Farmed fur animals harbour viruses with zoonotic spillover potential.

Animals such as raccoon dogs, mink and muskrats are farmed for fur and are sometimes used as food or medicinal products1,2, yet they are also potential reservoirs of emerging pathogens3. Here we performed single-sample metatranscriptomic sequencing of internal tissues from 461 individual fur animals that were found dead due to disease. We characterized 125 virus species, including 36 that were novel and 39 at potentially high risk of cross-species transmission, including zoonotic spillover. Notably, we identified seven species of coronaviruses, expanding their known host range, and documented the cross-species transmission of a novel canine respiratory coronavirus to raccoon dogs and of bat HKU5-like coronaviruses to mink, present at a high abundance in lung tissues. Three subtypes of influenza A virus-H1N2, H5N6 and H6N2-were detected in the lungs of guinea pig, mink and muskrat, respectively. Multiple known zoonotic viruses, such as Japanese encephalitis virus and mammalian orthoreovirus4,5, were detected in guinea pigs. Raccoon dogs and mink carried the highest number of potentially high-risk viruses, while viruses from the Coronaviridae, Paramyxoviridae and Sedoreoviridae families commonly infected multiple hosts. These data also reveal potential virus transmission between farmed animals and wild animals, and from humans to farmed animals, indicating that fur farming represents an important transmission hub for viral zoonoses.

Zoonotic infections by avian influenza virus: changing global epidemiology, investigation, and control.

Avian influenza virus continues to pose zoonotic, epizootic, and pandemic threats worldwide, as exemplified by the 2020-23 epizootics of re-emerging H5 genotype avian influenza viruses among birds and mammals and the fatal jump to humans of emerging A(H3N8) in early 2023. Future influenza pandemic threats are driven by extensive mutations and reassortments of avian influenza viruses rooted in frequent interspecies transmission and genetic mixing and underscore the urgent need for more effective actions. We examine the changing global epidemiology of human infections caused by avian influenza viruses over the past decade, including dramatic increases in both the number of reported infections in humans and the spectrum of avian influenza virus subtypes that have jumped to humans. We also discuss the use of advanced surveillance, diagnostic technologies, and state-of-the-art analysis methods for tracking emerging avian influenza viruses. We outline an avian influenza virus-specific application of the One Health approach, integrating enhanced surveillance, tightened biosecurity, targeted vaccination, timely precautions, and timely clinical management, and fostering global collaboration to control the threats of avian influenza viruses.

Dual-domain mean-reverting diffusion model-enhanced temporal compressive coherent diffraction imaging.

Temporal compressive coherent diffraction imaging is a lensless imaging technique with the capability to capture fast-moving small objects. However, the accuracy of imaging reconstruction is often hindered by the loss of frequency domain information, a critical factor limiting the quality of the reconstructed images. To improve the quality of these reconstructed images, a method dual-domain mean-reverting diffusion model-enhanced temporal compressive coherent diffraction imaging (DMDTC) has been introduced. DMDTC leverages the mean-reverting diffusion model to acquire prior information in both frequency and spatial domain through sample learning. The frequency domain mean-reverting diffusion model is employed to recover missing information, while hybrid input-output algorithm is carried out to reconstruct the spatial domain image. The spatial domain mean-reverting diffusion model is utilized for denoising and image restoration. DMDTC has demonstrated a significant enhancement in the quality of the reconstructed images. The results indicate that the structural similarity and peak signal-to-noise ratio of images reconstructed by DMDTC surpass those obtained through conventional methods. DMDTC enables high temporal frame rates and high spatial resolution in coherent diffraction imaging.

Real-world applications of the new grading system in lung adenocarcinoma: A study of 907 patients focusing on revealing the relationship between pathologic grade and genetic status.

BACKGROUND: The status of the lung adenocarcinoma (LUAD) grading system and the association between LUAD differentiation, driver genes, and clinicopathological features remain to be elucidated. METHODS: We included patients with invasive non-mucinous LUAD, evaluated their differentiation, and collected available clinicopathological information, gene mutations, and analyzed clinical outcomes. RESULTS: Among the 907 patients with invasive non-mucinous LUAD, 321 (35.4 %) were poorly differentiated, 422 (46.5 %) were moderately differentiated, and 164 (18.1 %) were well differentiated. EGFR mutation was more common in the LUADs accompanied without CGP (complex glandular pattern) than LUADs with CGP (p < 0.001). Correlation analysis between mutations and clinical characteristics showed that EGFR gene mutation (p < 0.001), KRAS gene mutation (p < 0.05), and ALK gene rearrangement (p < 0.001) were significantly related to the degree of tumor differentiation, and the KRAS and ALK gene mutation frequencies were higher in the low-differentiation group than in the high and medium differentiation groups. The EGFR mutation frequency was higher in the well/moderately differentiated adenocarcinoma group. CONCLUSIONS: Our study adds to the evidence regarding the role of the grading system in prognosis. EGFR, KRAS, and ALK are related to the degree of tumor differentiation.

Entropy-Optimized Deep Weighted Product Quantization for Image Retrieval.

Hashing and quantization have greatly succeeded by benefiting from deep learning for large-scale image retrieval. Recently, deep product quantization methods have attracted wide attention. However, representation capability of codewords needs to be further improved. Moreover, since the number of codewords in the codebook depends on experience, representation capability of codewords is usually imbalanced, which leads to redundancy or insufficiency of codewords and reduces retrieval performance. Therefore, in this paper, we propose a novel deep product quantization method, named Entropy Optimized deep Weighted Product Quantization (EOWPQ), which not only encodes samples into the weighted codewords in a new flexible manner but also balances the codeword assignment, improving while balancing representation capability of codewords. Specifically, we encode samples using the linear weighted sum of codewords instead of a single codeword as traditionally. Meanwhile, we establish the linear relationship between the weighted codewords and semantic labels, which effectively maintains semantic information of codewords. Moreover, in order to balance the codeword assignment, that is, avoiding some codewords representing most samples or some codewords representing very few samples, we maximize the entropy of the coding probability distribution and obtain the optimal coding probability distribution of samples by utilizing optimal transport theory, which achieves the optimal assignment of codewords and balances representation capability of codewords. The experimental results on three benchmark datasets show that EOWPQ can achieve better retrieval performance and also show the improvement of representation capability of codewords and the balance of codeword assignment.

Codon usage bias analysis of the spike protein of human coronavirus 229E and its host adaptability.

Human coronavirus 229E (HCoV-229E) represents one of the known coronaviruses capable of infecting humans and causes mild respiratory symptoms. It is also considered to have a zoonotic source, originating from animals and being transmitted the humans. In this study, a comprehensive phylogenetic and codon usage analysis of the spike (S) gene of HCoV-229E was conducted. Utilizing phylogenetic analysis and principal component analysis, HCoV-229E was categorized into four distinct clusters, each demonstrating unique host affiliations. Furthermore, it was observed that the codon usage bias within the S gene of HCoV-229E is relatively low, primarily influenced by natural selection patterns, with contributions from mutation pressure and dinucleotide abundance. Comparative analysis involving Codon Adaptation Index (CAI) and Relative Codon Deoptimization Index (RCDI) revealed that the codon usage pattern of HCoV-229E mirrors more closely that of camels, as opposed to alpacas and humans. The elucidation of the codon usage pattern within HCoV-229E, which we have meticulously examined, offers valuable insights for a more comprehensive comprehension of viral features, history, and evolutionary trajectory.

Multi-phase FZA lensless imaging via diffusion model.

Lensless imaging shifts the burden of imaging from bulky and expensive hardware to computing, which enables new architectures for portable cameras. However, the twin image effect caused by the missing phase information in the light wave is a key factor limiting the quality of lensless imaging. Conventional single-phase encoding methods and independent reconstruction of separate channels pose challenges in removing twin images and preserving the color fidelity of the reconstructed image. In order to achieve high-quality lensless imaging, the multiphase lensless imaging via diffusion model (MLDM) is proposed. A multi-phase FZA encoder integrated on a single mask plate is used to expand the data channel of a single-shot image. The information association between the color image pixel channel and the encoded phase channel is established by extracting prior information of the data distribution based on multi-channel encoding. Finally, the reconstruction quality is improved through the use of the iterative reconstruction method. The results show that the proposed MLDM method effectively removes the influence of twin images and produces high-quality reconstructed images compared with traditional methods, and the results reconstructed using MLDM have higher structural similarity and peak signal-to-noise ratio.

QuatJND: A Robust Quaternion JND Model for Color Image Watermarking.

Robust quantization watermarking with perceptual JND model has made a great success for image copyright protection. Generally, either restores each color channel separately or processes the vector representation from three color channels with the traditional monochromatic model. And it cannot make full use of the high correlation among RGB channels. In this paper, we proposed a robust quaternion JND Model for color image watermarking (QuatJND). In contrast to the existing perceptual JND models, the advantage of QuatJND is that it can integrate quaternion representation domain and colorfulness simultaneously, and QuatJND incorporates the pattern guided contrast masking effect in quaternion domain. On the other hand, in order to efficiently utilize the color information, we further develop a robust quantization watermarking framework using the color properties of the quaternion DCT coefficients in QuatJND. And the quantization steps of each quaternion DCT block in the scheme are optimal. Experimental results show that our method has a good performance in term of robustness with better visual quality.

A System of Rapidly Detecting Escherichia Coli in Food Based on a Nanoprobe and Improved ATP Bioluminescence Technology.

Bacterial contamination is an important factor causing food security issues. Among the bacteria, Escherichia coli is one of the main pathogens of food-borne microorganisms. However, traditional bacterial detection approaches cannot meet the requirements of real-time and on-site detection. Thus, it is of great significance to develop a rapid and accurate detection of bacteria in food to ensure food safety and safeguard human health. The pathogen heat-treatment module was designed in this paper based on the techniques including nanoprobe, pathogen heat-treatment, graphene transparent electrode (GTE), and adenosine triphosphate (ATP) bioluminescence technology. The system mainly consists of two parts: one is the optical detection unit; the other is the data processing unit. And it can quickly and automatically detect the number of bacterial colonies in food such as milk etc. The system uses not only the probe to capture and enrich E. coli by antigen-antibody interaction but also the heat treatment to increase the amount of ATP released from bacterial cells within five minutes. To enhance the detecting accuracy and sensitivity, the electric field generated by GTE is adopted in the system to enrich ATP. Compared to the other conventional methods, the linear correlation coefficient of the system can be reached 0.975, and the system meets the design requirements. Under the optimal experimental conditions, the detection can be completed within 25 min, and the detectable concentration of bacteria is in the range of 3.1 × 101-106 CFU/mL. This system satisfies the demands of a fast and on-site inspection.

AMB-Wnet: Embedding attention model in multi-bridge Wnet for exploring the mechanics of disease.

In recent years, progressive application of convolutional neural networks in image processing has successfully filtered into medical diagnosis. As a prerequisite for images detection and classification, object segmentation in medical images has attracted a great deal of attention. This study is based on the fact that most of the analysis of pathological diagnoses requires nuclei detection as the starting phase for obtaining an insight into the underlying biological process and further diagnosis. In this paper, we introduce an embedded attention model in multi-bridge Wnet (AMB-Wnet) to achieve suppression of irrelevant background areas and obtain good features for learning image semantics and modality to automatically segment nuclei, inspired by the 2018 Data Science Bowl. The proposed architecture, consisting of the redesigned down sample group, up-sample group, and middle block (a new multiple-scale convolutional layers block), is designed to extract different level features. In addition, a connection group is proposed instead of skip-connection to transfer semantic information among different levels. In addition, the attention model is well embedded in the connection group, and the performance of the model is improved without increasing the amount of calculation. To validate the model's performance, we evaluated it using the BBBC038V1 data sets for nuclei segmentation. Our proposed model achieves 85.83% F1-score, 97.81% accuracy, 86.12% recall, and 83.52% intersection over union. The proposed AMB-Wnet exhibits superior results compared to the original U-Net, MultiResUNet, and recent Attention U-Net architecture.

Administration of Dexmedetomidine Does Not Produce Long-Term Protective Effect on Testicular Damage Post Testicular Ischemia-Reperfusion Injury.

BACKGROUND: After surgical correction of testicular torsion, up to 68% of ipsilateral testes undergo atrophy due to ischemia-reperfusion injury (IRI). Recent studies have shown that dexmedetomidine (Dex) alleviates IRI in various vital organs. However, those studies evaluated its protective effect on short-term reperfusion. PURPOSE: We aimed to investigate whether Dex has a long-term protective effect against testicular injury after IRI. MATERIALS AND METHODS: A total of 24 New Zealand white rabbits were randomly divided into three groups (n = 8/group): the control group (saline-infused rabbits without IRI), the IRI group (saline-injected rabbits with IRI), and the Dex group (Dex-injected rabbits with IRI). The spermatic cord of rabbits in IRI and Dex groups was ligated for 4 h, and 1 h before reperfusion, Dex was administered intraperitoneally at a dose of 50 µg/kg body weight in group Dex, whereas saline was administered at the same dose to the IRI and control groups. Rabbits were kept alive for 4 weeks post reperfusion, then the testes were harvested, and the rabbits were euthanized. RESULTS: Four weeks post reperfusion, testicular volumes of the affected side decreased considerably in the IRI and Dex groups compared to the control group, with no significant difference between the IRI and Dex groups. Compared to the control group, the Johnson score and the mean seminiferous tubular diameters were significantly decreased in the IRI and Dex groups, but no significant differences were observed after administration of Dex. There were no significant differences in malondialdehyde and superoxide dismutase levels between the groups treated with and without Dex. CONCLUSION: Dex administration 3 h after ischemia and 1 h before reperfusion did not demonstrate a significant protective effect against testicular injury 4 weeks after IRI in rabbits. Further research is needed to confirm the potential therapeutic effects of Dex by varying the experimental conditions.

HIF-1α interacts with Kindlin-2 and influences breast cancer elasticity: A study based on shear wave elastography imaging.

Breast cancer was the most frequent and the second most deadly cancer in women in 2018 in China; thus, early diagnosis of breast cancer is important. Studies have reported that tissue stiffness promotes cancer progression through increased collagen or fibrosis. Shear wave elastography (SWE) is a technique for measuring tissue stiffness. However, the mechanisms underlying cancer tissue stiffness or fibrosis are not entirely clear. Hypoxia-inducible factor 1 (HIF-1α) is expressed in response to hypoxia and contributes to tumor progression and metastasis. Kindlin-2 is an important co-activator of integrin. We have reported that Kindlin-2 influences breast cancer stiffness and metastasis. In this study, SWE was used to determine the maximum elasticity (Emax ) of patients before operation or core needle biopsy. The specimens were used for staining. Knockdown, overexpression, co-immunoprecipitation, and immunofluorescence assays were used to explore the relationship between HIF-1α and Kindlin-2. We found that HIF-1α and Kindlin-2 were highly expressed in invasive breast cancer and that the expression levels of HIF-1α and Kindlin-2 were correlated with Emax . HIF-1α interacts with Kindlin-2. Besides, HIF-1α and Kindlin-2 influence the expression of P4HA1, an important protein in collagen biogenesis through the integrin/FAK pathway. Our study first identified a new mechanism of invasive breast cancer stiffness by linking HIF-1α and Kindlin-2 to collagen biogenesis. Therefore, based on SWE, Emax could be a physical biomarker of invasive breast cancer for early, noninvasive diagnosis, and HIF-1α and Kindlin-2 could be pathological markers for early diagnosis and targeted therapy.

Simultaneous recovery of a full set of optical properties in turbid media using incomplete P5 approximation to CW radiance.

Traditional methods for determining the optical properties of turbid media are implemented in diffusive regimes, where the scattering coefficient µs and anisotropy factor g are inseparable due to the similarity relation for anisotropy scattering. Determining µs and g in addition to the absorption coefficient µa normally requires measurements using thin samples or media of low scattering, which are inappropriate for in vivo applications. In this work, we propose an analytical method to simultaneously recover µa, µs, and g based on the incomplete P5 approximation (P5in) to the continuous wave (CW) radiative transport equation. The proposed method was verified using both simulated and experimental data with the relative errors less than 6.6%, 11.6%, and 8.2% for µa ranging 0.0071-0.0168 mm-1, µs ranging 2.35-8.47 mm-1, and g ranging 0.61-0.81, respectively. Since the P5in-based radiance method can be easily implemented with several measurements, it is expected to be used for recovering a full set of the optical properties in vivo.

Repeatability of the "flash-replenishment" method in contrast-enhanced ultrasound for the quantitative assessment of hepatic microvascular perfusion.

This study aimed to evaluate the feasibility and repeatability of the flash-replenishment method in contrast-enhanced ultrasound (CEUS) perfusion imaging and assess quantitatively microvascular perfusion in the liver. Twenty healthy New Zealand rabbits were submitted to CEUS perfusion imaging with continuous intravenous infusion. Using flash-replenishment kinetics, the dynamic process of depletion and refilling of microbubble contrast agent was recorded. The hepatic microvascular perfusion parameters were calculated, including region of interest, peak intensity (PI), area under the curve (AUC), and hepatic artery to vein transit time (HA-HVTT). A consistency test was performed for multiple measurements by the same operator and blind measurements by two different operators. The hepatic perfusion imaging of 3×108 bubbles/min had minimal error and the best imaging effect and repeatability. The variability of the perfusion parameter measured at 3 cm depth under the liver capsule was at a minimum with coefficient of variation of 3.9%. The interclass correlation coefficient (ICC) of measurements taken by the same operator was 0.985, (95% confidence interval, CI=0.927-0.998). Measurements taken by two operators had good consistency and reliability, with the ICC of 0.948 (95%CI=0.853-0.982). The PI and AUC of liver parenchyma after reperfusion were lower than before blocking; and HA-HVTT was significantly longer than before blocking (P<0.05). The flash-replenishment method in CEUS perfusion imaging showed good stability and repeatability, which provide a valuable experimental basis for the quantitative assessment of hepatic microvascular perfusion in clinical practice.

Enhancing sparse-view photoacoustic tomography with combined virtually parallel projecting and spatially adaptive filtering.

To fully realize the potential of photoacoustic tomography (PAT) in preclinical and clinical applications, rapid measurements and robust reconstructions are needed. Sparse-view measurements have been adopted effectively to accelerate the data acquisition. However, since the reconstruction from the sparse-view sampling data is challenging, both the effective measurement and the appropriate reconstruction should be taken into account. In this study, we present an iterative sparse-view PAT reconstruction scheme, where a concept of virtual parallel-projection matching the measurement condition is introduced to aid the "compressive sensing" in the reconstruction procedure, and meanwhile, the non-local spatially adaptive filtering exploring the a priori information of the mutual similarities in natural images is adopted to recover the unknowns in the transformed sparse domain. Consequently, the reconstructed images with the proposed sparse-view scheme can be evidently improved in comparison to those with the universal back-projection method, for the cases of same sparse views. The proposed approach has been validated by the simulations and ex vivo experiments, which exhibits desirable performances in image fidelity even from a small number of measuring positions.

Repeatability of the "flash-replenishment" method in contrast-enhanced ultrasound for the quantitative assessment of hepatic microvascular perfusion

This study aimed to evaluate the feasibility and repeatability of the flash-replenishment method in contrast-enhanced ultrasound (CEUS) perfusion imaging and assess quantitatively microvascular perfusion in the liver. Twenty healthy New Zealand rabbits were submitted to CEUS perfusion imaging with continuous intravenous infusion. Using flash-replenishment kinetics, the dynamic process of depletion and refilling of microbubble contrast agent was recorded. The hepatic microvascular perfusion parameters were calculated, including region of interest, peak intensity (PI), area under the curve (AUC), and hepatic artery to vein transit time (HA-HVTT). A consistency test was performed for multiple measurements by the same operator and blind measurements by two different operators. The hepatic perfusion imaging of 3×108 bubbles/min had minimal error and the best imaging effect and repeatability. The variability of the perfusion parameter measured at 3 cm depth under the liver capsule was at a minimum with coefficient of variation of 3.9%. The interclass correlation coefficient (ICC) of measurements taken by the same operator was 0.985, (95% confidence interval, CI=0.927-0.998). Measurements taken by two operators had good consistency and reliability, with the ICC of 0.948 (95%CI=0.853-0.982). The PI and AUC of liver parenchyma after reperfusion were lower than before blocking; and HA-HVTT was significantly longer than before blocking (P<0.05). The flash-replenishment method in CEUS perfusion imaging showed good stability and repeatability, which provide a valuable experimental basis for the quantitative assessment of hepatic microvascular perfusion in clinical practice.

Determination of optical properties of turbid medium from relative interstitial CW radiance measurements using the incomplete P3 approximation.

Interstitial determination of the tissue optical properties is important in biomedicine, especially for interstitial laser therapies. Continuous wave (CW) radiance techniques which examine light from multiple directions have been proposed as minimally invasive methods for determining the optical properties under an interstitial probe arrangement. However, both the fitting algorithm based on the P3 approximation and the analytical method based on the diffusion approximation (DA), which are currently used recovery algorithms, cannot extract the optical properties of tissue with low transport albedos accurately from radiance measurements. In this paper, we proposed an incomplete P3 approximation for the radiance, the P3in for short, which is the asymptotic part of the solution for the P3 approximation. The relative differences between the P3in and the P3 were within 0.48% over a wide range of clinically relevant optical properties for measurements at source detector separations (SDS) from 5 mm to 10 mm and angles from 0° to 160°. Based on the P3in, we developed an analytical method for extracting the optical properties directly using simple expressions constructed from the radiance measurements at only two SDSs and four angles. The developed recovery algorithm was verified by simulated and experimental radiance data. The results show that both the absorption and reduced scattering coefficients were recovered accurately with relative errors within 5.28% and 3.86%, respectively, from the simulated data and with relative errors within 10.82% and 10.67%, respectively, from the experimental data over a wide range of albedos from 0.5 to 0.99. Since the developed P3in-based radiance technique can obtain the optical properties rapidly from the measurements at only two SDSs and four angles, it is expected to be used for in vivo and in situ determination of the optical properties in online treatment planning during laser therapies.

Kindlin-2 could influence breast nodule elasticity and improve lymph node metastasis in invasive breast cancer.

This study investigated the relationship between quantitative parameters of shear wave elastography (SWE, maximum elasticity [Emax], minimum elasticity [Emin], mean elasticity [Emean]), collagen intensity and Kindlin-2 expression in benign and malignant breast nodules, and if Kindlin-2 expression is related with lymph node metastasis. A total of 102 breast nodules from 102 patients were included in our study who underwent ultrasound elastography before surgery or core needle biopsy. There was a significant difference between benign and malignant breast nodules in Emax, Emean, collagen intensity and Kindlin-2 expression, but it had no difference in Emin. Collagen intensity and Kindlin-2 expression both correlated positively with Emax, but not with Emean. Among 38 malignant breast nodules, the average Emax of the metastasis group was higher than that of the non-metastasis group, but it had no statistical significance. Compared with the non-metastasis group, Kindlin-2 expression was considerably higher in the metastasis group. However, there was no difference in collagen intensity between the metastasis group and the non-metastasis group. In conclusion, Kindlin-2 and collagen might contribute to breast nodule elasticity through molecular mechanisms. In breast cancer, overexpression of Kindlin-2 might be a risk factor for lymph node metastasis.

An Lp (0 ≤ p ≤ 1)-norm regularized image reconstruction scheme for breast DOT with non-negative-constraint.

BACKGROUND: In diffuse optical tomography (DOT), the image reconstruction is often an ill-posed inverse problem, which is even more severe for breast DOT since there are considerably increasing unknowns to reconstruct with regard to the achievable number of measurements. One common way to address this ill-posedness is to introduce various regularization methods. There has been extensive research regarding constructing and optimizing objective functions. However, although these algorithms dramatically improved reconstruction images, few of them have designed an essentially differentiable objective function whose full gradient is easy to obtain to accelerate the optimization process. METHODS: This paper introduces a new kind of non-negative prior information, designing differentiable objective functions for cases of L1-norm, Lp (0 < p < 1)-norm and L0-norm. Incorporating this non-negative prior information, it is easy to obtain the gradient of these differentiable objective functions, which is useful to guide the optimization process. RESULTS: Performance analyses are conducted using both numerical and phantom experiments. In terms of spatial resolution, quantitativeness, gray resolution and execution time, the proposed methods perform better than the conventional regularization methods without this non-negative prior information. CONCLUSIONS: The proposed methods improves the reconstruction images using the introduced non-negative prior information. Furthermore, the non-negative constraint facilitates the gradient computation, accelerating the minimization of the objective functions.

Region-based diffuse optical tomography with registered atlas: in vivo acquisition of mouse optical properties.

The reconstruction quality in the model-based optical tomography modalities can greatly benefit from a priori information of accurate tissue optical properties, which are difficult to be obtained in vivo with a conventional diffuse optical tomography (DOT) system alone. One of the solutions is to apply a priori anatomical structures obtained with anatomical imaging systems such as X-ray computed tomography (XCT) to constrain the reconstruction process of DOT. However, since X-ray offers low soft-tissue contrast, segmentation of abdominal organs from sole XCT images can be problematic. In order to overcome the challenges, the current study proposes a novel method of recovering a priori organ-oriented tissue optical properties, where anatomical structures of an in vivo mouse are approximately obtained by registering a standard anatomical atlas, i.e., the Digimouse, to the target XCT volume with the non-rigid image registration, and, in turn, employed to guide DOT for extracting the optical properties of inner organs. Simulative investigations have validated the methodological availability of such atlas-registration-based DOT strategy in revealing both a priori anatomical structures and optical properties. Further experiments have demonstrated the feasibility of the proposed method for acquiring the organ-oriented tissue optical properties of in vivo mice, making it as an efficient way of the reconstruction enhancement.