Deep learning system for screening AIDS-related cytomegalovirus retinitis with ultra-wide-field fundus images.

Background: Ophthalmological screening for cytomegalovirus retinitis (CMVR) for HIV/AIDS patients is important to prevent lifelong blindness. Previous studies have shown good properties of automated CMVR screening using digital fundus images. However, the application of a deep learning (DL) system to CMVR with ultra-wide-field (UWF) fundus images has not been studied, and the feasibility and efficiency of this method are uncertain. Methods: In this study, we developed, internally validated, externally validated, and prospectively validated a DL system to detect AIDS-related from UWF fundus images from different clinical datasets. We independently used the InceptionResnetV2 network to develop and internally validate a DL system for identifying active CMVR, inactive CMVR, and non-CMVR in 6960 UWF fundus images from 862 AIDS patients and validated the system in a prospective and an external validation data set using the area under the curve (AUC), accuracy, sensitivity, and specificity. A heat map identified the most important area (lesions) used by the DL system for differentiating CMVR. Results: The DL system showed AUCs of 0.945 (95 % confidence interval [CI]: 0.929, 0.962), 0.964 (95 % CI: 0.870, 0.999) and 0.968 (95 % CI: 0.860, 1.000) for detecting active CMVR from non-CMVR and 0.923 (95 % CI: 0.908, 0.938), 0.902 (0.857, 0.948) and 0.884 (0.851, 0.917) for detecting active CMVR from non-CMVR in the internal cross-validation, external validation, and prospective validation, respectively. Deep learning performed promisingly in screening CMVR. It also showed the ability to differentiate active CMVR from non-CMVR and inactive CMVR as well as to identify active CMVR and inactive CMVR from non-CMVR (all AUCs in the three independent data sets >0.900). The heat maps successfully highlighted lesion locations. Conclusions: Our UWF fundus image-based DL system showed reliable performance for screening AIDS-related CMVR showing its potential for screening CMVR in HIV/AIDS patients, especially in the absence of ophthalmic resources.

Evaluation of dry eye disease symptomatology and mental health status among patients with different COVID-19 statuses.

AIM: To evaluate dry eye disease (DED) symptomatology and mental health status in different COVID-19 patients. METHODS: A cross-sectional observational design was used. Totally 123 eligible adults (46.34% of men, age range, 18-59y) with COVID-19 included in the study from August to November, 2022. Ocular Surface Disease Index (OSDI), Five-item Dry Eye Questionnaire (DEQ-5), Hospital Anxiety and Depression Scale (HADS), and Pittsburgh Sleep Quality Index (PSQI) were used in this study. RESULTS: OSDI scores were 6.82 (1.25, 15.91) in asymptomatic carriers, 7.35 (2.50, 18.38) in mild cases, and 16.67 (4.43, 28.04) in recurrent cases, with 30.00%, 35.56%, and 57.89%, respectively evaluated as having DED symptoms (χ2=7.049, P=0.029). DEQ-5 score varied from 2.00 (0, 6.00) in asymptomatic carriers, 3.00 (0, 8.00) in mild cases, and 8.00 (5.00, 10.00) in recurrent cases, with 27.50%, 33.33%, and 55.26%, respectively assessed as having DED symptoms (χ2=8.532, P=0.014). The prevalence of clinical anxiety (50.00%) and depression (47.37%) symptoms were also significantly higher in patients with recurrent infection (χ2=24.541, P<0.001; χ2=30.871, P<0.001). Recurrent infection was a risk factor for high OSDI scores [odds ratio, 2.562; 95% confidence interval (CI), 1.631-7.979; P=0.033] and DEQ-5 scores (odds ratio, 3.353; 95%CI, 1.038-8.834; P=0.043), whereas having a fixed occupation was a protective factor for OSDI scores (odds ratio, 0.088; 95%CI, 0.022-0.360; P=0.001) and DEQ-5 scores (odds ratio, 0.126; 95%CI, 0.039-0.405; P=0.001). CONCLUSION: Patients with recurrent COVID-19 have more severe symptoms of DED, anxiety, and depression.

Gossamer: Scaling Image Processing and Reconstruction to Whole Brains.

Neuronal reconstruction-a process that transforms image volumes into 3D geometries and skeletons of cells-bottlenecks the study of brain function, connectomics and pathology. Unlike artistic domains with similar challenges (e.g., hair modeling), scientists need exact and complete segmentations to study subtle topological differences. Existing methods are disk-bound, dense-access, coupled, single-threaded, algorithmically unscalable and require manual cropping of small windows and proofreading of skeletons due to low topological accuracy. Designing a data-intensive parallel solution suited to a neurons' shape, topology and far-ranging connectivity is particularly challenging due to I/O and load-balance, yet by abstracting vision tasks such as segmentation and skeletonization into strategically ordered specializations of search, we progressively lower memory by 4 orders of magnitude. This enables 1 mouse brain to be fully processed in-memory on a single server, at 67× the scale with 870× less memory while having 78% higher automated yield than the highest performing alternative methods.

Evaluation of tear film in patients with AIDS without opportunistic ocular infections in the era of COVID-19: A case-control study.

PURPOSE: The assessment of tear film and ocular surface conditions in patients with acquired immunodeficiency syndrome (AIDS) has been poorly studied thus far. We aim to assess tear film parameters, ocular surface characteristics, and dry eye disease (DED) symptoms of patients with AIDS who did not undergo highly active antiretroviral treatment (HAART). METHODS: This case-control study included 154 age-, sex-, and ethnicity-matched healthy controls and patients with AIDS. All participants underwent comprehensive ocular surface assessment and subjective DED symptomology evaluation. Data were collected between March 2022 and July 2022. RESULTS: HAART-naïve patients with AIDS had a shorter noninvasive tear film breakup time (median 3.76 vs. 8.54 s), thinner tear film lipid layer thickness (median 73.00 vs. 91.00 nm), and lower Schirmer I test values (median 5.00 mm/5 min vs. 12.00 mm/5 min) (all P < 0.001). Moreover, higher corneal fluorescein staining scores (median 1.00 vs. 0.00) and higher upper, lower, and total meibomian gland grades were observed in AIDS patients (all P < 0.05). Negative correlations between the blood viral load and the Ocular Surface Disease Index score ( r = -3.50, P = 0.027) and the Schirmer I test score ( r = -0.374, P = 0.017) were detected in patients with AIDS. CONCLUSION: Altered tear film status was observed in individuals with HAART-naïve AIDS, even when there were no other ocular symptoms present. Therefore, patients with AIDS should be encouraged to undergo comprehensive ocular surface examinations to detect any subclinical tear film alterations occurring.

Combinatorial quantification of distinct neural projections from retrograde tracing.

Comprehensive quantification of neuronal architectures underlying anatomical brain connectivity remains challenging. We introduce a method to identify distinct axonal projection patterns from a source to a set of target regions and the count of neurons with each pattern. A source region projecting to n targets could have 2n-1 theoretically possible projection types, although only a subset of these types typically exists. By injecting uniquely labeled retrograde tracers in k target regions (k < n), one can experimentally count the cells expressing different color combinations in the source region. The neuronal counts for different color combinations from n-choose-k experiments provide constraints for a model that is robustly solvable using evolutionary algorithms. Here, we demonstrate this method's reliability for 4 targets using simulated triple injection experiments. Furthermore, we illustrate the experimental application of this framework by quantifying the projections of male mouse primary motor cortex to the primary and secondary somatosensory and motor cortices.

Full-Spectrum Neuronal Diversity and Stereotypy through Whole Brain Morphometry.

We conducted a large-scale study of whole-brain morphometry, analyzing 3.7 peta-voxels of mouse brain images at the single-cell resolution, producing one of the largest multi-morphometry databases of mammalian brains to date. We spatially registered 205 mouse brains and associated data from six Brain Initiative Cell Census Network (BICCN) data sources covering three major imaging modalities from five collaborative projects to the Allen Common Coordinate Framework (CCF) atlas, annotated 3D locations of cell bodies of 227,581 neurons, modeled 15,441 dendritic microenvironments, characterized the full morphology of 1,891 neurons along with their axonal motifs, and detected 2.58 million putative synaptic boutons. Our analysis covers six levels of information related to neuronal populations, dendritic microenvironments, single-cell full morphology, sub-neuronal dendritic and axonal arborization, axonal boutons, and structural motifs, along with a quantitative characterization of the diversity and stereotypy of patterns at each level. We identified 16 modules consisting of highly intercorrelated brain regions in 13 functional brain areas corresponding to 314 anatomical regions in CCF. Our analysis revealed the dendritic microenvironment as a powerful method for delineating brain regions of cell types and potential subtypes. We also found that full neuronal morphologies can be categorized into four distinct classes based on spatially tuned morphological features, with substantial cross-areal diversity in apical dendrites, basal dendrites, and axonal arbors, along with quantified stereotypy within cortical, thalamic and striatal regions. The lamination of somas was found to be more effective in differentiating neuron arbors within the cortex. Further analysis of diverging and converging projections of individual neurons in 25 regions throughout the brain reveals branching preferences in the brain-wide and local distributions of axonal boutons. Overall, our study provides a comprehensive description of key anatomical structures of neurons and their types, covering a wide range of scales and features, and contributes to our understanding of neuronal diversity and its function in the mammalian brain.

Neuronal Connectivity as a Determinant of Cell Types and Subtypes.

Classifications of single neurons at brain-wide scale is a powerful way to characterize the structural and functional organization of a brain. We acquired and standardized a large morphology database of 20,158 mouse neurons, and generated a whole-brain scale potential connectivity map of single neurons based on their dendritic and axonal arbors. With such an anatomy-morphology-connectivity mapping, we defined neuron connectivity types and subtypes (both called "c-types" for simplicity) for neurons in 31 brain regions. We found that neuronal subtypes defined by connectivity in the same regions may share statistically higher correlation in their dendritic and axonal features than neurons having contrary connectivity patterns. Subtypes defined by connectivity show distinct separation with each other, which cannot be recapitulated by morphology features, population projections, transcriptomic, and electrophysiological data produced to date. Within this paradigm, we were able to characterize the diversity in secondary motor cortical neurons, and subtype connectivity patterns in thalamocortical pathways. Our finding underscores the importance of connectivity in characterizing the modularity of brain anatomy, as well as the cell types and their subtypes. These results highlight that c-types supplement conventionally recognized transcriptional cell types (t-types), electrophysiological cell types (e-types), and morphological cell types (m-types) as an important determinant of cell classes and their identities.

Lattice Compression Revealed at the ≈1†nm Scale.

Lattice tuning at the ≈1 nm scale is fascinating and challenging; for instance, lattice compression at such a minuscule scale has not been observed. The lattice compression might also bring about some unusual properties, which waits to be verified. Through ligand induction, we herein achieve the lattice compression in a ≈1 nm gold nanocluster for the first time, as detected by the single-crystal X-ray crystallography. In a freshly synthesized Au52 (CHT)28 (CHT=S-c-C6 H11 ) nanocluster, the lattice distance of the (110) facet is found to be compressed from 4.51 to 3.58 Šat the near end. However, the lattice distances of the (111) and (100) facets show no change in different positions. The lattice-compressed nanocluster exhibits superior electrocatalytic activity for the CO2 reduction reaction (CO2 RR) compared to that exhibited by the same-sized Au52 (TBBT)32 (TBBT=4-tert-butyl-benzenethiolate) nanocluster and larger Au nanocrystals without lattice variation, indicating that lattice tuning is an efficient method for tailoring the properties of metal nanoclusters. Further theoretical calculations explain the high CO2 RR performance of the lattice-compressed Au52 (CHT)28 and provide a correlation between its structure and catalytic activity.

A guide to the BRAIN Initiative Cell Census Network data ecosystem.

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

Combinatorial quantification of distinct neural projections from retrograde tracing.

Comprehensive quantification of neuronal architectures underlying anatomical brain connectivity remains challenging. We introduce a method to identify the distinct axonal projection patterns from a source to a set of target regions and the count of neurons with each pattern. For a source region projecting to n targets, there are 2n - 1 theoretically possible projection types, although only a subset of these types typically exists. By injecting uniquely labeled retrograde tracers in k regions (k < n), one can experimentally count the cells expressing different combinations of colors in the source region1,2. Such an experiment can be performed for n choose k combinations. The counts of cells with different color combinations from all experiments provide constraints for a system of equations that include 2n - 1 unknown variables, each corresponding to the count of neurons for a projection pattern. Evolutionary algorithms prove to be effective at solving the resultant system of equations, thus allowing the determination of the counts of neurons with each of the possible projection patterns. Numerical analysis of simulated 4 choose 3 retrograde injection experiments using surrogate data demonstrates reliable and precise count estimates for all projection neuron types. We illustrate the experimental application of this framework by quantifying the projections of mouse primary motor cortex to four prominent targets: the primary and secondary somatosensory and motor cortices.

The Deep Learning-Based Framework for Automated Predicting COVID-19 Severity Score.

With the COVID-19 pandemic sweeping the globe, an increasing number of people are working on pandemic research, but there is less effort on predicting its severity. Diagnostic chest imaging is thought to be a quick and reliable way to identify the severity of COVID-19. We describe a deep learning method to automatically predict the severity score of patients by analyzing chest X-rays, with the goal of collaborating with doctors to create corresponding treatment measures for patients and can also be used to track disease change. Our model consists of a feature extraction phase and an outcome prediction phase. The feature extraction phase uses a DenseNet backbone network to extract 18 features related to lung diseases from CXRs; the outcome prediction phase, which employs the MLP regression model, selects several important features for prediction from the features extracted in the previous phase and demonstrates the effectiveness of our model by comparing it with several commonly used regression models. On a dataset of 2373 CXRs, our model predicts the geographic extent score with 1.02 MAE and the lung opacity score with 0.85 MAE.

Macroscale connections of the mouse lateral preoptic area and anterior lateral hypothalamic area.

The macroscale neuronal connections of the lateral preoptic area (LPO) and the caudally adjacent lateral hypothalamic area anterior region (LHAa) were investigated in mice by anterograde and retrograde axonal tracing. Both hypothalamic regions are highly and diversely connected, with connections to >200 gray matter regions spanning the forebrain, midbrain, and rhombicbrain. Intrahypothalamic connections predominate, followed by connections with the cerebral cortex and cerebral nuclei. A similar overall pattern of LPO and LHAa connections contrasts with substantial differences between their input and output connections. Strongest connections include outputs to the lateral habenula, medial septal and diagonal band nuclei, and inputs from rostral and caudal lateral septal nuclei; however, numerous additional robust connections were also observed. The results are discussed in relation to a current model for the mammalian forebrain network that associates LPO and LHAa with a range of functional roles, including reward prediction, innate survival behaviors (including integrated somatomotor and physiological control), and affect. The present data suggest a broad and intricate role for LPO and LHAa in behavioral control, similar in that regard to previously investigated LHA regions, contributing to the finely tuned sensory-motor integration that is necessary for behavioral guidance supporting survival and reproduction.

Macular Changes Observed on Optical Coherence Tomography Angiography in Patients Infected With Human Immunodeficiency Virus Without Infectious Retinopathy.

Purpose: As the human immunodeficiency virus (HIV) pandemic is far from over, whether there are subclinical macular changes in HIV-positive patients is something that should not be overlooked. We aimed to apply optical coherence tomography angiography (OCTA) to assess the macular structure and microvasculature changes in patients with HIV without infectious retinopathy. Methods: HIV-positive and -negative participants were included and classified into three groups: HIV-negative, HIV-positive, and HIV-positive with microvasculopathy. OCTA parameters regarding macular structure and microvasculature were analyzed. Results: Compared with the HIV-negative group, the superficial retinal vessel density (VD) in the parafovea sectors and the whole Early Treatment of Diabetic Retinopathy Study (ETDRS) grid and the choroidal vascularity index (CVI) in the whole ETDRS grid were significantly decreased in the HIV-positive and HIV-positive with microvasculopathy groups (p < 0.05). No differences were found in OCTA parameters between the HIV-positive and HIV-positive with microvasculopathy groups. Retinal, retinal nerve fiber layer-ganglion cell layer-inner plexiform layer (RNFL-GCL-IPL), RNFL, GCL-IPL, and INL thickness showed a negative association with the duration of HIV diagnosis or antiretroviral therapy (ART) (all p < 0.05). All OCTA microvasculature parameters showed no association with HIV-related clinical variables (all p > 0.05). Conclusions: Subclinical macular changes existed in HIV-infected patients without clinical infectious retinopathy. Substructures from inner retinal layers might be associated with HIV infection or ART duration.

Brain Networks of Connectionally Unique Basolateral Amygdala Cell Types.

Different brain regions structurally interconnected through networks regulate behavior output. Therefore, understanding the functional organization of the brain in health and disease necessitates a foundational anatomic roadmap to its network organization. To provide this to the research community, our lab has systematically traced thousands of pathways in the mouse brain and has applied computational measures to determine the network architecture of major brain systems. Toward this effort, the brain-wide networks of the basolateral amygdalar complex (BLA) were recently generated. The data revealed uniquely connected cell types within the same BLA nucleus that were constituents of distinct neural networks. Here, we elaborate on how these connectionally unique BLA cell types fit within the larger cortico-basal ganglia and limbic networks that were previously described by our team. The significance and utility of high quality, detailed anatomic data is also discussed.

Petabyte-Scale Multi-Morphometry of Single Neurons for Whole Brains.

Recent advances in brain imaging allow producing large amounts of 3-D volumetric data from which morphometry data is reconstructed and measured. Fine detailed structural morphometry of individual neurons, including somata, dendrites, axons, and synaptic connectivity based on digitally reconstructed neurons, is essential for cataloging neuron types and their connectivity. To produce quality morphometry at large scale, it is highly desirable but extremely challenging to efficiently handle petabyte-scale high-resolution whole brain imaging database. Here, we developed a multi-level method to produce high quality somatic, dendritic, axonal, and potential synaptic morphometry, which was made possible by utilizing necessary petabyte hardware and software platform to optimize both the data and workflow management. Our method also boosts data sharing and remote collaborative validation. We highlight a petabyte application dataset involving 62 whole mouse brains, from which we identified 50,233 somata of individual neurons, profiled the dendrites of 11,322 neurons, reconstructed the full 3-D morphology of 1,050 neurons including their dendrites and full axons, and detected 1.9 million putative synaptic sites derived from axonal boutons. Analysis and simulation of these data indicate the promise of this approach for modern large-scale morphology applications.

Tissue Engineering with Compact Bone-Derived Cell Spheroids Enables Bone Formation around Transplanted Tooth.

BACKGROUND: Although tooth transplantation is a desirable treatment option for congenital defects of permanent teeth in children, transplantation to a narrow alveolar ridge is not feasible. In this study, we investigated the possibility of bone tissue engineering simultaneously with tooth transplantation to enhance the width of the alveolar bone. METHODS: Bone marrow mononuclear cells or cortical bone-derived mesenchymal stromal cell spheroids were seeded onto atelocollagen sponge and transplanted with freshly extracted molars from mice of the same strain. New bone formation around the tooth root was evaluated using micro-computed tomography and histological analysis. Tooth alone, or tooth with scaffold but without cells, was also transplanted and served as controls. RESULTS: Micro-computed tomography showed new bone formation in the furcation area in all four groups. Remarkable bone formation outside the root was also observed in the cortical bone-derived mesenchymal stromal cell group, but was scarce in the other three groups. Histological analysis revealed that the space between the new bone and the root was filled with collagen fibers in all four groups, indicating that the periodontal ligament was maintained. CONCLUSION: This study demonstrates the potential of simultaneous alveolar bone expansion employing bone tissue engineering approach using cortical bone-derived mesenchymal stromal cell spheroids for tooth transplantation. The use of an orthotopic transplantation model may further clarify the feasibility and functional recovery of the transplanted tooth over a longer period.

Application of AAV1 for Anterograde Transsynaptic Circuit Mapping and Input-Dependent Neuronal Cataloging.

Viruses that spread transsynaptically provide a powerful means to study interconnected circuits in the brain. Here we describe the use of adeno-associated virus, serotype 1 (AAV1), as a tool to achieve robust, anterograde transsynaptic spread in a variety of unidirectional pathways. A protocol for performing intracranial AAV1 injections in mice is presented, along with additional guidance for planning experiments, sourcing materials, and optimizing the approach to achieve the most successful outcomes. By following the methods presented here, researchers will be able to reveal postsynaptically connected neurons downstream of a given AAV1 injection site and access these input-defined cells for subsequent mapping, recording, and manipulation to characterize their anatomical and functional properties. © 2022 Wiley Periodicals LLC. Basic Protocol: Stereotaxic injection of AAV1 for anterograde transsynaptic spread.

Sub-national climate change risk assessment: A case analysis for Tibet and its prefecture-level cities.

Avoiding climate change from exceeding its critical threshold is a serious challenge facing humanity at present and in the future. As the mode of global cooperative action is stranded, multi-center and multi-level efforts are needed to deal with global warming in the future. In order to provide information for the formulation of low-carbon development policies, it is essential to assess the maintain or cross of climate change threshold on different scales. In this study, the carbon footprint calculated based on the process coefficient approach is systematically integrated with the climate change indicator of the planetary boundaries framework improved with the goals of the Paris Agreement to identify the climate change risks of Tibet and its prefecture-level cities from 2000 to 2017. Moreover, the main driving factors behind carbon footprint were analyzed. The findings showed that: (1) Since 2000, Tibet's CO2 emissions have demonstrated steady and rapid increase. The sector composition is dominated by cement production-related and transportation sector-related emissions. The type composition is dominated by diesel-related, process-related, and coal-related emissions. There are significant differences in CO2 emissions among all prefecture-level cities, with Lhasa having the largest contribution. (2) Except for Lhasa and Shannan's CO2 emissions that have crossed their critical threshold of climate change and are in an unsafe state, Tibet and other prefecture-level cities have not yet crossed their critical threshold. (3) Except for Ngari, per capita GDP, energy intensity, population size, and carbon intensity positively affect the increase of CO2 emissions in Tibet and its prefecture-level cities. Our study helps actors at less aggregated scales to determine appropriate policy strengths based on globally agreed goals and ambitions in the process of responding to global warming in a bottom-up manner.

High Blood Cytomegalovirus Load Suggests Cytomegalovirus Retinitis in HIV/AIDS Patients: A Cross-Sectional Study.

PURPOSE: To clarify the cut off value of blood CMV load to indicate CMV retinitis and its relationships with ocular features. METHODS: Patients were divided into non-CMV and CMV retinitis groups. A logistic regression model was applied to estimate the association of each variable with CMV retinitis. Spearman correlation was used to estimate the correlation between the blood and aqueous CMV load. RESULTS: Blood CMV load higher than 4log10 (OR, 6.897; CI: 2.813-16.910; P < .001) was the major predictor of CMV retinitis. Blood CMV load wasn't different between the initial and early stage (P = .066). No correlation was observed between the blood and aqueous CMV load (P = .083, r = 0.228). CONCLUSIONS: Blood CMV load higher than 4log10 is an important predictor for CMV retinitis in HIV/AIDS patients, but it couldn't indicate the ocular features. Ophthalmologic screening is still necessary.Abbreviations: CMV: Cytomegalovirus; CMVR: Cytomegalovirus retinitis; HIV: Human Immunodeficiency Virus; AIDS: Acquired Immune Deficiency Syndrome; ART: Antiretroviral therapy; EOD: End-organ diseases; PCR: Polymerase Chain Reaction; OR: Odds Ratio; CI: 95% Confidence Interval; IQR: Interquartile range.

Current strategies with sensing technologies to eliminate stress cardiomyopathy.

Stress cardiomyopathy refers weakening of heart muscle due to the continuous stress. Generally, the severe status of stress cardiomyopathy has been revealed after damaging the muscles and measured by the physical changes in the heart system. To overcome this issue, biosensor can be used, which could eliminate the late identification stress cardiomyopathy. With biosensors, different stress markers such as epinephrine, dopamine, catecholamine, α-amylase, norepinephrine, serotonin and cortisol have been identified by a wide range of developments. These biosensors are available from laboratory to industry at the ranges of nano to macrodevices. To merge with the identification of stress cardiomyopathy, the above strategies might be utilized properly and can aid to reduce the stress-related problems. This overview gleaned the currently available biosensing methods and the associated biomarkers at various stages of the developments and implementations of stress cardiomyopathy.