PIV-MyoMonitor: an accessible particle image velocimetry-based software tool for advanced contractility assessment of cardiac organoids.

Induced pluripotent stem cell (iPSC)-derived cardiac organoids offer a versatile platform for personalized cardiac toxicity assessment, drug screening, disease modeling, and regenerative therapies. While previous image-based contractility analysis techniques allowed the assessment of contractility of two-dimensional cardiac models, they face limitations, including encountering high noise levels when applied to three-dimensional organoid models and requiring expensive equipment. Additionally, they offer fewer functional parameters compared to commercial software. To address these challenges, we developed an open-source, particle image velocimetry-based software (PIV-MyoMonitor) and demonstrated its capacity for accurate contractility analysis in both two- and three-dimensional cardiac models using standard lab equipment. Comparisons with four other open-source software programs highlighted the capability of PIV-MyoMonitor for more comprehensive quantitative analysis, providing 22 functional parameters and enhanced video outputs. We showcased its applicability in drug screening by characterizing the response of cardiac organoids to a known isotropic drug, isoprenaline. In sum, PIV-MyoMonitor enables reliable contractility assessment across various cardiac models without costly equipment or software. We believe this software will benefit a broader scientific community.

Design of Low-Noise CMOS Image Sensor Using a Hybrid-Correlated Multiple Sampling Technique.

We present a 320 × 240 CMOS image sensor (CIS) using the proposed hybrid-correlated multiple sampling (HMS) technique with an adaptive dual-gain analog-to-digital converter (ADC). The proposed HMS improves the noise characteristics under low illumination by adjusting the ADC gain according to the incident light on the pixels. Depending on whether it is less than or greater than 1/4 of the full output voltage range from pixels, either correlated multiple sampling or conventional-correlated double sampling (CDS) is used with different slopes of the ramping signals. The proposed CIS achieves 11-bit resolution of the ADC using an up-down counter that controls the LSB depending on the ramping signals used. The sensor was fabricated using a 0.11 µm CIS process, and the total chip area was 2.55 mm × 4.3 mm. Compared to the conventional CDS, the measurement results showed that the maximum dark random noise was reduced by 26.7% with the proposed HMS, and the maximum figure of merit was improved by 49.1%. The total power consumption was 5.1 mW at 19 frames per second with analog, pixel, and digital supply voltages of 3.3 V, 3.3 V, and 1.5 V, respectively.

L-Type Amino Acid Transporter 1 (LAT1) Promotes PMA-Induced Cell Migration through mTORC2 Activation at the Lysosome.

The mTOR signaling pathway integrates signaling inputs from nutrients, including glucose and amino acids, which are precisely regulated by transporters depending on nutrient levels. The L-type amino acid transporter 1 (LAT1) affects the activity of mTORC1 through upstream regulators that sense intracellular amino acid levels. While mTORC1 activation by LAT1 has been thoroughly investigated in cultured cells, the effects of LAT1 expression on the activity of mTORC2 has scarcely been studied. Here, we provide evidence that LAT1 recruits and activates mTORC2 on the lysosome for PMA-induced cell migration. LAT1 is translocated to the lysosomes in cells treated with PMA in a dose- and time-dependent manner. Lysosomal LAT1 interacted with mTORC2 through a direct interaction with Rictor, leading to the lysosomal localization of mTORC2. Furthermore, the depletion of LAT1 reduced PMA-induced cell migration in a wound-healing assay. Consistent with these results, the LAT1 N3KR mutant, which is defective in PMA-induced endocytosis and lysosomal localization, did not induce mTORC2 recruitment to the lysosome, with the activation of mTORC2 determined via Akt phosphorylation or the LAT1-mediated promotion of cell migration. Taken together, lysosomal LAT1 recruits and activates the mTORC2 complex and downstream Akt for PMA-mediated cell migration. These results provide insights into the development of therapeutic drugs targeting the LAT1 amino acid transporter to block metastasis, as well as disease progression in various types of cancer.

Large anatomical changes in head-and-neck cancers - A dosimetric comparison of online and offline adaptive proton therapy.

Purpose: This work evaluates an online adaptive (OA) workflow for head-and-neck (H&N) intensity-modulated proton therapy (IMPT) and compares it with full offline replanning (FOR) in patients with large anatomical changes. Methods: IMPT treatment plans are created retrospectively for a cohort of eight H&N cancer patients that previously required replanning during the course of treatment due to large anatomical changes. Daily cone-beam CTs (CBCT) are acquired and corrected for scatter, resulting in 253 analyzed fractions. To simulate the FOR workflow, nominal plans are created on the planning-CT and delivered until a repeated-CT is acquired; at this point, a new plan is created on the repeated-CT. To simulate the OA workflow, nominal plans are created on the planning-CT and adapted at each fraction using a simple beamlet weight-tuning technique. Dose distributions are calculated on the CBCTs with Monte Carlo for both delivery methods. The total treatment dose is accumulated on the planning-CT. Results: Daily OA improved target coverage compared to FOR despite using smaller target margins. In the high-risk CTV, the median D98 degradation was 1.1 % and 2.1 % for OA and FOR, respectively. In the low-risk CTV, the same metrics yield 1.3 % and 5.2 % for OA and FOR, respectively. Smaller setup margins of OA reduced the dose to all OARs, which was most relevant for the parotid glands. Conclusion: Daily OA can maintain prescription doses and constraints over the course of fractionated treatment, even in cases of large anatomical changes, reducing the necessity for manual replanning in H&N IMPT.

TOPAS-imaging: extensions to the TOPAS simulation toolkit for medical imaging systems.

Objective. The TOol for PArticle Simulation (TOPAS) is a Geant4-based Monte Carlo software application that has been used for both research and clinical studies in medical physics. So far, most users of TOPAS have focused on radiotherapy-related studies, such as modeling radiation therapy delivery systems or patient dose calculation. Here, we present the first set of TOPAS extensions to make it easier for TOPAS users to model medical imaging systems.Approach. We used the extension system of TOPAS to implement pre-built, user-configurable geometry components such as detectors (e.g. flat-panel and multi-planar detectors) for various imaging modalities and pre-built, user-configurable scorers for medical imaging systems (e.g. digitizer chain).Main results. We developed a flexible set of extensions that can be adapted to solve research questions for a variety of imaging modalities. We then utilized these extensions to model specific examples of cone-beam CT (CBCT), positron emission tomography (PET), and prompt gamma (PG) systems. The first of these new geometry components, the FlatImager, was used to model example CBCT and PG systems. Detected signals were accumulated in each detector pixel to obtain the intensity of x-rays penetrating objects or prompt gammas from proton-nuclear interaction. The second of these new geometry components, the RingImager, was used to model an example PET system. Positron-electron annihilation signals were recorded in crystals of the RingImager and coincidences were detected. The simulated data were processed using corresponding post-processing algorithms for each modality and obtained results in good agreement with the expected true signals or experimental measurement.Significance. The newly developed extension is a first step to making it easier for TOPAS users to build and simulate medical imaging systems. Together with existing TOPAS tools, this extension can help integrate medical imaging systems with radiotherapy simulations for image-guided radiotherapy.

A feasibility study on deep-neural-network-based dose-neutral dual-energy digital breast tomosynthesis.

BACKGROUND: Diagnostic performance based on x-ray breast imaging is subject to breast density. Although digital breast tomosynthesis (DBT) is reported to outperform conventional mammography in denser breasts, mass detection and malignancy characterization are often considered challenging yet. PURPOSE: As an improved diagnostic solution to the dense breast cases, we propose a dual-energy DBT imaging technique that enables breast compositional imaging at comparable scanning time and patient dose compared to the conventional single-energy DBT. METHODS: The proposed dual-energy DBT acquires projection data by alternating two different energy spectra. Then, we synthesize unmeasured projection data using a deep neural network that exploits the measured projection data and adjacent projection data obtained under the other x-ray energy spectrum. For material decomposition, we estimate partial path lengths of an x-ray through water, lipid, and protein from the measured and the synthesized projection data with the object thickness information. After material decomposition in the projection domain, we reconstruct material-selective DBT images. The deep neural network is trained with the numerical breast phantoms. A pork meat phantom is scanned with a prototype dual-energy DBT system to demonstrate the feasibility of the proposed imaging method. RESULTS: The developed deep neural network successfully synthesized missing projections. Material-selective images reconstructed from the synthesized data present comparable compositional contrast of the cancerous masses compared with those from the fully measured data. CONCLUSIONS: The proposed dual-energy DBT scheme is expected to substantially contribute to enhancing mass malignancy detection accuracy particularly in dense breasts.

Circadian gating of light-induced arousal in Drosophila sleep.

Circadian rhythms and sleep homeostasis constitute the two-process model for daily sleep regulation. However, evidence for circadian control of sleep-wake cycles has been relatively short since clock-less animals often show sleep behaviors quantitatively comparable to wild-type. Here we examine Drosophila sleep behaviors under different light-dark regimes and demonstrate that circadian clocks gate light-induced arousal. Genetic excitation of tyrosine decarboxylase 2 (TDC2)-expressing neurons suppressed sleep more evidently at night, causing nocturnal activity. The arousal effects were likely mediated in part by glutamate transmission from the octopaminergic neurons and substantially masked by light. Application of T12 cycles (6-h light: 6-h dark) further showed that the light-sensitive effects of TDC2 neurons depended on the time of the day. In particular, light-sensing via visual input pathway led to strong sleep suppression at subjective night, and such an effect disappeared in clock-less mutants. Transgenic mapping revealed that light-induced arousal and free-running behavioral rhythms require distinct groups of circadian pacemaker neurons. These results provide convincing evidence that circadian control of sleep is mediated by the dedicated clock neurons for light-induced arousal.

Characterization and activity-folding relationship of serine protease from Antarctic krill (Euphausia superba).

Euphausia superba (Antarctic krill) serine protease (ESP) was investigated to gain insights into the activity-structural relationship, folding behavior, and regulation of the catalytic function. We purified ESP from the krill muscle and characterized biochemical distinctions via enzyme kinetics. Studies of inhibition kinetics and unfolding in the presence of a serine residue modifier, such as phenylmethanesulfonyl fluoride, were conducted. Structural characterizations were measured by spectrofluorimetry, including 1-anilinonaphthalene-8-sulfonate dye labeling for hydrophobic residues. The computational simulations such as docking and molecular dynamics were finally conducted to detect key residues and folding behaviors in a nano-second range. The kinetic parameters of ESP were measured as KmBANH = 0.97 ± 0.15 mM and kcat/KmBANH = 4.59 s-1/mM. The time-interval kinetics measurements indicated that ESP inactivation was transformed from a monophase to a biphase process to form a thermodynamically stable state. Spectrofluorimetry measurements showed that serine is directly connected to the regional folding of ESP. Several osmolytes such as proline and glycine only partially protected the inactive form of ESP by serine modification. Computational molecular dynamics and docking simulations showed that three serine residues (Ser183, Ser188, and Ser207) and Cys184, Val206, and Gly209 are key residues of catalytic functions. Our study revealed the functional roles of serine residues as key residues of catalytic function at the active site and of the structural conformation as key folding factors, where ESP displays a flexible property of active site pocket compared to the overall structure.Communicated by Ramaswamy H. Sarma.

Attention to number requires magnitude-specific inhibition.

Recent studies have shown that the ability to process number in the face of conflicting dimensions of magnitude is a crucial aspect of numerosity judgments, relying in part on the inhibition of the non-numerical dimensions. Here we report, for the first time, that these inhibitory control processes are specific to the conflicting dimension of magnitude. Using a non-symbolic numerical comparison task adapted to a conflict adaptation paradigm on a group of 82 adults, we show that congruency effects between numerical and non-numerical information were reduced only when the conflicting dimension was the same in the preceding incongruent trial. Attention to number thus involves inhibitory control processes acting at a specific level of information. These results contribute to better characterize the domain general abilities involved in numerical cognition, and provide evidence for a specific interaction between numerosity perception and inhibitory control.

Optically stimulated luminescence dosimeters for simultaneous measurement of point dose and dose-weighted LET in an adaptive proton therapy workflow.

Purpose: To demonstrate the suitability of optically stimulated luminescence detectors (OSLDs) for accurate simultaneous measurement of the absolute point dose and dose-weighted linear energy transfer (LETD) in an anthropomorphic phantom for experimental validation of daily adaptive proton therapy. Methods: A clinically realistic intensity-modulated proton therapy (IMPT) treatment plan was created based on a CT of an anthropomorphic head-and-neck phantom made of tissue-equivalent material. The IMPT plan was optimized with three fields to deliver a uniform dose to the target volume covering the OSLDs. Different scenarios representing inter-fractional anatomical changes were created by modifying the phantom. An online adaptive proton therapy workflow was used to recover the daily dose distribution and account for the applied geometry changes. To validate the adaptive workflow, measurements were performed by irradiating Al2O3:C OSLDs inside the phantom. In addition to the measurements, retrospective Monte Carlo simulations were performed to compare the absolute dose and dose-averaged LET (LETD) delivered to the OSLDs. Results: The online adaptive proton therapy workflow was shown to recover significant degradation in dose conformity resulting from large anatomical and positioning deviations from the reference plan. The Monte Carlo simulations were in close agreement with the OSLD measurements, with an average relative error of 1.4% for doses and 3.2% for LETD. The use of OSLDs for LET determination allowed for a correction for the ionization quenched response. Conclusion: The OSLDs appear to be an excellent detector for simultaneously assessing dose and LET distributions in proton irradiation of an anthropomorphic phantom. The OSLDs can be cut to almost any size and shape, making them ideal for in-phantom measurements to probe the radiation quality and dose in a predefined region of interest. Although we have presented the results obtained in the experimental validation of an adaptive proton therapy workflow, the same approach can be generalized and used for a variety of clinical innovations and workflow developments that require accurate assessment of point dose and/or average LET.

OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines.

Objective.To establish an open framework for developing plan optimization models for knowledge-based planning (KBP).Approach.Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models.Main results.The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50-0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P< 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model.Significance.This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.

MOQUI: an open-source GPU-based Monte Carlo code for proton dose calculation with efficient data structure.

Objective.Monte Carlo (MC) codes are increasingly used for accurate radiotherapy dose calculation. In proton therapy, the accuracy of the dose calculation algorithm is expected to have a more significant impact than in photon therapy due to the depth-dose characteristics of proton beams. However, MC simulations come at a considerable computational cost to achieve statistically sufficient accuracy. There have been efforts to improve computational efficiency while maintaining sufficient accuracy. Among those, parallelizing particle transportation using graphic processing units (GPU) achieved significant improvements. Contrary to the central processing unit, a GPU has limited memory capacity and is not expandable. It is therefore challenging to score quantities with large dimensions requiring extensive memory. The objective of this study is to develop an open-source GPU-based MC package capable of scoring those quantities.Approach.We employed a hash-table, one of the key-value pair data structures, to efficiently utilize the limited memory of the GPU and score the quantities requiring a large amount of memory. With the hash table, only voxels interacting with particles will occupy memory, and we can search the data efficiently to determine their address. The hash-table was integrated with a novel GPU-based MC code, moqui.Main results.The developed code was validated against an MC code widely used in proton therapy, TOPAS, with homogeneous and heterogeneous phantoms. We also compared the dose calculation results of clinical treatment plans. The developed code agreed with TOPAS within 2%, except for the fall-off and regions, and the gamma pass rates of the results were >99% for all cases with a 2 mm/2% criteria.Significance.We can score dose-influence matrix and dose-rate on a GPU for a 3-field H&N case with 10 GB of memory using moqui, which would require more than 100 GB of memory with the conventionally used array data structure.

Single-cell transcriptome of the mouse retinal pigment epithelium in response to a low-dose of doxorubicin.

Cellular senescence of the retinal pigment epithelium (RPE) is thought to play an important role in vision-threatening retinal degenerative diseases, such as age-related macular degeneration (AMD). However, the single-cell RNA profiles of control RPE tissue and RPE tissue exhibiting cellular senescence are not well known. We have analyzed the single-cell transcriptomes of control mice and mice with low-dose doxorubicin (Dox)-induced RPE senescence (Dox-RPE). Our results have identified 4 main subpopulations in the control RPE that exhibit heterogeneous biological activities and play roles in ATP synthesis, cell mobility/differentiation, mRNA processing, and catalytic activity. In Dox-RPE mice, cellular senescence mainly occurs in the specific cluster, which has been characterized by catalytic activity in the control RPE. Furthermore, in the Dox-RPE mice, 6 genes that have not previously been associated with senescence also show altered expression in 4 clusters. Our results might serve as a useful reference for the study of control and senescent RPE.

Second-Generation JK-206 Targets the Oncogenic Signal Mediator RHOA in Gastric Cancer.

Ras homologous A (RHOA), a signal mediator and a GTPase, is known to be associated with the progression of gastric cancer (GC), which is the fourth most common cause of death in the world. Previously, we designed pharmacologically optimized inhibitors against RHOA, including JK-136 and JK-139. Based on this previous work, we performed lead optimization and designed novel RHOA inhibitors for greater anti-GC potency. Two of these compounds, JK-206 and JK-312, could successfully inhibit the viability and migration of GC cell lines. Furthermore, using transcriptomic analysis of GC cells treated with JK-206, we revealed that the inhibition of RHOA might be associated with the inhibition of the mitogenic pathway. Therefore, JK-206 treatment for RHOA inhibition may be a new therapeutic strategy for regulating GC proliferation and migration.

Deep-learning-based projection-domain breast thickness estimation for shape-prior iterative image reconstruction in digital breast tomosynthesis.

BACKGROUND: Digital breast tomosynthesis (DBT) is a technique that can overcome the shortcomings of conventional X-ray mammography and can be effective for the early screening of breast cancer. The compression of the breast is essential during the DBT imaging. However, since the periphery of the breast cannot be compressed to a constant value, nonuniformity of thickness and in-plane shape variation happen. These cause inconvenience in diagnosis, scatter correction, and breast density estimation. PURPOSE: In this study, we propose a deep-learning-based methodology for projection-domain breast thickness estimation and demonstrate a shape-prior iterative DBT image reconstruction. METHODS: We prepared the Euclidean distance map, the thickness map, and the thickness corrected image of the simulated breast projections for thickness and shape estimation. Each pixel of the Euclidean distance map denotes a distance to the closest skin-line. The thickness map is defined as a conceptual projection of ideal breast support that differentiates the inner and outer regions of the breast phantom. The thickness projection map thus represents the X-ray path lengths of a homogeneous breast phantom. We generated the thickness corrected image by dividing the projection image by the thickness map in a pixel-wise manner. We developed a convolutional neural network for thickness estimation and correction. The network utilizes a projection image and a Euclidean distance image together as a dual input. An estimated breast thickness map is then used for constructing the breast shape mask by use of the discrete algebraic reconstruction technique. RESULTS: The proposed network effectively corrected the breast thickness in various simulation situations. Low normalized root-mean-squared error (1.976%) and high structural similarity (99.997%) indicated a good agreement between the network-generated thickness corrected image and the ground truth image. Compared to the existing methods and simple single-input network, the proposed method showed outperformance in breast thickness estimation and accordingly in breast shape recovery for various numerical phantoms without provoking any significant artifact. We have demonstrated that the uniformity of voxel value has improved by the inclusion of a shape prior for the iterative DBT reconstruction. CONCLUSIONS: We presented a novel deep-learning-based breast thickness correction and a shape reconstruction method. This approach to estimating the true thickness map and the shape of the breast undergoing compression can benefit various fields such as improvement of diagnostic breast images, scatter correction, material decomposition, and breast density estimation.

Reduced acoustic resonator dimensions improve focusing efficiency of bacteria and submicron particles.

In this study, we demonstrate an acoustofluidic device that enables single-file focusing of submicron particles and bacteria using a two-dimensional (2D) acoustic standing wave. The device consists of a 100 µm × 100 µm square channel that supports 2D particle focusing in the channel center at an actuation frequency of 7.39 MHz. This higher actuation frequency compared with conventional bulk acoustic systems enables radiation-force-dominant motion of submicron particles and overcomes the classical size limitation (≈2 µm) of acoustic focusing. We present acoustic radiation force-based focusing of particles with diameters less than 0.5 µm at a flow rate of 12 µL min-1, and 1.33 µm particles at flow rates up to 80 µL min-1. The device focused 0.25 µm particles by the 2D acoustic radiation force while undergoing a channel cross-section centered, single-vortex acoustic streaming. A suspension of bacteria was also investigated to evaluate the biological relevance of the device, which demonstrated the alignment of bacteria in the channel at a flow rate of up to 20 µL min-1. The developed acoustofluidic device can align submicron particles within a narrow flow stream in a highly robust manner, validating its use as a flow-through focusing chamber to perform high-throughput and accurate flow cytometry of submicron objects.

Reagent Filming for Universal Point-of-Care Diagnostics.

Simplifying assays while maintaining the robustness of reagents is a challenge in diagnostics. This problem is exacerbated when translating quality diagnostic assays to developing countries that lack resources and infrastructure such as trained health workers, high-end equipment, and cold-chain systems. To solve this problem, in this study, a simple solution that films assay reagents to simplify the operation of diagnostic assays and preserve the stability of diagnostic reagents without using cold chains is presented. A polyvinyl-alcohol-based water-soluble film is used to encapsulate premeasured and premixed reagents. The reagent film, produced through a simple and scalable cast-drying process, provides a glassy inner matrix with abundant hydroxyl groups that can stabilize various reagents (ranging from chemicals to biological materials) by restricting molecular mobility and generating hydrogen bonds. The reagent film is applied to an enzymatic glucose assay, a high-sensitivity immunoassay for cardiac troponin, and a molecular assay for viral RNA detection, to test its practicability and universal applicability. The film-based assays result in excellent analytical/diagnostic performance and stable long-term reagent storage at elevated temperatures (at 25 or 37 °C, for six months), demonstrating clinical readiness. This technology advances the development and distribution of affordable high-quality diagnostics to resource-limited regions.

A rapid assay provides on-site quantification of tetrahydrocannabinol in oral fluid.

Tetrahydrocannabinol (THC), the primary psychoactive ingredient of cannabis, impairs cognitive and motor function in a concentration-dependent fashion. Drug testing is commonly performed for employment and law enforcement purposes; however, available tests produce low-sensitive binary results (lateral flow assays) or have long turnaround (gas chromatography­mass spectrometry). To enable on-site THC quantification in minutes, we developed a rapid assay for oral THC analysis called EPOCH (express probe for on-site cannabis inhalation). EPOCH features distinctive sensor design such as a radial membrane and transmission optics, all contained in a compact cartridge. This integrated approach permitted assay completion within 5 min with a detection limit of 0.17 ng/ml THC, which is below the regulatory guideline (1 ng/ml). As a proof of concept for field testing, we applied EPOCH to assess oral fluid samples from cannabis users (n = 43) and controls (n = 43). EPOCH detected oral THC in all specimens from cannabis smokers (median concentration, 478 ng/ml) and THC-infused food consumers. Longitudinal monitoring showed a fast drop in THC concentrations within the first 6 hours of cannabis smoking (half-life, 1.4 hours).

Genetic Differences between Physical Injury Patients With and Without Post-traumatic Syndrome: Focus on Secondary Findings and Potential Variants Revealed by Whole Exome Sequencing.

Objective: Sudden traumatic physical injuries often cause psychological distress, which may be associated with chronic disability. Although considerable effort has been expended to identify genetic predictors of post-traumatic stress disorder (PTSD) after traumatic events, genetic predictors of psychological distress in response to severe physical injuries have been yet to be elucidated using whole exome sequencing (WES). Here, the genetic architecture of post-traumatic syndrome (PTS), which encompasses a broad range of psychiatric disorders after traumatic events including depression, anxiety disorder, acute stress disorder, and PTSD, was explored using WES in severely physically injured patients, focusing on secondary findings and potential PTS-related variants. Methods: In total, 141 severely physically injured patients were consecutively recruited, and PTS was evaluated within 1 month of the injury. Secondary findings were analyzed according to PTS status. To identify PTS-related variants, genome-wide association analyses and the optimal sequencing kernel association test were performed. Results: Of the 141 patients, 88 (62%) experienced PTS. There were 108 disease-causing variants in severely physically injured patients. As secondary findings, the stress- and inflammation-related signaling pathways were enriched in the PTS patients, while the glucose metabolism pathway was enriched in those without PTS. However, no significant PTS-related variants were identified. Conclusion: Our findings suggest that genetic alterations in stress and inflammatory pathways might increase the likelihood of PTS immediately after severe physical injury. Future studies with larger samples and longitudinal designs are needed.