Rare Earth Doping Engineering Tailoring Advanced Oxygen-Vacancy Co3 O4 with Tunable Structures for High-Efficiency Energy Storage.

Co3 O4  with high theoretical capacitance is a promising electrode material for high-end energy applications, yet the unexcited bulk electrochemical activity, low conductivity, and poor kinetics of Co3 O4  lead to unsatisfactory charge storage capacity. For boosting its energy storage capability, rare earth (RE)-doped Co3 O4  nanostructures with abundant oxygen vacancies are constructed by simple, economical, and universal chemical precipitation. By changing different types of RE (RE = La, Yb, Y, Ce, Er, Ho, Nd, Eu) as dopants, the RE-doped Co3 O4  nanostructures can be well transformed from large nanosheets to coiled tiny nanosheets and finally to ultrafine nanoparticles, meanwhile, their specific surface area, pore distribution, the ratio of Co2+ /Co3+ , oxygen vacancy content, crystalline phase, microstrain parameter, and the capacitance performance are regularly affected. Notably, Eu-doped Co3 O4  nanoparticles with good cycle stability show a maximum specific capacitance of 1021.3 F g-1 (90.78 mAh g-1 ) at 2 A g-1 , higher than 388 F g-1 (34.49 mAh g-1 ) of pristine Co3 O4  nanosheets. The assembling asymmetric supercapacitor delivers a high energy density of 48.23 Wh kg-1  at high power density of 1.2 kW kg-1 . These findings denote the significance and great potential of RE-doped Co3 O4  in the development of high-efficiency energy storage.

Self super-resolution of optical coherence tomography images based on deep learning.

As a medical imaging modality, many researches have been devoted to improving the resolution of optical coherence tomography (OCT). We developed a deep-learning based OCT self super-resolution (OCT-SSR) pipeline to improve the axial resolution of OCT images based on the high-resolution and low-resolution spectral data collected by the OCT system. In this pipeline, the enhanced super-resolution asymmetric generative adversarial networks were built to improve the network outputs without increasing the complexity. The feasibility and effectiveness of the approach were demonstrated by experimental results on the images of the biological samples collected by the home-made spectral-domain OCT and swept-source OCT systems. More importantly, we found the sidelobes in the original images can be obviously suppressed while improving the resolution based on the OCT-SSR method, which can help to reduce pseudo-signal in OCT imaging when non-Gaussian spectra light source is used. We believe that the OCT-SSR method has broad prospects in breaking the limitation of the source bandwidth on the axial resolution of the OCT system.

Multiscale reconstruction of bronchus and cancer cells in human lung adenocarcinoma.

BACKGROUND: While previous studies primarily focused on the structure of the normal whole mouse lung, the whole bronchus and cytoarchitectural details of the mouse intact lung lobe have been discovered at single-cell resolution. Revealing the sophisticated lung adenocarcinoma structure at three-dimensional (3D) and single-cell level remains a fundamental and critical challenge for the pathological mechanism research of lung adenocarcinoma (LA). METHODS: Fluorescence micro-optical Sectioning Tomography (fMOST) combined with PI staining were used to obtain the 3D imaging of the human LA tissue at single-cell resolution. RESULTS: With a spatial resolution of 0.32 × 0.32 × 1.0 µm3, the dataset of human LA with single-cell precision consists of two channels, each of which contains information about the bronchi and the cytoarchitecture. The bronchial wall is thicker and the lumen is smaller in the cancer tissue, in which its original normal structure is vanished. More solid components, more clustered cancer cells with larger nucleoli, and more significant atypia are found in cancer tissue. In paracancerous tissue, the bronchial wall cells have a monolayer or bilayer structure, cluster along the wall, and are relatively dispersed. Few fibrous structures and occasional dissemination of spread through air spaces (STAS) are observed. CONCLUSIONS: Based on the human LA tissue dataset obtained by fMOST and PI staining, the bronchi and cells were reconstructed and visualized. This work provides a technical roadmap for studying the bronchus and cytoarchitectural structure and their spatial relationship in LA tissue, which may help with the understanding of the main histological structure of LA among pathologists.

Identification of oral precancerous and cancerous tissue by swept source optical coherence tomography.

BACKGROUND AND OBJECTIVES: Distinguishing cancer from precancerous lesions is critical and challenging in oral medicine. As a noninvasive method, optical coherence tomography (OCT) has the advantages of real-time, in vivo, and large-depth imaging. Texture information hidden in OCT images can provide an important auxiliary effect for improving diagnostic accuracy. The aim of this study is to explore a reliable and accurate OCT-based method for the screening and diagnosis of human oral diseases, especially oral cancer. MATERIALS AND METHODS: Fresh ex vivo oral tissues including normal mucosa, leukoplakia with epithelial hyperplasia (LEH), and oral squamous cell carcinoma (OSCC) were imaged intraoperatively by a homemade OCT system, and 58 texture features were extracted to create computational models of these tissues. A principal component analysis algorithm was employed to optimize the combination of texture feature vectors. The identification based on artificial neural network (ANN) was proposed and the sensitivity/specificity was calculated statistically to evaluate the classification performance. RESULTS: A total of 71 sites of three types of oral tissues were measured, and 5176 OCT images of three types of oral tissues were used in this study. The superior classification result based on ANN was obtained with an average accuracy of 98.17%. The sensitivity and specificity of normal mucosa, LEH, and OSCC are 98.17% / 98.38%, 93.81% / 98.54%, and 98.11% / 99.04%, respectively. CONCLUSION: It is demonstrated from the high accuracies, sensitivities, and specificities that texture-based analysis can be used to identify oral precancerous and cancerous tissue in OCT images, and it has the potential to help surgeons in diseases screening and diagnosis effectively.

Classification of neck tissues in OCT images by using convolutional neural network.

Identification and classification of surrounding neck tissues are very important in thyroid surgery. The advantages of optical coherence tomography (OCT), high resolution, non-invasion, and non-destruction make it have great potential in identifying different neck tissues during thyroidectomy. We studied the automatic classification for neck tissues in OCT images based on convolutional neural network in this paper. OCT images of five kinds of neck tissues were collected firstly by our home-made swept source (SS-OCT) system, and a dataset was built for neural network training. Three image classification neural networks: LeNet, VGGNet, and ResNet, were used to train and test the dataset. The impact of transfer learning on the classification of neck tissue OCT images was also studied. Through the comparison of accuracy, it was found that ResNet has the best classification accuracy among the three networks. In addition, transfer learning did not significantly improve the accuracy, but it can somewhat accelerate the convergence of the network and shorten the network training time.

Classification of oral salivary gland tumors based on texture features in optical coherence tomography images.

Currently, the diagnoses of oral diseases primarily depend on the visual recognition of experienced clinicians. It has been proven that automatic recognition based on images can support clinical decision-making by extracting and analyzing objective hidden information. In recent years, optical coherence tomography (OCT) has become a powerful optical imaging technique with the advantages of high resolution and non-invasion. In our study, a dataset composed of four kinds of oral salivary gland tumors (SGTs) was obtained from a homemade swept-source OCT, including two benign and two malignant tumors. Seventy-six texture features were extracted from OCT images to create computational models of diseases. It was demonstrated that the artificial neural network (ANN) based on principal component analysis (PCA) can obtain high diagnostic sensitivity and specificity (higher than 99%) for these four kinds of tumors. The classification accuracy of each tumor is larger than 99%. In addition, the performances of two classifiers (ANN and support vector machine) were quantitatively evaluated based on SGTs. It was proven that the texture features in OCT images provided objective information to classify oral tumors.

Classification of Salivary Gland Tumors Based on Quantitative Optical Coherence Tomography.

BACKGROUND AND OBJECTIVES: Visual inspection is the primary diagnostic method for oral diseases, and its accuracy of diagnosis mainly depends on surgeons' experience. Histological examination is still the golden standard, but it is invasive and time-consuming. In order to address these issues, as a noninvasive imaging technique, optical coherence tomography (OCT) can differentiate oral tissue with advantages of real-time, in situ, and high resolution. The aim of this study is to explore optimal quantitative parameters in OCT images to distinguish different salivary gland tumors. STUDY DESIGN/MATERIALS AND METHODS: OCT images of four salivary gland tumors were obtained from 14 patients, including mucoepidermoid carcinoma (MC), adenoid cystic carcinoma (ACC), basal cell adenoma (BCA), and pleomorphic adenoma (PA). Two parameters of optical attenuation coefficient (OAC) and standard deviation (SD) along the depth of OCT signal were combined to create a computational model of classification, and sensitivity/specificity of classification was calculated statistically to evaluate their results. RESULTS: A total of 5,919 two-dimensional (2D) OCT images were used for quantitative analysis. The classification sensitivities of 89.6%, 95.0%, 89.5%, 97.8%, and specificities of 97.6%, 99.0%, 98.0%, 98.2%, respectively, were obtained for MC, ACC, BCA, and PA, with the thresholds of 3.6 mm-1 based on OAC and 0.22/0.18 based on SD. CONCLUSION: It was demonstrated that OAC and SD could be considered as important parameters in quantitative analysis of OCT images for salivary gland tissue characterization and intraoperative diagnosis. It is of great potential value in promoting the application of this method based on OCT in clinical practice. Lasers Surg. © 2020 Wiley Periodicals LLC.

Multimodal imaging with integrated auto-fluorescence and optical coherence tomography for identification of neck tissues.

We report a multimodal optical system by combining OCT with autofluorescence imaging for identifying neck tissues, which can use the advantages of large field of view and high sensitivity for identifying parathyroid glands of fluorescence imaging, and high-resolution structural imaging of OCT to confirm them and identify lymph nodes and metastatic lymph nodes at the same time. It is proven that this multimodal optical system can be used to identify different neck tissues effectively and efficiently. We think that integrated auto-fluorescence and OCT imaging have the great potential in the application of navigation and assistant diagnosis of thyroid surgery.

Enhancing the selectivity of liquid chromatography-mass spectrometry by using trilinear decomposition on LC-MS data: An application to three-way calibration of coeluting analytes in human plasma.

The high selectivities of liquid chromatography and mass spectrometry make liquid chromatography-mass spectrometry one of the most popular tools for quantitative analysis in complex chemical, biological, and environmental systems, while the potential mathematical selectivity of liquid chromatography-mass spectrometry is rarely investigated. This work discussed the mathematical selectivity of liquid chromatography-mass spectrometry by three-way calibration based on the trilinear model, with an application to quantitative analysis of coeluting aromatic amino acids in human plasma. By the trilinear decomposition of the constructed liquid chromatography-mass spectrometry-sample trilinear model and individual regression of the decomposed relative intensity versus concentration, the proposed three-way calibration method successfully achieved quantitative analysis of coeluting aromatic amino acids in human plasma, even in the presence of uncalibrated interferent(s) and a varying background. This analytical method can ease the requirements for sample preparation and complete chromatographic separation of components, reduce the use of organic solvents, decrease the time of chromatographic separation, and increase the peak capacity of liquid chromatography-mass spectrometry. As a "green analytical method", the liquid chromatography-mass spectrometry three-way calibration method can provide a promising tool for direct and fast quantitative analysis in complex systems containing uncalibrated spectral interferents, especially for the situation where the coelution problem is difficult to overcome.

Chlamydia trachomatis Infection, when Treated during Pregnancy, Is Not Associated with Preterm Birth in an Urban Safety-Net Hospital.

Preterm birth is a major public health problem, occurring in more than half a million births per year in the United States. A number of maternal conditions have been recognized as risk factors for preterm birth, but for the majority of cases, the etiology is not completely understood. Chlamydia trachomatis is one of the most prevalent sexually transmitted infections in the world. However, its role in adverse pregnancy outcome in women is still debated. In order to determine if genitourinary tract infection with C. trachomatis during pregnancy was associated with preterm birth, we conducted a case-control study on women who delivered at Boston Medical Center, an urban "safety-net" hospital that serves a socioeconomically disadvantaged and racially diverse population. Women with known risk factors for preterm birth or immune suppression were excluded. Variables collected on enrolled subjects included demographics; diagnosis of C. trachomatis during or prior to pregnancy; tobacco, alcohol, and illicit substance use; gestational age; and birthweight and gender of the newborn. We also collected urine for chlamydia testing at the time of delivery and placental biopsies for nucleic acid amplification and histological studies. A total of 305 subjects were enrolled: 100 who delivered preterm and 205 who delivered full term. Among those subjects, we identified 19 cases of pregnancy-associated C. trachomatis infection: 6/100 preterm and 13/205 full term, a difference which was not statistically significant. Only two cases of untreated chlamydia infection were identified postpartum, and both occurred in women who delivered at term. We conclude that genitourinary tract infection with C. trachomatis during pregnancy, when appropriately treated, is not associated with preterm birth.

Identification of oral cancer in OCT images based on an optical attenuation model.

Surgery is still the first choice to treat oral cancer, where it is important to detect surgical margins in order to reduce cancer recurrence and maintain oral-maxillofacial function simultaneously. As a non-invasive and in situ imaging technique, optical coherence tomography (OCT) can obtain images close to the resolution of histopathology, which makes it have great potential in intraoperative diagnosis. However, it is not enough to find surgical margins accurately just observing OCT images directly and qualitatively. The purpose of this study is to identify oral cancer in OCT images by investigating the quantitative difference of cancer and non-cancer tissue. Based on an available optical attenuation model and the axial confocal PSF of a home-made swept source OCT system, by using fresh ex vivo human oral tissues from 14 patients of oral squamous cell carcinoma (OSCC) as the samples, diagnosis with sensitivity (97.88%) and specificity (83.77%) was achieved at the attenuation threshold of 4.7 mm-1, and the accuracy of identification reached 91.15% in our study. Our preliminary results demonstrated that the oral cancer resection will be guided accurately and the clinical application of OCT will be further promoted by deeply mining the information hidden in OCT images.

Symmetrical illumination based extending depth of field in Fourier ptychographic microscopy.

Fourier ptychographic microscopy (FPM), simply replacing the traditional light source of a microscope with a LED array, can obtain high resolution and large field of view images simultaneously. A symmetrical LED illumination FPM is presented to improve the quality of high resolution images for defocus or thick samples in this paper. It is proven theoretically that symmetrical LED illumination had higher defocus tolerance than that of single LED illumination at first. Then, it is confirmed that symmetrical LED illumination FPM has better low-resolution images and reconstruction effect for defocus samples than that of single LED illumination by simulated and experimental results. Compared with the single illumination FPM, it is demonstrated that the depth of field of symmetrical FPM is more than doubled.

Detection of laser-induced bulk damage in optical crystals by swept-source optical coherence tomography.

An approach to characterize laser-induced bulk damage in optical crystal materials was demonstrated. With a homemade swept-source optical coherence tomography (SS-OCT) system, we obtained three-dimensional images of the bulk damage produced by laser pulses with wavelength of 351 nm, pulse width of 5 ns, beam diameter of 5.5 mm and fluences from 4.56 J/cm2 to 9.95 J/cm2 in Potassium Dihydrogen Phosphate (KDP) crystal. Algorithms based on three-dimensional OCT images were specially designed to count and locate bulk damage pinpoints in KDP crystal, obtaining their equivalent diameter distribution and pinpoint density caused by different fluences. It is demonstrated that the characteristics of bulk damage detected by SS-OCT are similar to those obtained by available approaches. The rapid three-dimensional imaging by SS-OCT provides a new approach of detecting laser-induced bulk damage.

MiR-218 produces anti-tumor effects on cervical cancer cells in vitro.

BACKGROUND: As indoleamine-2,3-dioxygenase 1 (IDO1) is critical in tumor immune escape, we determined to study the regulatory mechanism of miR-218 on IDO1 in cervical cancer. METHODS: Real-time PCR (RT-qPCR) was carried out to measure the expression of miR-218. RT-qPCR and Western blot were performed to detect the expression of IDO1 in cervical cancer. Dual-luciferase reporter assay was used to determine the binding of miR-218 on the IDO1 3'UTR. Cell viability, apoptosis, and related factors were determined using cell counting kit-8 (CCK-8), Annexin-V/PI (propidium) assay, enzyme-linked immunosorbnent assay (ELISA), RT-qPCR, and Western blot assays after miR-218 mimics has been transfected to HeLa cervical cancer cells. RESULTS: MiR-218 was downregulated in cervical cancer. The expression of miR-218 was negatively correlated with IDO1 in cervical cancer tissues and cells. IDO1 is a direct target of miR-218. MiR-218 overexpression was found to inhibit cell viability and promoted apoptosis via activating the expression of Cleaved-Caspase-3 and to inhibit the expression of Survivin, immune factors (TGF-ß, VEGF, IL-6, PGE2, COX-2), and JAK2/STAT3 pathway. CONCLUSION: MiR-218 inhibits immune escape of cervical cancer cells by direct downregulating IDO1.

Automatic identification of parathyroid in optical coherence tomography images.

BACKGROUND AND OBJECTIVE: The identification and preservation of parathyroid is a major problem in thyroid surgery. In order to solve this problem, optical coherence tomography was involved as a real-time, non-invasive high-resolution imaging technique. This study demonstrated an effective and fast method to distinguish parathyroid tissue from thyroid, lymph node, and adipose tissue in their ex vivo optical coherence tomography (OCT) images automatically. METHODS: OCT images were obtained from parathyroid, thyroid, lymph node, and adipose tissue, respectively. A classification and an identification system based on texture features analysis and back propagation artificial neural network (BP-ANN) were established to classify the four types of tissue and identify each of the four types automatically. RESULTS: A total of 248 OCT images were taken from 16 patients undergoing thyroidectomy. The accuracy of classification for parathyroid, thyroid, lymph node, and adipose were 99.21, 98.43, 97.65, and 98.43%, respectively. CONCLUSION: The proposed automatic identification method is capable of distinguishing among parathyroid, thyroid, lymph, and adipose automatically and effectively. Compared with the identification results of human, it has a better accuracy and reliability. For identifying parathyroid from the other entities, it has a satisfying performance. Lasers Surg. Med. 49:305-311, 2017. © 2017 Wiley Periodicals, Inc.

A regulator from Chlamydia trachomatis modulates the activity of RNA polymerase through direct interaction with the beta subunit and the primary sigma subunit.

The obligate intracellular human pathogen Chlamydia trachomatis undergoes a complex developmental program involving transition between two forms: the infectious elementary body (EB), and the rapidly dividing reticulate body (RB). However, the regulators controlling this development have not been identified. To uncover potential regulators of transcription in C. trachomatis, we screened a C. trachomatis genomic library for sequences encoding proteins that interact with RNA polymerase (RNAP). We report the identification of one such protein, CT663, which interacts with the beta and sigma subunits of RNAP. Specifically, we show that CT663 interacts with the flap domain of the beta subunit (beta-flap) and conserved region 4 of the primary sigma subunit (sigma(66) in C. trachomatis). We find that CT663 inhibits sigma(66)-dependent (but not sigma(28)-dependent) transcription in vitro, and we present evidence that CT663 exerts this effect as a component of the RNAP holoenzyme. The analysis of C. trachomatis-infected cells reveals that CT663 begins to accumulate at the commencement of the RB-to-EB transition. Our findings suggest that CT663 functions as a negative regulator of sigma(66)-dependent transcription, facilitating a global change in gene expression. The strategy used here is generally applicable in cases where genetic tools are unavailable.

Comparative analysis of the growth and biological activity of a respiratory and atheroma isolate of Chlamydia pneumoniae reveals strain-dependent differences in inflammatory activity and innate immune evasion.

BACKGROUND: Chlamydia pneumoniae is a common human pathogen that is associated with upper and lower respiratory tract infections. It has also been suggested that C. pneumoniae infection can trigger or promote a number of chronic inflammatory conditions, including asthma and atherosclerosis. Several strains of C. pneumoniae have been isolated from humans and animals, and sequence data demonstrates marked genetic conservation, leaving unanswered the question as to why chronic inflammatory conditions may occur following some respiratory-acquired infections. METHODS: C. pneumoniae strains AR39 and AO3 were used in vitro to infect murine bone marrow derived macrophages and L929 fibroblasts, or in vivo to infect C57BL/6 mice via the intranasal route. RESULTS: We undertook a comparative study of a respiratory isolate, AR39, and an atheroma isolate, AO3, to determine if bacterial growth and host responses to infection varied between these two strains. We observed differential growth depending on the host cell type and the growth temperature; however both strains were capable of forming plaques in vitro. The host response to the respiratory isolate was found to be more inflammatory both in vitro, in terms of inflammatory cytokine induction, and in vivo, as measured by clinical response and lung inflammatory markers using a mouse model of respiratory infection. CONCLUSIONS: Our data demonstrates that a subset of C. pneumoniae strains is capable of evading host innate immune defenses during the acute respiratory infection. Further studies on the genetic basis for these differences on both the host and pathogen side could enhance our understanding how C. pneumoniae contributes to the development chronic inflammation at local and distant sites.

Immuno-evasive tactics by schistosomes identify an effective allergy preventative.

Many chronic inflammatory diseases can be improved by helminth infection, but the mechanisms are poorly understood. Allergy and helminthiasis are both associated with Th2-like immune responses; thus, defining how infection with parasites leads to reduced allergy has been particularly challenging. We sought to better understand this conundrum by evaluating host-parasite interactions involved in Th2 immunity in human schistosomiasis. Immune cells were cultured with schistosomes and the effect on CD23, an IgE receptor associated with resistance in schistosomiasis, was evaluated. Cells treated with schistosomes demonstrated reduced surface CD23 levels with a parallel accumulation of soluble (s) CD23 suggesting this IgE receptor is proteolytically cleaved by the parasite. Consistent with this hypothesis, a schistosome-generated (SG)-sCD23 fragment of 15 kDa was identified. SG-sCD23 inhibited IgE from binding to CD23 and FcεRI, but lacked the ability to bind CD21. These results suggested that schistosomes target IgE-mediated immunity in immuno-evasive tactics. Based on its characteristics, we predicted that SG-sCD23 would function as an efficacious allergy preventative. Treatment of human FcεRI-transgenic mice with recombinant (r) SG-sCD23 reduced the ability of human IgE to induce an acute allergic response in vivo. In addition, an optimized form of rSG-sCD23 with an introduced point mutation at Asp258 (D258E)to stabilize IgE binding had increased efficacy compared to native rSG-sCD23. Schistosome infection may thus inhibit allergic-like protective immune responses by increasing soluble IgE decoy receptors. Allergy treatments based on this naturally occurring phenomenon may be highly effective and have fewer side effects with long-term use.

Enhancement of OCTen faceimages by unsupervised deep learning.

Objective. The quality of optical coherence tomography (OCT)en faceimages is crucial for clinical visualization of early disease. As a three dimensional and coherent imaging, defocus and speckle noise are inevitable, which seriously affect evaluation of microstructure of bio-samples in OCT images. The deep learning has demonstrated great potential in OCT refocusing and denoising, but it is limited by the difficulty of sufficient paired training data. This work aims to develop an unsupervised method to enhance the quality of OCTen faceimages.Approach. We proposed an unsupervised deep learning-based pipeline. The unregistered defocused conventional OCT images and focused speckle-free OCT images were collected by a home-made speckle modulating OCT system to construct the dataset. The image enhancement model was trained with the cycle training strategy. Finally, the speckle noise and defocus were both effectively improved.Main results. The experimental results on complex bio-samples indicated that the proposed method is effective and generalized in enhancing the quality of OCTen faceimages.Significance. The proposed unsupervised deep learning method helps to reduce the complexity of data construction, which is conducive to practical applications in OCT bio-sample imaging.

Salinity decreases the contribution of microbial necromass to soil organic carbon pool in arid regions.

Saline soils are widely distributed in arid areas but there is a lack of mechanistic understanding on the effect of salinity on the formation and biochemical composition of soil organic carbon (SOC). We investigated the effects of salinity on the accumulation of microbial necromass under natural vegetation and in cropland in salt-affected arid areas stretching over a 1200-km transect in northwest China. Under both natural vegetation and cropland, microbial physiological activity (indicated by microbial biomass carbon normalized enzymatic activity) decreased sharply where the electrical conductivity approached 4 ds m-1 (a threshold to distinguish between saline and non-saline soils), but microbial biomass was only slightly affected by salinity. These indicated that a larger proportion of microbes could be inactive or dormant in saline soils. The contribution of fungal necromass C to SOC decreased but the contribution of bacterial necromass C to the SOC increased with increasing soil salinity. Adding fungal and bacterial necromass C together, the contribution of microbial necromass C to SOC in saline soils was 32-39 % smaller compared with non-saline soils. Fungal necromass C took up 85-86 % of microbial necromass C in non-saline soils but this proportion dropped to 60-66 % in saline soils. We suggested that the activity, growth, and turnover rate of microbes slowed by salinity was responsible for the decreased accumulation of fungal necromass in saline compared with non-saline soils, while the increased accumulation of bacterial residue in saline soils could be induced mainly by its slower decomposition. Soil microbial biomass was a poor predictor for the accumulation of microbial necromass in saline soils. We demonstrated a reduced contribution of microbial necromass to SOC and a shift in its composition towards the increase in bacterial origin in saline relative to non-saline soils. We concluded that salinity profoundly changes the biochemistry of SOC in arid regions.