ad hoc kernels, or the energy-based Ising model, which requires gene expression to be measured on a lattice grid. To overcome these potential limitations, we developed a generalized energy-based framework to model gene expression measured from imaging-based SRT platforms, accommodating the irregular spatial distribution of measured cells. Our Bayesian model applies a zero-inflated negative binomial mixture model to dichotomize the raw count data, reducing noise. Additionally, we incorporate a geostatistical mark interaction model with a generalized energy function, where the interaction parameter is used to identify the spatial pattern. Auxiliary variable MCMC algorithms were employed to sample from the posterior distribution with an intractable normalizing constant. We demonstrated the strength of our method on both simulated and real data. Our simulation study showed that our method captured various spatial patterns with high accuracy; moreover, analysis of a seqFISH dataset and a STARmap dataset established that our proposed method is able to identify genes with novel and strong spatial patterns.

Detection and characterization of eravacycline heteroresistance in clinical bacterial isolates.

Eravacycline (ERV) has emerged as a therapeutic option for the treatment of carbapenem-resistant pathogens. However, the advent of heteroresistance (HR) to ERV poses a challenge to these therapeutic strategies. This study aimed to investigate ERV HR prevalence among common clinical isolates and further characterize ERV HR in carbapenem-resistant Klebsiella pneumoniae (CRKP). A total of 280 clinical pathogens from two centers were selected for HR and analyzed using population analysis profiling (PAP) and modified E-tests. The PAP assay revealed an overall ERV HR prevalence of 0.7% (2/280), with intermediate heterogeneity observed in 24.3% (68/280) of strains. The proportion of heteroresistant strains was 18.3% according to modified E-test results. A time-killing assay demonstrated that CRKP CFU increased significantly after 10 h of ERV treatment, contributing to the reduced bactericidal effect of ERV in vitro. Interestingly, dual treatment with ERV and polymyxin B effectively inhibited the total CFU, simultaneously reducing the required polymyxin B concentration. Furthermore, fitness cost measurements revealed a growth trade-off in CRKP upon acquiring drug resistance, highlighting fitness costs as crucial factors in the emergence of ERV HR in CRKP. Overall, the findings of the current study suggest that ERV HR in clinical strains presents a potential obstacle in its clinical application.

Intranasal delivery of phenytoin loaded layered double hydroxide nanoparticles improves therapeutic effect on epileptic seizures.

Improving the efficiency of antiseizure medication entering the brain is the key to reducing its peripheral toxicity. A combination of intranasal administration and nanomedicine presents a practical approach for treating epileptic seizures via bypassing the blood-brain barrier. In this study, phenytoin (PHT) loaded layered double hydroxide nanoparticles (BSA-LDHs-PHT) were fabricated via a coprecipitation - hydrothermal method for epileptic seizure control. In this study, we expound on the preparation method and characterization of BSA-LDHs-PHT. In-vitro drug release experiment shows both rapid and continuous drug release from BSA-LDHs-PHT, which is crucial for acute seizure control and chronic epilepsy therapy. In-vivo biodistribution assays after intranasal administration indicate excellent brain targeting ability of BSA-LDHs. Compared to BSA-Cyanine5.5, BSA-LDHs-Cyanine5.5 were associated with a higher brain/peripheral ratio across all tested time points. Following intranasal delivery with small doses of BSA-LDHs-PHT, the latency of seizures in the pentylenetetrazole-induced mouse models was effectively improved. Collectively, the present study successfully designed and applied BSA-LDHs-PHT as a promising strategy for treating epileptic seizures with an enhanced therapeutic effect.

Risk factors for amputation in diabetic foot ulcers: A retrospective analysis.

Diabetic foot ulcers (DFUs) are chronic, difficult-to-heal wounds with a very high incidence of amputation. For patients with DFUs, prevention of amputation is crucial. However, the risk factors associated with DFU amputation and the extent to which different risk factors increase the risk of amputation are still uncertain. This study intends to provide a clinical basis for early intervention in DFU by retrospectively analysing the risk factors for DFU amputation. A retrospective analysis of 200 patients with DFUs admitted between October 2019 and October 2023 was conducted. Sixty-eight of the 200 underwent amputations. The overall amputation rate was 34%. Multiple logistic regression model showed that neutrophil/lymphocyte ratio (OR = 1.943; 95% CI:1.826-2.139), white blood cell (OR = 1.143; 95% CI:1.034-1.267), C-reactive protein (OR = 1.307; 95% CI:1.113-2.194) and Wagner grading (OR = 2.783; 95% CI: 1.751-4.302) were independent risk factors for amputation, while haemoglobin (OR = 0.742; 95% CI:0.638-0.965) and high density lipoprotein were independent protective factors for amputation (OR = 0.168; 95% CI:0.037-0.716), and further Receiver Operating Characteristic Curve curves showed that they showed high accuracy and were good predictors of amputation of DFUs.

Image-based profiling and deep learning reveal morphological heterogeneity of colorectal cancer organoids.

Patient-derived organoids have proven to be a highly relevant model for evaluating of disease mechanisms and drug efficacies, as they closely recapitulate in vivo physiology. Colorectal cancer organoids, specifically, exhibit a diverse range of morphologies, which have been analyzed with image-based profiling. However, the relationship between morphological subtypes and functional parameters of the organoids remains underexplored. Here, we identified two distinct morphological subtypes ("cystic" and "solid") across 31360 bright field images using image-based profiling, which correlated differently with viability and apoptosis level of colorectal cancer organoids. Leveraging object detection neural networks, we were able to categorize single organoids achieving higher viability scores as "cystic" than "solid" subtype. Furthermore, a deep generative model was proposed to predict apoptosis intensity based on a apoptosis-featured dataset encompassing over 17000 bright field and matched fluorescent images. Notably, a significant correlation of 0.91 between the predicted value and ground truth was achived, underscoring the feasibility of this generative model as a potential means for assessing organoid functional parameters. The underlying cellular heterogeneity of the organoids, i.e., conserved colonic cell types and rare immune components, was also verified with scRNA sequencing, implying a compromised tumor microenvironment. Additionally, the "cystic" subtype was identified as a relapse phenotype featuring intestinal stem cell signatures, suggesting that this visually discernible relapse phenotype shows potential as a novel biomarker for colorectal cancer diagnosis and prognosis. In summary, our findings demonstrate that the morphological heterogeneity of colorectal cancer organoids explicitly recapitulate the association of phenotypic features and exogenous perturbations through the image-based profiling, providing new insights into disease mechanisms.

Hormonal Changes in Women with Epilepsy.

Epilepsy is a prevalent neurological disorder among women globally, often requiring long-term treatment. Hormonal fluctuations in women with epilepsy (WWE) can have reciprocal effects on epilepsy and antiseizure medications (ASMs), posing significant challenges for WWE. Notably, WWE commonly experience endocrine alterations such as thyroid dysfunctions, low bone metabolism, and reproductive hormone irregularities. On the one hand, the presence of hormones in women with epilepsy affects their susceptibility to epilepsy as well as the metabolism of antiseizure medications in various ways. On the other hand, epilepsy itself and the use of antiseizure medications impact the production, secretion, and metabolism of hormones, resulting in low fertility, increased risk of pregnancy complications, negative offspring outcomes, and so on. In order to develop more precise treatment strategies in the future, it is necessary to comprehend the explicit relationships between hormones, epilepsy, and antiseizure medications, as well as to elucidate the currently known mechanisms underlying these interactions.

Recognition memory deficits detected through eye-tracking in well-controlled children with self-limited epilepsy with centrotemporal spikes.

OBJECTIVE: Children with self-limited epilepsy characterized by centrotemporal spikes (SeLECTS) exhibit cognitive deficits in memory during the active phase, but there is currently a lack of studies and techniques to assess their memory development after well-controlled seizures. In this study, we employed eye-tracking techniques to investigate visual memory and its association with clinical factors and global intellectual ability, aiming to identify potential risk factors by examining encoding and recognition processes. METHODS: A total of 26 recruited patients diagnosed with SeLECTS who had been seizure-free for at least 2 years, along with 24 control subjects, underwent Wechsler cognitive assessment and an eye-movement-based memory task while video-electroencephalographic (EEG) data were recorded. Fixation and pupil data related to eye movements were utilized to detect distinct memory processes and subsequently to compare the cognitive performance of patients exhibiting different regression patterns on EEG. RESULTS: The findings revealed persistent impairments in visual memory among children with SeLECTS after being well controlled, primarily observed in the recognition stage rather than the encoding phase. Furthermore, the age at onset, frequency of seizures, and interictal epileptiform discharges exhibited significant correlations with eye movement data. SIGNIFICANCE: Children with SeLECTS exhibit persistent recognition memory impairment after being well controlled for the disease. Controlling the frequency of seizures and reducing prolonged epileptiform activity may improve memory cognitive development. The application of the eye-tracking technique may provide novel insights into exploring memory cognition as well as underlying mechanisms associated with pediatric epilepsy.

A qualitative exploration of 40 Hz sound and music for older adults with mild cognitive impairment.

Emerging evidence suggests that 40 Hz auditory stimulation may benefit cognition. Nested within a randomized crossover trial, this qualitative study evaluates the acceptability and experience of three auditory interventions-self-selected music, 40 Hz sound, and a novel combination, termed 40 Hz music-in individuals with Mild Cognitive Impairment (MCI). Semi-structured interviews were conducted with individuals with MCI post-intervention exposure. Findings indicated a preference for self-selected music due to its memory-boosting and emotional benefits, while responses to 40 Hz sound were mixed, with several participants reporting discomfort. The composite 40 Hz music intervention showed promise, striking a balance by enhancing user experience and mitigating the 40 Hz sound's negative aspects. Engagement was influenced by personal music interests, listening routines, and support networks. This study highlights the potential of integrating 40 Hz sound with personalized music to offer a more acceptable 40 Hz auditory intervention for cognition in older adults with MCI.

Pregnancy-related knowledge in women with epilepsy in childbearing age: A pilot questionnaire survey from China.

PURPOSE: We aim to understand the knowledge of and attitudes toward pregnancy issues among women with epilepsy (WWE) and their caregivers and analyze the answers from the questionnaire to expose topics that require educational activities; thus, WWE experiences pregnancy better. METHODS: WWE at their childbearing age and/or their caregivers who entered the Fourth Affiliated Hospital of Zhejiang University for treatment of their condition were invited to fill out a questionnaire between March 1 and November 31, 2022. RESULTS: A combined total of 205 WWE and 142 caregivers completed the questionnaires. Among the surveyed WWE, a majority (63.74%) reported experiencing at least one miscarriage or induced abortion. However, a significant proportion (84.62%) of these WWE were still able to successfully give birth to at least one child. Furthermore, the offspring of these WWE showed no significant differences compared to the offspring of women without epilepsy, as reported by 93.51% of the participants. The participants' knowledge regarding the impact of epilepsy on pregnancy was found to be comparable, with average scores of 7.74 and 7.84, respectively. The participants exhibited a limited comprehension of antiseizure medications (ASMs)-related knowledge, specifically pertaining to ASMs adjustment during pregnancy (17.56% vs. 16.90%) and offspring outcomes (30.24% vs. 26.06%). Statistical analysis revealed significant correlations between the overall score and education level (p < .001), as well as epilepsy duration (p = .008). Regarding the source of knowledge, participants acknowledged primarily relying on neurologists, who remained their preferred choice for consultation. CONCLUSION: In our study, the understanding of pregnancy-related knowledge did not differ from WWE and their caregivers, both are far from satisfactory in certain areas. It is urgent for WWE and their caregivers to improve their pregnancy-related knowledge of epilepsy. As their primary access is from knowledgeable health care professionals like neurologists, well-trained neurologists in epilepsy management during pregnancy are in need.

DNMT3A Cooperates with YAP/TAZ to Drive Gallbladder Cancer Metastasis.

Gallbladder cancer (GBC) is an extremely lethal malignancy with aggressive behaviors, including liver or distant metastasis; however, the underlying mechanisms driving the metastasis of GBC remain poorly understood. In this study, it is found that DNA methyltransferase DNMT3A is highly expressed in GBC tumor tissues compared to matched adjacent normal tissues. Clinicopathological analysis shows that DNMT3A is positively correlated with liver metastasis and poor overall survival outcomes in patients with GBC. Functional analysis confirms that DNMT3A promotes the metastasis of GBC cells in a manner dependent on its DNA methyltransferase activity. Mechanistically, DNMT3A interacts with and is recruited by YAP/TAZ to recognize and access the CpG island within the CDH1 promoter and generates hypermethylation of the CDH1 promoter, which leads to transcriptional silencing of CDH1 and accelerated epithelial-to-mesenchymal transition. Using tissue microarrays, the association between the expression of DNMT3A, YAP/TAZ, and CDH1 is confirmed, which affects the metastatic ability of GBC. These results reveal a novel mechanism through which DNMT3A recruitment by YAP/TAZ guides DNA methylation to drive GBC metastasis and provide insights into the treatment of GBC metastasis by targeting the functional connection between DNMT3A and YAP/TAZ.

Inflammatory markers for improved recurrent UTI diagnosis in postmenopausal women.

Recurrent urinary tract infection (rUTI) severely impacts postmenopausal women. The lack of rapid and accurate diagnostic tools is a major obstacle in rUTI management as current gold standard methods have >24-h diagnostic windows. Work in animal models and limited human cohorts have identified robust inflammatory responses activated during UTI. Consequently, urinary inflammatory cytokines secreted during UTI may function as diagnostic biomarkers. This study aimed to identify urinary cytokines that could accurately diagnose UTI in a controlled cohort of postmenopausal women. Women passing study exclusion criteria were classified into no UTI and active rUTI groups, and urinary cytokine levels were measured by immunoassay. Pro-inflammatory cytokines IL-8, IL-18, IL-1ß, and monocyte chemoattractant protein-1 were significantly elevated in the active rUTI group, and anti-inflammatory cytokines IL-13 and IL-4 were elevated in women without UTI. We evaluated cytokine diagnostic performance and found that an IL-8, prostaglandin E2, and IL-13 multivariable model had the lowest misclassification rate and highest sensitivity. Our data identify urinary IL-8, prostaglandin E2, and IL-13 as candidate biomarkers that may be useful in the development of immunoassay-based UTI diagnostics.

A fast and non-invasive artificial intelligence olfactory-like system that aids diagnosis of Parkinson's disease.

BACKGROUND AND PURPOSE: Several previous studies have shown that skin sebum analysis can be used to diagnose Parkinson's disease (PD). The aim of this study was to develop a portable artificial intelligence olfactory-like (AIO) system based on gas chromatographic analysis of the volatile organic compounds (VOCs) in patient sebum and explore its application value in the diagnosis of PD. METHODS: The skin VOCs from 121 PD patients and 129 healthy controls were analyzed using the AIO system and three classic machine learning models were established, including the gradient boosting decision tree (GBDT), random forest and extreme gradient boosting, to assist the diagnosis of PD and predict its severity. RESULTS: A 20-s time series of AIO system data were collected from each participant. The VOC peaks at a large number of time points roughly concentrated around 5-12 s were significantly higher in PD subjects. The gradient boosting decision tree model showed the best ability to differentiate PD from healthy controls, yielding a sensitivity of 83.33% and a specificity of 84.00%. However, the system failed to predict PD progression scored by Hoehn-Yahr stage. CONCLUSIONS: This study provides a fast, low-cost and non-invasive method to distinguish PD patients from healthy controls. Furthermore, our study also indicates abnormal sebaceous gland secretion in PD patients, providing new evidence for exploring the pathogenesis of PD.

Social Factors and Older Adults' Use of Wearable Activity Trackers: Before and During the First Wave of the COVID-19 Pandemic.

Wearable activity trackers (WAT) have shown high potential to improve health in the aging population. Evidence links various social factors with WAT use in older adults, but mainly within small samples and the prevalence of their WAT use during the COVID-19 is unknown. We reported WAT use prevalence before and during the first wave of COVID-19 and examined social factors associated with WAT use frequency using a nationally representative sample of 3302 U.S. older adults. We used Multinomial Logistic Regression to identify social factors associated with WAT use frequency. Only 10.3% of pre-COVID-19 and 10.9% of first-wave subsamples were frequent WAT users. Older adults aged 75 and above and those with low incomes were less likely to frequently use WATs. Our findings suggest socioeconomic and age disparities in WAT use among older Americans. Future studies should focus on enhancing low-income older adults' WAT adoption to enable equal access to WAT-related health benefits.

Ultra-high-resolution mapping of ambient fine particulate matter to estimate human exposure in Beijing.

With the decreasing regional-transported levels, the health risk assessment derived from fine particulate matter (PM2.5) has become insufficient to reflect the contribution of local source heterogeneity to the exposure differences. Here, we combined the both ultra-high-resolution PM2.5 concentration with population distribution to provide the personal daily PM2.5 internal dose considering the indoor/outdoor exposure difference. A 30-m PM2.5 assimilating method was developed fusing multiple auxiliary predictors, achieving higher accuracy (R2 = 0.78-0.82) than the chemical transport model outputs without any post-simulation data-oriented enhancement (R2 = 0.31-0.64). Weekly difference was identified from hourly mobile signaling data in 30-m resolution population distribution. The population-weighted ambient PM2.5 concentrations range among districts but fail to reflect exposure differences. Derived from the indoor/outdoor ratio, the average indoor PM2.5 concentration was 26.5 µg/m3. The internal dose based on the assimilated indoor/outdoor PM2.5 concentration shows high exposure diversity among sub-groups, and the attributed mortality increased by 24.0% than the coarser unassimilated model.

Reconstructing Spatial Transcriptomics at the Single-cell Resolution with BayesDeep.

Spatially resolved transcriptomics (SRT) techniques have revolutionized the characterization of molecular profiles while preserving spatial and morphological context. However, most next-generation sequencing-based SRT techniques are limited to measuring gene expression in a confined array of spots, capturing only a fraction of the spatial domain. Typically, these spots encompass gene expression from a few to hundreds of cells, underscoring a critical need for more detailed, single-cell resolution SRT data to enhance our understanding of biological functions within the tissue context. Addressing this challenge, we introduce BayesDeep, a novel Bayesian hierarchical model that leverages cellular morphological data from histology images, commonly paired with SRT data, to reconstruct SRT data at the single-cell resolution. BayesDeep effectively model count data from SRT studies via a negative binomial regression model. This model incorporates explanatory variables such as cell types and nuclei-shape information for each cell extracted from the paired histology image. A feature selection scheme is integrated to examine the association between the morphological and molecular profiles, thereby improving the model robustness. We applied BayesDeep to two real SRT datasets, successfully demonstrating its capability to reconstruct SRT data at the single-cell resolution. This advancement not only yields new biological insights but also significantly enhances various downstream analyses, such as pseudotime and cell-cell communication.

Quorum sensing N-acyl homoserine lactones-SdiA enhances the biofilm formation of E. coli by regulating sRNA CsrB expression.

As an important virulence phenotype of Escherichia coli, the regulation mechanism of biofilm by non-coding RNA and quorum sensing system has not been clarified. Here, by transcriptome sequencing and RT-PCR analysis, we found CsrB, a non-coding RNA of the carbon storage regulation system, was positively regulated by the LuxR protein SdiA. Furthermore, ß-galactosidase reporter assays showed that SdiA enhanced promoter transcriptional activity of csrB. The consistent dynamic expression levels of SdiA and CsrB during Escherichia coli growth were also detected. Moreover, curli assays and biofilm assays showed sdiA deficiency in Escherichia coli SM10λπ or BW25113 led to a decreased formation of biofilm, and was significantly restored by over-expression of CsrB. Interestingly, the regulations of SdiA on CsrB in biofilm formation were enhanced by quorum sensing signal molecules AHLs. In conclusion, SdiA plays a crucial role in Escherichia coli biofilm formation by regulating the expression of non-coding RNA CsrB. Our study provides new insights into SdiA-non-coding RNA regulatory network involved in Escherichia coli biofilm formation.

Imaging cellular forces with photonic crystals.

Current techniques for visualizing and quantifying cellular forces have limitations in live cell imaging, throughput, and multi-scale analysis, which impede progress in cell force research and its practical applications. We developed a photonic crystal cellular force microscopy (PCCFM) to image vertical cell forces over a wide field of view (1.3 mm ⨯ 1.0 mm, a 10 ⨯ objective image) at high speed (about 20 frames per second) without references. The photonic crystal hydrogel substrate (PCS) converts micro-nano deformations into perceivable color changes, enabling in situ visualization and quantification of tiny vertical cell forces with high throughput. It enabled long-term, cross-scale monitoring from subcellular focal adhesions to tissue-level cell sheets and aggregates.

Life Space and Activity Space Measurement: Making 'Room' for Structural Racism.

As we age, the ability to move is foundational to health. Life space is one measure of a person's ability to move and engage in activity beyond the home. A separate but related concept is activity space, a measurement of a person's spatial behaviors and visited locations that include social networks, neighborhoods, and institutions. In this article, we integrate the literature on life space and activity space discussing how physical function is not only determined by individual capabilities, but also by the surrounding social and environmental factors which may limit their agency. We show how structural racism contributes to inequities within this paradigm linking related concepts of movement, agency, belonging, and timing. We also explore implications for research and theory for mobility, social connection, and activity.

Molecular epidemiology and genomic dynamics of Pseudomonas aeruginosa isolates causing relapse infections.

Pseudomonas aeruginosa (P. aeruginosa) is one of the leading causes of chronic infections, including reinfection, relapse, and persistent infection, especially in cystic fibrosis patients. Relapse P. aeruginosa infections are more harmful because of repeated hospitalization and undertreatment of antimicrobials. However, relapse P. aeruginosa infection in China remains largely unknown. Herein, we performed a 3-year retrospective study from 2019 to 2022 in a tertiary hospital, which included 442 P. aeruginosa isolates from 196 patients. Relapse infection was identified by screening clinical records and whole-genome sequencing (WGS). We found that 31.6% (62/196) of patients had relapsed infections. The relapse incidence of carbapenem-resistant P. aeruginosa infection (51.4%) is significantly higher than that of carbapenem-susceptible P. aeruginosa infection (20.2%, P < 0.0001). These isolates were assigned to 50 distinct sequence types and sporadically distributed in phylogeny, indicating that relapsed infections were not caused by certain lineages. Fast adaptation and evolution of P. aeruginosa isolates were reflected by dynamic changes of antimicrobial resistance, gene loss and acquisition, and single-nucleotide polymorphisms during relapse episodes. Remarkably, a convergent non-synonymous mutation that occurs in a pyochelin-associated virulence gene fptA (T1056C, M252T) could be a considerable target for the diagnosis and treatment of relapse P. aeruginosa infection. These findings suggest that integrated utilization of WGS and medical records provides opportunities for improved diagnostics of relapsed infections. Continued surveillance of the genomic dynamics of relapse P. aeruginosa infection will generate further knowledge for optimizing treatment and prevention in the future.IMPORTANCEPseudomonas aeruginosa is a predominant pathogen that causes various chronic infections. Relapse infections promote the adaptation and evolution of antimicrobial resistance and virulence of P. aeruginosa, which obscure evolutionary trends and complicate infection management. We observed a high incidence of relapse P. aeruginosa infection in this study. Whole-genome sequencing (WGS) revealed that relapse infections were not caused by certain lineages of P. aeruginosa isolates. Genomic dynamics of relapse P. aeruginosa among early and later stages reflected a plasticity scattered through the entire genome and fast adaptation and genomic evolution in different ways. Remarkably, a convergent evolution was found in a significant virulence gene fptA, which could be a considerable target for diagnosis and treatment. Taken together, our findings highlight the importance of longitudinal surveillance of relapse P. aeruginosa infection in China since cystic fibrosis is rare in Chinese. Integrated utilization of WGS and medical records provides opportunities for improved diagnostics of relapse infections.

Artificial intelligence in mental healthcare: an overview and future perspectives.

Artificial intelligence is disrupting the field of mental healthcare through applications in computational psychiatry, which leverages quantitative techniques to inform our understanding, detection, and treatment of mental illnesses. This paper provides an overview of artificial intelligence technologies in modern mental healthcare and surveys recent advances made by researchers, focusing on the nascent field of digital psychiatry. We also consider the ethical implications of artificial intelligence playing a greater role in mental healthcare.