Miracle-dz/UniFAR-FTUs huggingface dataset:
STAIG: Spatial Transcriptomics Analysis via Image-Aided Graph Contrastive Learning for Domain Exploration and Alignment-Free Integration

Spatial transcriptomics is an essential application for investigating cellular structures and interactions and requires multimodal information to precisely study spatial domains. Here, we propose STAIG, a novel deep-learning model that integrates gene expression, spatial coordinates, and histological images using graph-contrastive learning coupled with high-performance feature extraction. STAIG can integrate tissue slices without prealignment and remove batch effects. Moreover, it was designed to accept data acquired from various platforms, with or without histological images. By performing extensive benchmarks, we demonstrated the capability of STAIG to recognize spatial regions with high precision and uncover new insights into tumor microenvironments, highlighting its promising potential in deciphering spatial biological intricates.
Restore or retreat? saltwater intrusion and water management in coastal wetlands

Abstract Coastal wetlands perform a unique set of physical, chemical, and biological functions, which provide billions of dollars of ecosystem services annually. These wetlands also face myriad environmental and anthropogenic pressures, which threaten their ecological condition and undermine their capacity to provide these services. Coastal wetlands have adapted to a dynamic range of natural disturbances over recent millennia, but face growing pressures from human population growth and coastal development. These anthropogenic pressures are driving saltwater intrusion () in many coastal systems. The position of coastal wetlands at the terrestrial–marine interface also makes them vulnerable to increasing rates of sea‐level rise and changing climate. Critically, anthropogenic and natural stressors to coastal wetlands can act synergistically to create negative, and sometimes catastrophic, consequences for both human and natural systems. This review focused on the drivers and impacts of in coastal wetlands and has two goals: (1) to synthesize understanding of coastal wetland change driven by and (2) to review approaches for improved water management to mitigate in impacted systems. While we frame this review as a choice between restoration and retreat, we acknowledge that choices about coastal wetland management are context‐specific and may be confounded by competing management goals. In this setting, the choice between restoration and retreat can be prioritized by identifying where the greatest return in ecosystem services can be achieved relative to restoration dollars invested. We conclude that restoration and proactive water management is feasible in many impacted systems.
Lysosomal TBK1 Responds to Amino Acid Availability to Relieve Rab7-Dependent mTORC1 Inhibition

Lysosomes play a pivotal role in coordinating macromolecule degradation and regulating cell growth and metabolism. Despite substantial progress in identifying lysosomal signaling proteins, understanding the pathways that synchronize lysosome functions with changing cellular demands remains incomplete. This study uncovers a role for TANK-binding kinase 1 (TBK1), well known for its role in innate immunity and organelle quality control, in modulating lysosomal responsiveness to nutrients. Specifically, we identify a pool of TBK1 that is recruited to lysosomes in response to elevated amino acid levels. At lysosomes, this TBK1 phosphorylates Rab7 on serine 72. This is critical for alleviating Rab7-mediated inhibition of amino acid-dependent mTORC1 activation. Furthermore, a TBK1 mutant (E696K) associated with amyotrophic lateral sclerosis and frontotemporal dementia constitutively accumulates at lysosomes, resulting in elevated Rab7 phosphorylation and increased mTORC1 activation. This data establishes the lysosome as a site of amino acid regulated TBK1 signaling that is crucial for efficient mTORC1 activation. This lysosomal pool of TBK1 has broader implications for lysosome homeostasis, and its dysregulation could contribute to the pathogenesis of ALS-FTD.
Action history and target uncertainty co-determine human reaching direction under time pressure

Given the inaccuracies that are inherent in biological sensory and motor functions, animal sensorimotor control should be probabilistic. Effective neural control systems for movement must estimate the most likely true state of the world on the basis of uncertain sensory information, and to select and execute movements that are most likely to be successful given motor variability. Bayesian inference dictates that if sensory information is ambiguous (e.g. low light conditions), animals should rely more on their past experience of target locations to guide motor planning, and less on their current sensory information about target location. Here we investigated how time pressure affects degree to which the precision of sensory information about a target influences movement direction bias towards previous target locations. We used a paradigm developed by Dekleva et al. (2016) that involved uncertain cues to the location of a hidden target for reaching with movement preparation time strictly controlled. One group of participants (n=10) were required to initiate their reaches within 150-300ms of target presentation, and a second group (n=10) were required to initiate their reaches with 1150-1300ms of target presentation. We found that participants relied more on prior target location information when target precision was reduced under time pressure, which suggests that integration of target uncertainty information according to Bayesian principles is an inherent component of sensorimotor transformation and does not require time-consuming cognitive processes.
The effect of variable inertial resistance on force, velocity, power and muscle activation during a chest press exercise

This study investigated the effect of the inertial component of the resistance (INERTIA) at different intensity levels (LOAD ) on force (FORCE ), velocity (VELOCITY ), power (POWER), and the muscle activity of the pectoralis major (EMGPM), anterior deltoid (EMGDA) and triceps brachii (EMGTB) muscles during a chest press exercise. A motor-driven exercise apparatus was programmed to offer resistance with different inertial profiles over the range of movement (ROM ): gravitational-type constant inertia (IFULL); no-inertia (IZERO); linearly descending inertia along the ROM (IVAR). Nine healthy adults performed five, maximal-effort, explosive movements with each inertial profile at 30, 50 and 70% of their 1 repetition maximum. Meanwhile, the EMGPM, EMGDA and EMGTB signals were obtained jointly with the FORCE, VELOCITY and POWER readings returned by the exercise apparatus. One-dimensional statistical non-parametric maps based on 2-way repeated measures ANOVA (SnPM ) were employed to evaluate the effect of LOAD and INERTIA on the collected timeseries. Paired t-tests were then used as post-hoc tests on the portions of the ROM denoting significant differences in the SnPM. Higher LOAD resulted in elevated outcomes over large portions of the ROM in all the investigated timeseries. Compared to IFULL, IZERO allowed greater VELOCITY at the cost of lower FORCE throughout the ROM, while IVAR, despite the lower VELOCITY than IZERO, resulted in higher FORCE and POWER output. In addition, IZERO and IVAR elevated EMGTB at the end of the ROM with respect to IFULL. IVAR overcame both IFULL and IZERO in terms of FORCE and POWER, which indicates that variable inertial profiles might be effectively integrated into resistance exercise programs. Ultimately, this study suggested that INERTIA acts independently to the imposed LOAD on the FORCE, VELOCITY and POWER production. Coaches and therapists are encouraged to account for the type of INERTIA as one of the parameters considered during the exercise selection for their athletes or patients.
Ca2+ Oscillation in Vascular Smooth Muscle Cells Control Myogenic Spontaneous Vasomotion and Counteract Post-ischemic No-reflow

Ischemic stroke produces the highest adult disability. Despite successful recanalization, no-reflow, or the futile restoration of the cerebral perfusion after ischemia, is a major cause of brain lesion expansion. However, the vascular mechanism underlying this hypoperfusion is largely unknown, and no approach is available to actively promote optimal reperfusion to treat no-reflow. Here, by combining two-photon laser scanning microscopy (2PLSM) and a mouse middle cerebral arteriolar occlusion (MCAO) model, we found myogenic vasomotion deficits correlated with post-ischemic cerebral circulation interruptions and no-reflow. Transient occlusion-induced transient loss of mitochondrial membrane potential (ΔΨm) permanently impaired mitochondria-endoplasmic reticulum (ER) contacts and abolished Ca2+ oscillation in smooth muscle cells (SMCs), the driving force of myogenic spontaneous vasomotion. Furthermore, tethering mitochondria and ER by specific overexpression of ME-Linker in SMCs restored cytosolic Ca2+ homeostasis, remotivated myogenic spontaneous vasomotion, achieved optimal reperfusion, and ameliorated neurological injury. Collectively, the maintaining of arteriolar myogenic vasomotion and mitochondria-ER contacts in SMCs, are of critical importance in preventing post-ischemic no-reflow.
Diverging roles of TRPV1 and TRPM2 in warm-temperature detection

The accurate perception of innocuous temperatures, particularly those experienced as pleasantly warm, is essential for achieving thermal comfort and maintaining thermoregulatory balance. Warm-sensitive neurons (WSN) innervating the skin play a central role in non-painful warmth detection. The TRP ion channels TRPV1 and TRPM2 have been suggested as sensors of warm temperature in WSNs. However, the precise contribution of these channels to the process of warmth detection is not fully understood. A significant challenge in analysing WSNs lies in their scarcity: fewer than 10 % of sensory neurons in the rodent dorsal root ganglion (DRG) respond to innocuous warm temperatures. In this study, we examined >20,000 cultured mouse DRG neurons using calcium imaging and discovered distinct contributions of TRPV1 and TRPM2 to warm-temperature sensitivity. TRPV1 and TRPM2 affect the abundance of WSNs, with TRPV1 mediating the rapid, dynamic response to warmth. By carefully tracking animal movement in a whole-body thermal preference paradigm, we observe that these cellular differences correlate with nuanced thermal behaviours. Utilizing a driftdiffusion model to quantitatively analyse the decision-making process of animals exposed to different environmental temperatures, we found that: TRPV1 primarily impairs the precision of evidence accumulation, whereas TRPM2 significantly increases the total duration of exposure to uncomfortably warm environments. Our findings provide valuable insights into the distinct molecular responses to warmth stimuli, and underpin the subtle aspects of thermal decision-making when encountering minor temperature variations.
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 energybased 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.
The association of longitudinal diet and waist-to-hip ratio from midlife to old age with hippocampus connectivity and memory in old age: a cohort study

Epidemiological studies suggest lifestyle factors may reduce the risk of dementia. However, few studies have examined the association of diet and waist-to-hip ratio with hippocampus connectivity. In the Whitehall II Imaging Sub-study, we examined longitudinal changes in diet quality in 512 participants and waist-to-hip ratio in 665 participants. Diet quality was measured using the Alternative Health Eating Index-2010 assessed three times across 11 years between ages 48 and 60 years, and waist-to-hip ratio five times over 21 years between ages 48 and 68 years. Brain imaging and cognitive tests were performed at age 70±5 years. We measured white matter using diffusion tensor imaging and hippocampal functional connectivity using resting-state functional magnetic resonance imaging. In addition to associations of diet and waist-to-hip ratio with brain imaging measures, we tested whether associations between diet, waist-to-hip ratio and cognitive performance were mediated by brain connectivity. We found better diet quality in midlife and improvements in diet over mid-to-late life were associated with higher hippocampal functional connectivity to the occipital lobe and cerebellum, and better white matter integrity as measured by higher fractional anisotropy and lower diffusivity. Higher waist-to-hip ratio in midlife was associated with higher mean and radial diffusivity and lower fractional anisotropy in several tracts including the inferior longitudinal fasciculus and cingulum. Associations between midlife waist-to-hip ratio, working memory and executive function were partially mediated by radial diffusivity. All associations were independent of age, sex, education, and physical activity. Our findings highlight the importance of maintaining a good diet and a healthy waist-to-hip ratio in midlife to maintain brain health in later life. Future interventional studies for the improvement of dietary and metabolic health should target midlife for the prevention of cognitive decline in old age.
Identifying factors contributing to social vulnerability through a deliberative Q-Sort process: an application to heat vulnerability in Taiwan

Extreme heat events are gaining ever more policy and societal attention under a warming climate. Although a breadth of expertises are required to understand drivers of vulnerability to hazards such as extreme heat, it is also acknowledged that expert assessments in group settings may be subject to biases and uneven power relations. In this Technical Note, we outline a structured deliberative process for supporting experts to work collaboratively to assess social vulnerability to a climate-related hazard, in this case extreme heat in Taiwanese cities. We argue that adapting elicitation approaches such as Q-Methodology for use in collaborative settings can help to organise expert discussion and enable dialogue and mutual learning, in a way that supports consensus-building on vulnerability assessment. Outcomes from our collaborative assessments suggest elderly people living alone, elderly people over 75, pre-existing circulatory diseases and level of participation in community decision-making may all be notable drivers of heat vulnerability in the Taiwanese context. Methodologically, we argue that collaborative sorting exercises offer a way to embed local and experiential knowledges into assessments of available evidence, but that strong facilitation and additional checks are necessary to ensure an inclusive process that reflects the diversity of perspectives involved.
Influence of peer mentorship on nursing education and student attrition

Peer mentoring is the exchange of skills or knowledge from a more experienced individual to a novice in the same field. Due to the constraints placed on nursing education, many students struggle to complete the nursing curriculum. This leads to high attrition rates within colleges of nursing. Without maximizing graduate rates, the current nursing shortage is exacerbated. This integrated literature review examines the impact of more experienced nursing students mentoring their junior peers. With implementation of peer mentoring attrition rates were reduced. Additionally, the research showed that mentees experienced an enhanced feeling of support and were able to learn more efficiently. Mentors benefited from the arrangement with enhanced leadership and teaching abilities. Instructors of nursing programs also benefited from the arrangement by having decreased demand for review sessions, which could be taken over by the mentors, and could focus on enhancing their lessons or other educational obligations.
Impact of Weather Patterns and Meteorological Factors on PM 2.5 and O 3 during the Covid-19 Lockdown in China

The abnormal haze event in NCP (North China Plain) and the decline in ozone levels in SC (Southern China) from 21 st January to 9 th February 2020 have attracted public curiosity and scholarly attention during the COVID-19 lockdown. Most 10 previous studies focused on the impact of atmospheric chemistry processes associated with anomalous weather elements in these cases, but fewer studies quantified the impact of various weather elements within the context of a specific weather pattern. To identify the weather patterns responsible for inducing this unexpected situation and to further quantify the importance of different meteorological factors during the haze event, two scenarios are employed. These scenarios compared observations to climatology averaged over the years 2015-2019 and the ‘Business As Usual’ (hereafter referred to as BAU) emission strength, 15 using a novel structural SOM (Self-Organising Map) and ML (Machine Learning) models. The results reveal that the unexpected PM 2.5 pollution and O 3 decline from the climatology in NCP, North East China (NEC), and SC could be effectively explained by the presence of a double-centre high-pressure system. Moreover, the ML results provided a quantitative assessment of the importance of each meteorological factor in driving the predictions of PM 2.5 and O 3 under the specific weather system. These results indicate that temperature played the most crucial role in the haze event in NCP and NEC, as well as in 20 the O 3 decline in SC. This valuable information will ultimately contribute to our ability to predict air pollution under future emission scenarios and changing weather patterns that may be influenced by climate change
Impact of Human Activities on Rainwater Quality in South-South Region of Nigeria

The first three spills of rainfall in 2016 were harvested from areas impacted by gas flaring and exhaust emissions namely: Ibeno, Eket, Onna, Mkpat Enin and Uyo local government areas south-south of Nigeria. Control samples were harvested from Ibiono Ibom local government area where anthropogenic source of air contaminants is negligible. These samples and Control were treated and analysed using standard procedures for their pH, electrical conductivity, turbidity, nitrate, total suspended solids, total dissolved solids, Fe, Zn, Cu, Pb, Cd and Ni levels. Mean concentrations of all parameters assessed in studied rainwater were higher than their corresponding levels in the Control revealing anthropogenic inputs of these properties in the ambient air. Mean concentration of all properties determined except those of pH, Fe, Pb, Cd and Ni were within their acceptable limits. Consequently, rainwater harvested from studied areas should be treated before consumption to avoid health implications associated with acidity, Fe, Pb, Cd and Ni. This study has also shown that, human activities executed within studied areas impacted negatively on the quality of rainwater harvested. All the parameters examined exhibited strong association and common source in ambient air except pH with strong negative correlation with all the properties.
Particle phase state and aerosol liquid water greatly impact secondary aerosol formation: insights into phase transition and its role in haze events

Abstract. The particle phase state is crucial for reactive gas uptake, heterogeneous, and multiphase chemical reactions, thereby impacting secondary aerosol formation. This study provides valuable insights into the significance of particle-phase transition and aerosol liquid water (ALW) in particle mass growth during winter. Our findings reveal that particles predominantly exist in a semi-solid or solid state during clean winter days with ambient relative humidity (RH) below 30 %. However, a non-liquid to liquid phase transition occurs when the ALW mass fraction exceeds 15 % (dry mass) at transition RH thresholds of 40 %–60 %. During haze episodes, the transformation rates of sulfate and nitrate aerosols rapidly increase through phase transition and increased ALW by 48 % and 11 %, respectively, resulting in noticeable increases in secondary inorganic aerosols (SIA). The presence of abundant ALW, favored by elevated RH and higher proportion of SIA, facilitates the partitioning of water-soluble compounds from the gas to the particle phase, as well as heterogeneous and aqueous processes in liquid particles. This leads to a substantial increase in the formation of secondary organic aerosols and elevated aerosol oxidation. Consequently, the overall hygroscopicity parameters exhibit a substantial enhancement, with a mean value of 23 %. These results highlight phase transition as a key factor initiating the positive feedback loops between ALW and secondary aerosol formation during haze episodes over the North China Plain. Accurate predictions of secondary aerosol formation necessitate explicit consideration of the particle phase state in chemical transport models.