Browse Articles

Learning reshapes the hippocampal representation hierarchy

A key feature of biological and artificial neural networks is the progressive refinement of their neural representations with experience. In neuroscience, this fact has inspired several recent studies in sensory and motor systems. However, less is known about how higher associational cortical areas, such as the hippocampus, modify representations throughout the learning of complex tasks. Here, we focus on associative learning, a process that requires forming a connection between the representations of different variables for appropriate behavioral response. We trained rats in a space-context associative task and monitored hippocampal neural activity throughout the entire learning period, over several days. This allowed us to assess changes in the representations of context, movement direction, and position, as well as their relationship to behavior. We identified a hierarchical representational structure in the encoding of these three task variables that was preserved throughout learning. Nevertheless, we also observed changes at the lower levels of the hierarchy where context was encoded. These changes were local in neural activity space and restricted to physical positions where context identification was necessary for correct decision-making, supporting better context decoding and contextual code compression. Our results demonstrate that the hippocampal code not only accommodates hierarchical relationships between different variables but also enables efficient learning through minimal changes in neural activity space. Beyond the hippocampus, our work reveals a representation learning mechanism that might be implemented in other biological and artificial networks performing similar tasks.

Retraction: Impact of donors’ financial fairness perception on donation intention in nonprofit organizations after COVID-19 outbreak

Transfer learning for securing electric vehicle charging infrastructure from cyber-physical attacks

Astrocytes in the mouse brain respond bilaterally to unilateral retinal neurodegeneration

Glaucomatous optic neuropathy, or glaucoma, is the world’s primary cause of irreversible blindness. Glaucoma is comorbid with other neurodegenerative diseases, but how it might impact the environment of the full central nervous system to increase neurodegenerative vulnerability is unknown. Two neurodegenerative events occur early in the optic nerve, the structural link between the retina and brain: loss of anterograde transport in retinal ganglion cell (RGC) axons and early alterations in astrocyte structure and function. Here, we used whole-mount tissue clearing of full mouse brains to image RGC anterograde transport function and astrocyte responses across retinorecipient regions early in a unilateral microbead occlusion model of glaucoma. Using light sheet imaging, we found that RGC projections terminating specifically in the accessory optic tract are the first to lose transport function. Although degeneration was induced in one retina, astrocytes in both brain hemispheres responded to transport loss in a retinotopic pattern that mirrored the degenerating RGCs. A subpopulation of these astrocytes in contact with large descending blood vessels were immunopositive for LCN2, a marker associated with astrocyte reactivity. Together, these data suggest that even early stages of unilateral glaucoma have broad impacts on the health of astrocytes across both hemispheres of the brain, implying a glial mechanism behind neurodegenerative comorbidity in glaucoma.

Neural correlates of the uncanny valley effect for robots and hyper-realistic masks

Viewing artificial objects and images that are designed to appear human can elicit a sense of unease, referred to as the ‘uncanny valley’ effect. Here we investigate neural correlates of the uncanny valley, using still images of androids (robots designed to look human), and humans wearing hyper-realistic silicone masks, as well as still images of real humans, in two experiments. In both experiments, human-like stimuli were harder to distinguish from real human faces than stimuli that were clearly not designed to mimic humans but contain facial features (mechanical robots and Halloween masks). Stimulus evoked potentials (electromagnetic brain responses) did not show convincing differences between faces and either androids or realistic masks when using traditional univariate statistical tests. However, a more sensitive multivariate analysis identified two regions of above-chance decoding, indicating neural differences in the response between human faces and androids/realistic masks. The first time window was around 100–200 ms post stimulus onset, and most likely corresponds to low-level image differences between conditions. The second time window was around 600 ms post stimulus onset, and may reflect top-down processing, and may correspond to the subjective sense of unease characteristic of the uncanny valley effect. Objective neural components might be used in future to rapidly train generative artificial intelligence systems to produce more realistic images that are perceived as natural by human observers.

Electrocardiogram analysis for cardiac arrhythmia classification and prediction through self attention based auto encoder

The SUbventral-Gland Regulator (SUGR-1) of nematode virulence

Pathogens must precisely tailor their gene expression to cause infection. However, a signaling cascade from host signal to effector production has remained elusive for metazoan pathogens. Here, we show that plants contain molecular signals, termed effectostimulins, that activate the first identified regulator of plant-parasitic nematode effectors. SUGR-1 directly binds effector promoters, and is central to a transcriptional network that activates 58 effector genes. Importantly, we demonstrate that downregulation of sugr-1 inhibits parasitism, underlining SUGR-1 signaling as a valuable target for crop protection and food security. This, in the wider context of nematodes as parasites of humans and other animals, has scope for potentially broader impact: Disrupting effector production could, in principle, be applied to any pathogen that secrets effectors.

Evaluation of community pharmacists’ knowledge and attitude about Hajj and Umrah-related health conditions in the western region, Saudi Arabia: A cross-sectional study

Background During the Hajj and Umrah seasons in Saudi Arabia, pilgrims tend to experience a higher frequency of various health conditions. Respiratory infections, gastrointestinal infections, and food poisoning are among the most prevalent ailments. To address these health concerns, community pharmacists (CPs) have developed standardized treatment protocols. Pharmacists’ skills in medication dispensing, health consultations, and preventive care enhance pilgrims’ well-being in challenging pilgrimage settings. Aims The objective of this study was to investigate the knowledge and attitude of CPs towards health conditions related to Hajj and Umrah in the Western Region of Saudi Arabia where the Hajj and Umrah are taking place. Methods Between March and April 2023, an online cross-sectional study using Google form was carried out among CPs who work in the western region of Saudi Arabia. The study made use of a self-administered questionnaire consisting of four sections that aimed to obtain information about the CPs’ knowledge and attitudes towards health conditions related to Hajj and Umrah. Data analysis was conducted using the Statistical Package for the Social Sciences version 26 (SPSS). Result A total of 496 CPs completed and returned the questionnaire, by giving a response rate of 99.2% (n = 500). Among them, 55.1% were aware of the necessary vaccines for Hajj and Umrah. Approximately 46.6% of CPs provided health-related advice to pilgrims. The most common health conditions experienced by pilgrims were diarrhea (59.5%), followed by flu and cough (58%), gastrointestinal diseases (39.4%), food poisoning (33.6%), viral fever, and heat stroke (24.4%). Regarding attitudes towards vaccination, 55.3% of CPs agreed that vaccination is safe for pilgrims aged 65 years and above, and 65.7% agreed that vaccination can help reduce medical costs during Hajj and Umrah seasons. Additionally, 61.1% of CPs recommended updating immunization against vaccine-preventable diseases for all travelers to ensure a safe Hajj and Umrah. The overall mean knowledge of CPs regarding vaccination during Hajj and Umrah was 4.739(2.49) (median = 5; Range = 0-9). However, 56.7% of CPs demonstrated good knowledge, while 43.3% reported poor knowledge regarding vaccination during Hajj and Umrah. Conclusion The community pharmacists (CPs) in the Mecca region were found to have good knowledge, with more than half of them having positive attitudes about vaccination for Hajj and Umrah-related health conditions. It is crucial to enhance the knowledge and attitudes of CPs to provide better care and participate in reliable and supportive healthcare and counseling sessions for managing various health infections.

Cavity nesting birds show behavioural plasticity to simulated territorial intrusions in response to natural resource pulses

Abstract We investigated the impact of two natural pulses (food and nesting resources) on intra- and inter-specific territorial behaviour of species that co-occur year-round in multi-species groups. We simulated conspecific and heterospecific territorial intrusions in two cavity-nesting species using 974 model presentations with territorial song playbacks during and after a dual resource pulse of insect (bark beetle) prey and nest cavities across 5 years in British Columbia, Canada. As beetle abundance increased, both species increased aggression toward conspecific intruders. At peak beetle abundance the (typically) subordinate generalist insectivore, mountain chickadee (Poecile gambeli), attacked model intruders more frequently than did the dominant bark insectivore, red-breasted nuthatch (Sitta canadensis), and responded more aggressively to nuthatch intruders than to conspecifics. The reversal in the inter-specific dominance hierarchy suggests that behavioural mechanisms governing community structure may change during resource pulses. Overall, we suggest that social interactions between chickadees and nuthatches are dynamic with high complexity and flexibility to major ecological changes. Future work that examines the fitness consequences of temporal variation in community dynamics and resiliency could help to reveal evolutionary mechanisms by which these species co-exist.

Neanderthal adaptive introgression shaped <i>LCT</i> enhancer region diversity without linking to lactase persistence in East Asian populations

Positive selection at the 2q21.3 enhancer region for lactase gene ( LCT ) expression in Europeans and Africans has long been attributed to selection for lactase persistence (LP), the capacity of adults to digest lactose in milk, presumably because of the benefits associated with milk consumption. While considered a classic example of gene–culture coevolution, recently doubts have been raised about the link between selection at 2q21.3 and LP. Analysis of additional populations could shed further light; here, we demonstrate that a haplotype spanning ~467 kb at the 2q21.3 locus has risen to high frequency in East Asians (~25%) but is absent from Africans and Europeans. This haplotype likely derived from Neanderthals and has been under positive selection in East Asians. The East Asian–specific haplotype is associated with alterations in LCT expression and promoter methylation in certain cell types, similar to what is observed with LP-associated haplotypes in Europeans. Moreover, its frequency is comparable to that of LP in East Asians, suggesting a potential association with LP in East Asians. However, it is highly unlikely that selection in East Asians was related to milk-drinking habits. We find that this haplotype impacts the expression of UBXN4 , DARS1, and DARS1-AS1 in immune cells and is associated with neutrophil and white blood cell counts. Hence, the selection might be linked to certain aspects of immune function. This implies that selection on 2q21.3 has thus either occurred for different reasons in different populations or the selection observed in other populations is also not due to LP.

Access to lactation consult services during the COVID-19 pandemic and the impact on breastfeeding outcome variables

Background: Inpatient lactation consultation and social influences affect breastfeeding (BF) choices and sustainability. The COVID-19 pandemic introduced barriers to BF initiation and continuation including access to lactation support and social connection. Equitable access to lactation support can reduce health disparities. Research aim: The study aimed to (1) determine the prevalence of professional lactation support during the COVID-19 pandemic, (2) explore the influence of this pandemic on the equitable accessibility to lactation support services, and (3) identify changes in BF rates and access to lactation support at three different phases of the pandemic (early, middle, and late). Methods: Patients receiving prenatal care at a mid-sized academic medical institution in Central Pennsylvania were recruited and surveyed and this data was collected and combined with data from the electronic medical record. Results: 88% of patients received a lactation consultation during birth hospitalization. Having COVID-19 during pregnancy did not change access to lactation consultation post-partum (p = 0.0961). Neither BF exclusivity during the three phases of the pandemic nor the number of lactation consult visits were statistically different (p = 0.2263; p = 0.0958 respectively). Multiple regression models assessing BF exclusivity in the hospital found significant associations with having a lactation consult (OR 2.50, 95% CI 1.04, 6.04), having an infant in the neonatal intensive care unit (OR 0.29, 95% CI 0.11, 0.73), and having reported social support during pregnancy (OR 1.09, 95% CI 1.01,1.18). Conclusions: Social support during pregnancy and having a lactation consult visit during birth hospitalization remained critical factors for BF exclusivity. This study highlights the importance of having professional lactation support on both BF exclusivity and continuation during the COVID-19 pandemic.

Research on establishment decision of medical equipment measurement standard based on GDM-AHP

A global estimate of multiecosystem photosynthesis losses under microplastic pollution

Understanding how ecosystems respond to ubiquitous microplastic (MP) pollution is crucial for ensuring global food security. Here, we conduct a multiecosystem meta-analysis of 3,286 data points and reveal that MP exposure leads to a global reduction in photosynthesis of 7.05 to 12.12% in terrestrial plants, marine algae, and freshwater algae. These reductions align with those estimated by a constructed machine learning model using current MP pollution levels, showing that MP exposure reduces the chlorophyll content of photoautotrophs by 10.96 to 12.84%. Model estimates based on the identified MP-photosynthesis nexus indicate annual global losses of 4.11 to 13.52% (109.73 to 360.87 MT·y −1 ) for main crops and 0.31 to 7.24% (147.52 to 3415.11 MT C·y −1 ) for global aquatic net primary productivity induced by MPs. Under scenarios of efficient plastic mitigation, e.g., a ~13% global reduction in environmental MP levels, the MP-induced photosynthesis losses are estimated to decrease by ~30%, avoiding a global loss of 22.15 to 115.73 MT·y −1 in main crop production and 0.32 to 7.39 MT·y −1 in seafood production. These findings underscore the urgency of integrating plastic mitigation into global hunger and sustainability initiatives.

Longitudinal trajectories of muscle impairments in growing boys with Duchenne muscular dystrophy

Background Insights into the progression of muscle impairments in growing boys with Duchenne muscular dystrophy (DMD) remain incomplete due to the frequent oversight of normal maturation as a confounding factor, thereby restricting the delineation of sole pathological processes. Objective To establish longitudinal trajectories for a comprehensive integrated set of muscle impairments, including muscle weakness, contractures and muscle size alterations, while correcting for normal maturation, in DMD. Methods Thirty-three boys with DMD (aged 4.3–17 years) were included. Fixed dynamometry, goniometry, and 3D freehand ultrasound were used to repeatedly assess lower limb muscle strength, passive range of motion (ROM) and muscle size, resulting in 161, 178 and 64 assessments for the strength, ROM and ultrasound dataset, respectively. To account for natural strength development, ROM reduction, and muscle growth in growing children, muscle outcomes were converted to unit-less z-scores calculated in reference to typically developing (TD) peers. This allows the interpretation of the muscle outcomes as deficits or alterations with respect to TD. Mixed-effect models estimated the longitudinal change in muscle impairments. Results At 4.3–4.9 years of age, all muscle strength outcomes and several ROMs (i.e., dorsiflexion, hamstrings, and hip extension) showed deficits relative to TD, while m. medial gastrocnemius size was increased. Most muscle outcomes remained stable or slightly improved until the ages of 6.6–9.4 years (except knee flexion strength). After this period, muscle strength (−0.27 to −0.45 z-score/year; p &lt; 0.0044), dorsiflexion ROM (−0.23 to −0.33 z-score/year; p &lt; 0.0007), m. medial gastrocnemius size (−0.56 z-score/year; p = 0.0022), and m. rectus femoris size (−0.36 z-score/year; p = 0.0054) declined. Conclusions The current study established longitudinal trajectories of muscle impairments in boys with DMD. The results provided enriched history data and revealed promising outcome measures that could enhance the detection of the efficacy of novel therapeutic strategies. Future studies are necessary to validate these outcomes.

Association between air pollution exposure and lower urinary tract symptoms in Korean men

How nidoviruses evolved the largest known RNA genomes

Identifying healthcare needs with patient experience reviews using ChatGPT

Background Valuable findings can be obtained through data mining in patients’ online reviews. Also identifying healthcare needs from the patient’s perspective can more accurately improve the quality of care and the experience of the visit. Thereby avoiding unnecessary waste of health care resources. The large language model (LLM) can be a promising tool due to research that demonstrates its outstanding performance and potential in directions such as data mining, healthcare management, and more. Objective We aim to propose a methodology to address this problem, specifically, the recent breakthrough of LLM can be leveraged for effectively understanding healthcare needs from patient experience reviews. Methods We used 504,198 reviews collected from a large online medical platform, haodf.com. We used the reviews to create Aspect Based Sentiment Analysis (ABSA) templates, which categorized patient reviews into three categories, reflecting the areas of concern of patients. With the introduction of thought chains, we embedded ABSA templates into the prompts for ChatGPT, which was then used to identify patient needs. Results Our method has a weighted total precision of 0.944, which was outstanding compared to the direct narrative tasks in ChatGPT-4o, which have a weighted total precision of 0.890. Weighted total recall and F1 scores also reached 0.884 and 0.912 respectively, surpassing the 0.802 and 0.843 scores for “direct narratives in ChatGPT.” Finally, the accuracy of the three sampling methods was 91.8%, 91.7%, and 91.2%, with an average accuracy of over 91.5%. Conclusions Combining ChatGPT with ABSA templates can achieve satisfactory results in analyzing patient reviews. As our work applies to other LLMs, we shed light on understanding the demands of patients and health consumers with novel models, which can contribute to the agenda of enhancing patient experience and better healthcare resource allocations effectively.

The associations between the FAGR and all-cause and cardiovascular mortality in patients with STEMI

Abstract Although the fibrinogen-to-albumin-to-globulin ratio (FAGR) has been proven to be related to coronary artery disease (CAD), the association between the FAGR and acute ST-segment elevation myocardial infarction (STEMI) has not been adequately investigated. This study aimed to evaluate the prognostic potential of the FAGR for STEMI. A total of 1042 patients with STEMI after emergency PCI admitted to the First Affiliated Hospital of Kunming Medical University from June 2018 to January 2023 were enrolled in the study. Patients were divided into a low FAGR group and a high FAGR group according to the median FAGR (2.44). We used Kaplan–Meier plots, restricted cubic spline regression, Cox survival analyses and time-dependent ROC analyses to explore the predictive value of the FAGR for all-cause and cardiovascular mortality. Kaplan‒Meier analysis revealed that the cumulative incidence rates of all-cause and cardiovascular mortality in patients with STEMI were greater in the high FAGR group. Multivariate Cox proportional hazard analysis revealed that the FAGR was an independent predictor of both all-cause and cardiovascular death. In terms of the prediction of all-cause mortality, the FAGR had an area under the ROC curve of 0.720, which was better than that for fibrinogen (AUC = 0.687). In terms of the prediction of cardiovascular mortality, the area under the ROC curve for the FAGR was 0.726, which was also better than that for Fib (AUC = 0.698). The present results suggest that the FAGR may serve as a potential prognostic indicator in patients with STEMI after emergency PCI.

Antibody reactivity against EBNA1 and GlialCAM differentiates multiple sclerosis patients from healthy controls

Multiple sclerosis (MS) is an autoimmune demyelinating disorder of the central nervous system (CNS), which is linked to Epstein–Barr virus (EBV) infection, preceding the disease. The molecular mechanisms underlying this connection are only partially understood. We previously described molecular mimicry between the EBV transcription factor EBV nuclear antigen 1 (EBNA1) and three human CNS proteins: anoctamin-2 (ANO2), alpha-B crystallin (CRYAB), and glial cellular adhesion molecule (GlialCAM). Here, we investigated antibody responses against EBNA1 and GlialCAM in a large cohort of 650 MS patients and 661 matched population controls and compared them to responses against CRYAB and ANO2. We confirmed that elevated IgG responses against EBNA1 and all three CNS-mimic antigens associate with increased MS risk. Blocking experiments confirmed the presence of cross-reactive antibodies and molecular mimicry between EBNA1 and GlialCAM, and accompanying antibody responses against adjacent peptide regions of GlialCAM suggest epitope spreading. Antibody responses against EBNA1, GlialCAM, CRYAB, and ANO2 are elevated in MS patients carrying the main risk allele HLA-DRB1*15:01, and combinations of HLA-DRB1*15:01 with anti-EBNA1 and anti-GlialCAM antibodies increase MS risk significantly and in an additive fashion. In addition, antibody reactivities against more than one EBNA1 peptide and more than one CNS-mimic increase the MS risk significantly but modestly. Overall, we show that molecular mimicry between EBNA1 and GlialCAM is likely an important molecular mechanism contributing to MS pathology.

Analysis of vehicle and pedestrian detection effects of improved YOLOv8 model in drone-assisted urban traffic monitoring system

This study proposes an improved YOLOv8 model for vehicle and pedestrian detection in urban traffic monitoring systems. In order to improve the detection performance of the model, we introduced a multi-scale feature fusion module and an improved non-maximum suppression (NMS) algorithm based on the YOLOv8 model. The multi-scale feature fusion module enhances the model’s detection ability for targets of different sizes by combining feature maps of different scales; the improved non-maximum suppression algorithm effectively reduces repeated detection and missed detection by optimizing the screening process of candidate boxes. Experimental results show that the improved YOLOv8 model exhibits excellent detection performance on the VisDrone2019 dataset, and outperforms other classic target detection models and the baseline YOLOv8 model in key indicators such as precision, recall, F1 score, and mean average precision (mAP). In addition, through visual analysis, our method demonstrates strong target detection capabilities in complex urban traffic environments, and can accurately identify and label targets of multiple categories. Finally, these results prove the effectiveness and superiority of the improved YOLOv8 model, providing reliable technical support for urban traffic monitoring systems.