Computational pathology model to assess acute and chronic transformations of the tubulointerstitial compartment in renal allograft biopsies.

Managing patients with kidney allografts largely depends on biopsy diagnosis which is based on semiquantitative assessments of rejection features and extent of acute and chronic changes within the renal parenchyma. Current methods lack reproducibility while digital image data-driven computational models enable comprehensive and quantitative assays. In this study we aimed to develop a computational method for automated assessment of histopathology transformations within the tubulointerstitial compartment of the renal cortex. Whole slide images of modified Picrosirius red-stained biopsy slides were used for the training (n = 852) and both internal (n = 172) and external (n = 94) tests datasets. The pipeline utilizes deep learning segmentations of renal tubules, interstitium, and peritubular capillaries from which morphometry features were extracted. Seven indicators were selected for exploring the intrinsic spatial interactions within the tubulointerstitial compartment. A principal component analysis revealed two independent factors which can be interpreted as representing chronic and acute tubulointerstitial injury. A K-means clustering classified biopsies according to potential phenotypes of combined acute and chronic transformations of various degrees. We conclude that multivariate analyses of tubulointerstitial morphometry transformations enable extraction of and quantification of acute and chronic components of injury. The method is developed for renal allograft biopsies; however, the principle can be applied more broadly for kidney pathology assessment.

Mitochondria-derived reactive oxygen species are the likely primary trigger of mitochondrial retrograde signaling in Arabidopsis.

Besides their central function in respiration, plant mitochondria play a crucial role in maintaining cellular homeostasis during stress by providing "retrograde" feedback to the nucleus. Despite the growing understanding of this signaling network, the nature of the signals that initiate mitochondrial retrograde regulation (MRR) in plants remains unknown. Here, we investigated the dynamics and causative relationship of a wide range of mitochondria-related parameters for MRR, using a combination of Arabidopsis fluorescent protein biosensor lines, in vitro assays, and genetic and pharmacological approaches. We show that previously linked physiological parameters, including changes in cytosolic ATP, NADH/NAD+ ratio, cytosolic reactive oxygen species (ROS), pH, free Ca2+, and mitochondrial membrane potential, may often be correlated with-but are not the primary drivers of-MRR induction in plants. However, we demonstrate that the induced production of mitochondrial ROS is the likely primary trigger for MRR induction in Arabidopsis. Furthermore, we demonstrate that mitochondrial ROS-mediated signaling uses the ER-localized ANAC017-pathway to induce MRR response. Finally, our data suggest that mitochondrially generated ROS can induce MRR without substantially leaking into other cellular compartments such as the cytosol or ER lumen, as previously proposed. Overall, our results offer compelling evidence that mitochondrial ROS elevation is the likely trigger of MRR.

Intratumoral heterogeneity of Ki67 proliferation index outperforms conventional immunohistochemistry prognostic factors in estrogen receptor-positive HER2-negative breast cancer.

In breast cancer (BC), pathologists visually score ER, PR, HER2, and Ki67 biomarkers to assess tumor properties and predict patient outcomes. This does not systematically account for intratumoral heterogeneity (ITH) which has been reported to provide prognostic value. This study utilized digital image analysis (DIA) and computational pathology methods to investigate the prognostic value of ITH indicators in ER-positive (ER+) HER2-negative (HER2-) BC patients. Whole slide images (WSIs) of surgically excised specimens stained for ER, PR, Ki67, and HER2 from 254 patients were used. DIA with tumor tissue segmentation and detection of biomarker-positive cells was performed. The DIA-generated data were subsampled by a hexagonal grid to compute Haralick's texture indicators for ER, PR, and Ki67. Cox regression analyses were performed to assess the prognostic significance of the immunohistochemistry (IHC) and ITH indicators in the context of clinicopathologic variables. In multivariable analysis, the ITH of Ki67-positive cells, measured by Haralick's texture entropy, emerged as an independent predictor of worse BC-specific survival (BCSS) (hazard ratio (HR) = 2.64, p-value = 0.0049), along with lymph node involvement (HR = 2.26, p-value = 0.0195). Remarkably, the entropy representing the spatial disarrangement of tumor proliferation outperformed the proliferation rate per se established either by pathology reports or DIA. We conclude that the Ki67 entropy indicator enables a more comprehensive risk assessment with regard to BCSS, especially in cases with borderline Ki67 proliferation rates. The study further demonstrates the benefits of high-capacity DIA-generated data for quantifying the essentially subvisual ITH properties.

Overall Survival Prediction by Tumor Microenvironment Lymphocyte Distribution in Hepatocellular Carcinoma After Liver Transplantation.

INTRODUCTION: Our previous research demonstrated that CD8+ cell density profiling using a hexagonal grid-based digital image analysis method provides predictors of patient outcomes after liver resection due to hepatocellular carcinoma (HCC). Continuing our study, we have further investigated the applicability of the methodology to patients receiving a liver transplant for HCC. METHODS: The retrospective study enrolled patients with HCC who underwent liver transplantation (LT) at the Vilnius University Hospital Santaros Clinics between 2007 and 2020. We determined the density profiles of CD8+ lymphocytes at the interface between HCC and stroma and the interface between the perineoplastic liver parenchyma and stroma. Both digital image analysis and the hexagonal grid-based immunogradient method were applied to CD8+ immunohistochemistry images. Survival statistics based on clinicopathological, peripheral blood analysis, and surgical data determined the prognostic value of these indicators. RESULTS: Univariate clinicopathological predictors of worse OS after LT included: patient's age at the time of the transplantation, a higher number of HCC nodules, lower platelet count, longer activated thromboplastin time, lower serum albumin, higher serum total bilirubin, and lower serum creatinine levels. The two independent predictors of overall survival were mean CD8+ cell density at the epithelial edge of the explanted liver parenchyma-stroma interface and peripheral blood platelet count. CONCLUSIONS: Our model discloses that preoperative peripheral blood platelet count and mean CD8+ cell density at the epithelial edge of nonmalignant interface in the explanted liver parenchyma are independent predictors of OS for HCC after LT.

An mTRAN-mRNA interaction mediates mitochondrial translation initiation in plants.

Plant mitochondria represent the largest group of respiring organelles on the planet. Plant mitochondrial messenger RNAs (mRNAs) lack Shine-Dalgarno-like ribosome-binding sites, so it is unknown how plant mitoribosomes recognize mRNA. We show that "mitochondrial translation factors" mTRAN1 and mTRAN2 are land plant-specific proteins, required for normal mitochondrial respiration chain biogenesis. Our studies suggest that mTRANs are noncanonical pentatricopeptide repeat (PPR)-like RNA binding proteins of the mitoribosomal "small" subunit. We identified conserved Adenosine (A)/Uridine (U)-rich motifs in the 5' regions of plant mitochondrial mRNAs. mTRAN1 binds this motif, suggesting that it is a mitoribosome homing factor to identify mRNAs. We demonstrate that mTRANs are likely required for translation of all plant mitochondrial mRNAs. Plant mitochondrial translation initiation thus appears to use a protein-mRNA interaction that is divergent from bacteria or mammalian mitochondria.

CD8+ Cell Density Gradient across the Tumor Epithelium-Stromal Interface of Non-Muscle Invasive Papillary Urothelial Carcinoma Predicts Recurrence-Free Survival after BCG Immunotherapy.

BACKGROUND: Bacille Calmette-Guerin (BCG) immunotherapy is the first-line treatment in patients with high-risk non-muscle invasive papillary urothelial carcinoma (NMIPUC), the most common type of bladder cancer. The therapy outcomes are variable and may depend on the immune response within the tumor microenvironment. In our study, we explored the prognostic value of CD8+ cell density gradient indicators across the tumor epithelium-stroma interface of NMIPUC. METHODS: Clinical and pathologic data were retrospectively collected from 157 NMIPUC patients treated with BCG immunotherapy after transurethral resection. Whole-slide digital image analysis of CD8 immunohistochemistry slides was used for tissue segmentation, CD8+ cell quantification, and the assessment of CD8+ cell densities within the epithelium-stroma interface. Subsequently, the gradient indicators (center of mass and immunodrop) were computed to represent the density gradient across the interface. RESULTS: By univariable analysis of the clinicopathologic factors, including the history of previous NMIPUC, poor tumor differentiation, and pT1 stage, were associated with shorter RFS (p < 0.05). In CD8+ analyses, only the gradient indicators but not the absolute CD8+ densities were predictive for RFS (p < 0.05). The best-performing cross-validated model included previous episodes of NMIPUC (HR = 4.4492, p = 0.0063), poor differentiation (HR = 2.3672, p = 0.0457), and immunodrop (HR = 5.5072, p = 0.0455). CONCLUSIONS: We found that gradient indicators of CD8+ cell densities across the tumor epithelium-stroma interface, along with routine clinical and pathology data, improve the prediction of RFS in NMIPUC.

Tetratricopeptide-containing SMALL KERNEL 11 is essential for the assembly of cytochrome c oxidase in maize mitochondria.

Assembly of the functional complexes of the mitochondrial respiratory chain requires sophisticated and efficient regulatory mechanisms. In plants, the subunit composition and assembly factors involved in the biogenesis of cytochrome c oxidase (complex IV) are substantially less defined than in mammals and yeast. In this study, we cloned maize (Zea mays) Small kernel 11 (Smk11) via map-based cloning. Smk11 encodes a mitochondria-localized tetratricopeptide repeat protein. Disruption of Smk11 severely affected the assembly and activity of mitochondrial complex IV, leading to delayed plant growth and seed development. Protein interactions studies revealed that SMK11 might interact with four putative complex IV assembly factors, Inner membrane peptidase 1A (ZmIMP1A), MYB domain protein 3R3 (ZmMYB3R-3), cytochrome c oxidase 23 (ZmCOX23), and mitochondrial ferredoxin 1 (ZmMFDX1), among which ZmMFDX1 might interact with subunits ZmCOX6a and ZmCOX-X1; ZmMYB3R-3 might also interact with ZmCOX6a. The mutation of SMK11 perturbed the normal assembly of these subunits, leading to the inactivation of complex IV. The results of this study revealed that SMK11 serves as an accessory assembly factor required for the normal assembly of subunits into complex IV, which will accelerate the elucidation of the assembly of complex IV in plant mitochondria.

Prognostic Value of CD8+ Lymphocytes in Hepatocellular Carcinoma and Perineoplastic Parenchyma Assessed by Interface Density Profiles in Liver Resection Samples.

Hepatocellular carcinoma (HCC) often emerges in the setting of long-standing inflammatory liver disease. CD8 lymphocytes are involved in both the antitumoral response and hepatocyte damage in the remaining parenchyma. We investigated the dual role of CD8 lymphocytes by assessing density profiles at the interfaces of both HCC and perineoplastic liver parenchyma with surrounding stroma in whole-slide immunohistochemistry images of surgical resection samples. We applied a hexagonal grid-based digital image analysis method to sample the interface zones and compute the CD8 density profiles within them. The prognostic value of the indicators was explored in the context of clinicopathological, peripheral blood testing, and surgery data. Independent predictors of worse OS were a low standard deviation of CD8+ density along the tumor edge, high mean CD8+ density within the epithelial aspect of the perineoplastic liver-stroma interface, longer duration of surgery, a higher level of aspartate transaminase (AST), and a higher basophil count in the peripheral blood. A combined score, derived from these five independent predictors, enabled risk stratification of the patients into three prognostic categories with a 5-year OS probability of 76%, 40%, and 8%. Independent predictors of longer RFS were stage pT1, shorter duration of surgery, larger tumor size, wider tumor-free margin, and higher mean CD8+ density in the epithelial aspect of the tumor-stroma interface. We conclude that (1) our computational models reveal independent and opposite prognostic impacts of CD8+ cell densities at the interfaces of the malignant and non-malignant epithelium interfaces with the surrounding stroma; and (2) together with pathology, surgery, and laboratory data, comprehensive prognostic models can be constructed to predict patient outcomes after liver resection due to HCC.

Improving HCC Prognostic Models after Liver Resection by AI-Extracted Tissue Fiber Framework Analytics.

Despite advances in diagnostic and treatment technologies, predicting outcomes of patients with hepatocellular carcinoma (HCC) remains a challenge. Prognostic models are further obscured by the variable impact of the tumor properties and the remaining liver parenchyma, often affected by cirrhosis or non-alcoholic fatty liver disease that tend to precede HCC. This study investigated the prognostic value of reticulin and collagen microarchitecture in liver resection samples. We analyzed 105 scanned tissue sections that were stained using a Gordon and Sweet's silver impregnation protocol combined with Picric Acid-Sirius Red. A convolutional neural network was utilized to segment the red-staining collagen and black linear reticulin strands, generating a detailed map of the fiber structure within the HCC and adjacent liver tissue. Subsequent hexagonal grid subsampling coupled with automated epithelial edge detection and computational fiber morphometry provided the foundation for region-specific tissue analysis. Two penalized Cox regression models using LASSO achieved a concordance index (C-index) greater than 0.7. These models incorporated variables such as patient age, tumor multifocality, and fiber-derived features from the epithelial edge in both the tumor and liver compartments. The prognostic value at the tumor edge was derived from the reticulin structure, while collagen characteristics were significant at the epithelial edge of peritumoral liver. The prognostic performance of these models was superior to models solely reliant on conventional clinicopathologic parameters, highlighting the utility of AI-extracted microarchitectural features for the management of HCC.

A new approach for microstructure imaging.

A recurring issue with microstructure studies is specimen lighting. In particular, microscope lighting must be deployed in such a way as to highlight biological elements without enhancing caustic effects and diffraction. We describe here a high frequency technique due to address this lighting issue. First, an extensive study is undertaken concerning asymptotic equations in order to identify the most promising algorithm for 3D microstructure analysis. Ultimately, models based on virtual light rays are discarded in favor of a model that considers the joint computation of phase and irradiance. This paper maintains the essential goal of the study concerning biological microstructures but offers several supplementary notes on computational details which provide perspectives on analyses of the arrangements of numerous objects in biological tissues.

The Disease Progression and Molecular Defense Response in Chenopodium Quinoa Infected with Peronospora Variabilis, the Causal Agent of Quinoa Downy Mildew.

Downy mildew disease, caused by the biotrophic oomycete Peronospora variabilis, is the largest threat to the cultivation of quinoa (Chenopodium quinoa Willd.) in the Andean highlands, and occurs worldwide. However, so far, no molecular study of the quinoa-Peronospora interaction has been reported. Here, we developed tools to study downy mildew disease in quinoa at the gene expression level. P. variabilis was isolated and maintained, allowing the study of downy mildew disease progression in two quinoa cultivars under controlled conditions. Quinoa gene expression changes induced by P. variabilis were analyzed by qRT-PCR, for quinoa homologues of A. thaliana pathogen-associated genes. Overall, we observed a slower disease progression and higher tolerance in the quinoa cultivar Kurmi than in the cultivar Maniqueña Real. The quinoa orthologs of putative defense genes such as the catalase CqCAT2 and the endochitinase CqEP3 showed no changes in gene expression. In contrast, quinoa orthologs of other defense response genes such as the transcription factor CqWRKY33 and the chaperone CqHSP90 were significantly induced in plants infected with P. variabilis. These genes could be used as defense response markers to select quinoa cultivars that are more tolerant to P. variabilis infection.

Isolation of Highly Purified, Intact, and Functional Mitochondria from Potato Tubers Using a Two-in-One Percoll Density Gradient.

The isolation of mitochondria from potato tubers (Solanum tuberosum L.) is described, but the methodology can easily be adapted to other storage tissues. After homogenization of the tissue, filtration and differential centrifugation, the key step is a Percoll density gradient centrifugation. The Percoll gradient contains two parts: a bottom part containing Percoll in 0.3 M sucrose, and a slightly less dense top part containing Percoll in 0.3 M mannitol. After centrifugation, a density gradient is formed that is almost linear in the central part, and this is where the band containing the purified intact mitochondria is formed. This method makes it possible to process large amounts of plant material (2-6 kg) and saves at least 1.5 h on the preparation time compared to methods where two consecutive purification methods are used. Nonetheless, it yields large amounts of mitochondria (50-125 mg protein) of very high purity, intactness and functionality.

Integrity Assessment of Isolated Plant Mitochondria.

The integrity of isolated mitochondria can be estimated functionally using enzymatic activities or the permeability of mitochondrial membranes to molecules of different sizes. Thus, the permeability of the outer membrane to the protein cytochrome c, the permeability of the inner membrane to protons, and the permeability of the inner membrane to NAD+, NADH and organic acids using soluble matrix dehydrogenases as markers have all been used. These assays all have limitations to how the data can be converted into a measure of integrity, are differently sensitive to artifacts and require widely variable amounts of material. Therefore, each method has a restricted utility for estimating integrity, depending on the type of mitochondria analysed. Here, we review the advantages and disadvantages of different integrity assays and present protocols for integrity assays that require relatively small amounts of mitochondria. They are based on the permeability of the outer membrane to cytochrome c, and the inner membrane to protons or NAD(H). The latter has the advantage of utilizing a membrane-bound activity (complex I) and the pore-forming peptide alamethicin to gain access to the matrix space. These methods together provide a toolbox for the determination of functionality and quality of isolated mitochondria.

Assessment of Respiratory Enzymes in Intact Cells by Permeabilization with Alamethicin.

We here describe measurements of respiratory enzymes in situ, which can be done on very small cell samples and make mitochondrial isolation unnecessary. The method is based on the ability of the fungal peptide alamethicin to permeate biological membranes from the net positively charged side, and form nonspecific ion channels. These channels allow rapid transport of substrates and products across the plasma membrane, the inner mitochondrial membrane, and the inner plastid envelope. In this way, mitochondrial enzyme activities can be studied without disrupting the cells. The enzymes can be investigated in their natural proteinaceous environment and the activity of enzymes, also those sensitive to detergents or to dilution, can be quantified on a whole cell basis. We here present protocols for in situ measurement of two mitochondrial enzymatic activities: malate oxidation measured as oxygen consumption by the electron transport chain, which is sensitive to detergents, and NAD+-isocitrate dehydrogenase, a tricarboxylic acid cycle enzyme that dissociates upon dilution.

Genes from oxidative phosphorylation complexes II-V and two dual-function subunits of complex I are transcribed in Viscum album despite absence of the entire mitochondrial holo-complex I.

Mistletoes (Viscum) and close relatives are unique among flowering plants in having a drastically altered electron transport chain. Lack of complex I genes has previously been reported for the mitochondrial genome, and here we report an almost complete absence of nuclear-encoded complex I genes in the transcriptome of Viscum album. Compared to Arabidopsis with approximately 40 nuclear complex I genes, we recover only transcripts of two dual-function genes: gamma carbonic anhydrase and L-galactono-1,4-lactone dehydrogenase. The complement of genes belonging to complexes II-V of the oxidative phosphorylation pathway appears to be in accordance with other vascular plants. Additionally, transcripts encoding alternative NAD(P)H dehydrogenases and alternative oxidase were found. Despite sequence divergence, structural modeling suggests that the encoded proteins are structurally conserved. Complex I loss is a special feature in Viscum species and relatives, as all other parasitic flowering plants investigated to date seem to have a complete OXPHOS system. Hence, Viscum offers a unique system for specifically investigating molecular consequences of complex I absence, such as the role of complex I subunits involved in secondary functions.

Intratumoral Heterogeneity and Immune Response Indicators to Predict Overall Survival in a Retrospective Study of HER2-Borderline (IHC 2+) Breast Cancer Patients.

Breast cancer (BC) categorized as human epidermal growth factor receptor 2 (HER2) borderline [2+ by immunohistochemistry (IHC 2+)] presents challenges for the testing, frequently obscured by intratumoral heterogeneity (ITH). This leads to difficulties in therapy decisions. We aimed to establish prognostic models of overall survival (OS) of these patients, which take into account spatial aspects of ITH and tumor microenvironment by using hexagonal tiling analytics of digital image analysis (DIA). In particular, we assessed the prognostic value of Immunogradient indicators at the tumor-stroma interface zone (IZ) as a feature of antitumor immune response. Surgical excision samples stained for estrogen receptor (ER), progesterone receptor (PR), Ki67, HER2, and CD8 from 275 patients with HER2 IHC 2+ invasive ductal BC were used in the study. DIA outputs were subsampled by HexT for ITH quantification and tumor microenvironment extraction for Immunogradient indicators. Multiple Cox regression revealed HER2 membrane completeness (HER2 MC) (HR: 0.18, p = 0.0007), its spatial entropy (HR: 0.37, p = 0.0341), and ER contrast (HR: 0.21, p = 0.0449) as independent predictors of better OS, with worse OS predicted by pT status (HR: 6.04, p = 0.0014) in the HER2 non-amplified patients. In the HER2-amplified patients, HER2 MC contrast (HR: 0.35, p = 0.0367) and CEP17 copy number (HR: 0.19, p = 0.0035) were independent predictors of better OS along with worse OS predicted by pN status (HR: 4.75, p = 0.0018). In the non-amplified tumors, three Immunogradient indicators provided the independent prognostic value: CD8 density in the tumor aspect of the IZ and CD8 center of mass were associated with better OS (HR: 0.23, p = 0.0079 and 0.14, p = 0.0014, respectively), and CD8 density variance along the tumor edge predicted worse OS (HR: 9.45, p = 0.0002). Combining these three computational indicators of the CD8 cell spatial distribution within the tumor microenvironment augmented prognostic stratification of the patients. In the HER2-amplified group, CD8 cell density in the tumor aspect of the IZ was the only independent immune response feature to predict better OS (HR: 0.22, p = 0.0047). In conclusion, we present novel prognostic models, based on computational ITH and Immunogradient indicators of the IHC biomarkers, in HER2 IHC 2+ BC patients.

Plant mitochondria - past, present and future.

The study of plant mitochondria started in earnest around 1950 with the first isolations of mitochondria from animal and plant tissues. The first 35 years were spent establishing the basic properties of plant mitochondria and plant respiration using biochemical and physiological approaches. A number of unique properties (compared to mammalian mitochondria) were observed: (i) the ability to oxidize malate, glycine and cytosolic NAD(P)H at high rates; (ii) the partial insensitivity to rotenone, which turned out to be due to the presence of a second NADH dehydrogenase on the inner surface of the inner mitochondrial membrane in addition to the classical Complex I NADH dehydrogenase; and (iii) the partial insensitivity to cyanide, which turned out to be due to an alternative oxidase, which is also located on the inner surface of the inner mitochondrial membrane, in addition to the classical Complex IV, cytochrome oxidase. With the appearance of molecular biology methods around 1985, followed by genomics, further unique properties were discovered: (iv) plant mitochondrial DNA (mtDNA) is 10-600 times larger than the mammalian mtDNA, yet it only contains approximately 50% more genes; (v) plant mtDNA has kept the standard genetic code, and it has a low divergence rate with respect to point mutations, but a high recombinatorial activity; (vi) mitochondrial mRNA maturation includes a uniquely complex set of activities for processing, splicing and editing (at hundreds of sites); (vii) recombination in mtDNA creates novel reading frames that can produce male sterility; and (viii) plant mitochondria have a large proteome with 2000-3000 different proteins containing many unique proteins such as 200-300 pentatricopeptide repeat proteins. We describe the present and fairly detailed picture of the structure and function of plant mitochondria and how the unique properties make their metabolism more flexible allowing them to be involved in many diverse processes in the plant cell, such as photosynthesis, photorespiration, CAM and C4 metabolism, heat production, temperature control, stress resistance mechanisms, programmed cell death and genomic evolution. However, it is still a challenge to understand how the regulation of metabolism and mtDNA expression works at the cellular level and how retrograde signaling from the mitochondria coordinates all those processes.

The effect of reversible permeabilization and post-electroporation resting on the survival of Thai basil (O. Basilicum cv. thyrsiflora) leaves during drying.

Horticultural crops have a low tolerance to dehydration. In this paper, we show that the reversible electroporation (200 monopolar, rectangular pulses of 50 µs pulse duration, 760 µs between pulses and nominal field strength of 650 V/cm) of Thai basil leaves followed by 24 h resting before hot air drying at 40 °C enhanced the survivability of the tissues at certain levels of dehydration (moisture ratio = 0.2 and 0.1). However, this increased survival was rather limited. Through measurements of metabolic heat production during resting, rehydration kinetics, respiration and photosynthesis of the rehydrated leaves, we show that resting after the application of a reversible pulse-electric field (PEF) may allow a phase of hardening that has a protective effect on the cells, thus decreasing damage during the subsequent drying phase. Increased preservation of cell vitality would be associated with a more turgid and fresh-like rehydrated product, as cells would have the capacity to retain the rehydration water.

The pentatricopeptide repeat protein EMP603 is required for the splicing of mitochondrial Nad1 intron 2 and seed development in maize.

Intron splicing is an essential event in post-transcriptional RNA processing in plant mitochondria, which requires the participation of diverse nuclear-encoded splicing factors. However, it is presently unclear how these proteins cooperatively take part in the splicing of specific introns. In this study, we characterized a nuclear-encoded mitochondrial P-type pentatricopeptide repeat (PPR) protein named EMP603. This protein is essential for splicing of intron 2 in the Nad1 gene and interacts with the mitochondria-localized DEAD-box RNA helicase PMH2-5140, the RAD52-like proteins ODB1-0814 and ODB1-5061, and the CRM domain-containing protein Zm-mCSF1. Further study revealed that the N-terminal region of EMP603 interacts with the DEAD-box of PMH2-5140, the CRM domain of Zm-mCSF1, and OBD1-5061, but not with OBD1-0814, whereas the PPR domain of EMP603 can interact with ODB1-0814, ODB1-5061, and PMH2-5140, but not with Zm-mCSF1. Defects in EMP603 severely disrupt the assembly and activity of mitochondrial complex I, leading to impaired mitochondrial function, and delayed seed development. The interactions revealed between EMP603 and PMH2-5140, ODB1-0814, ODB1-5061, and Zm-mCSF1 indicate a possible involvement of a dynamic 'spliceosome-like' complex in intron splicing, and may accelerate the elucidation of the intron splicing mechanism in plant mitochondria.

Machine-Learning-Based Evaluation of Intratumoral Heterogeneity and Tumor-Stroma Interface for Clinical Guidance.

Assessment of intratumoral heterogeneity and tumor-host interaction within the tumor microenvironment is becoming increasingly important for innovative cancer therapy decisions because of the unique information it can generate about the state of the disease. However, its assessment and quantification are limited by ambiguous definitions of the tumor-host interface and by human cognitive capacity in current pathology practice. Advances in machine learning and artificial intelligence have opened the field of digital pathology to novel tissue image analytics and feature extraction for generation of high-capacity computational disease management models. A particular benefit is expected from machine-learning applications that can perform extraction and quantification of subvisual features of both intratumoral heterogeneity and tumor microenvironment aspects. These methods generate information about cancer cell subpopulation heterogeneity, potential tumor-host interactions, and tissue microarchitecture, derived from morphologically resolved content using both explicit and implicit features. Several studies have achieved promising diagnostic, prognostic, and predictive artificial intelligence models that often outperform current clinical and pathology criteria. However, further effort is needed for clinical adoption of such methods through development of standardizable high-capacity workflows and proper validation studies.