Revision of the foraminiferal biozonation scheme in Upper Cretaceous carbonates of the Dezful Embayment,Zagros, Iran: Integrated palaeontological,sedimentological and geochemical investigation

Cretaceous carbonate successions of the Bangestan Group, such as the Sarvak and Ilam formations, are among the most prolific hydrocarbon reserves of the Middle East. However, relatively little is known about their detailed palaeontology and biostratigraphy. Moreover, due to lithological similarity of these carbonate formations recognition of their boundaries in subsurface studies is problematic. To investigate these units, biostratigraphic analyses were carried out on nearly 1100 m of cores, including core plug samples and thin sections prepared from five giant and supergiant oilfields in the northern and southern Dezful Embayment, SW Iran. Accordingly, 59 species of foraminifera (assigned to 43 genera) as well as 11 species of non-foraminifera (10 genera) were recognized. As a result, three biozones were identified, which in stratigraphic order are: Nezzazata-Alveolinids Assemblage Zone; Moncharmontia apenninica-Nezzazatinella-Dicyclina Assemblage Zone; and Rotalia skourensis-algae Assemblage Zone. These are compared with the Wynd's (1965) biozonation scheme, previously introduced in the Zagros area, and a revised scheme is presented. Accordingly, a Cenomanian–Turonian age and a Coniacian–Campanian age are envisaged for the Upper Sarvak and Ilam formations, respectively. In our new biostratigraphic scheme, the Sarvak–Ilam formations boundary is considered to be located above the Moncharmontia apenninica-Nezzazatinella-Dicyclina Assemblage Zone (equivalent of Valvulammina-Dicyclina Assemblage Zone of Wynd, 1965), that is Turonian in age. This zone is bounded by two palaeoexposure surfaces, which correspond approximately to the C–T boundary transitional interval and a post-Turonian, which can be possibly assigned to the Coniacian. Significant sedimentological features of these disconformities include bauxitic–lateritic horizons, karstified profiles and solution-collapsed breccias. Geochemical signatures of these meteorically altered surfaces are also considered to calibrate biofacies and biozones. Finally, we compared our new biozonation scheme with other studies in neighboring areas of SW Iran and the Middle East.     

The mechanism of specific binding of free cholesterol by the steroidogenic acute regulatory protein: evidence for a role of the C-terminal alpha-helix in the gating of the binding site

Steroidogenesis depends on the delivery of free cholesterol to the inner mitochondrial membrane by StAR (steroidogenic acute regulatory protein). Mutations in the StAR gene leads to proteins with limited cholesterol-binding capacity. This gives rise to the accumulation of cytoplasmic cholesterol, a deficit in steroid hormone production and to the medical condition of lipoid congenital adrenal hyperplasia. A detailed understanding of the mechanism of the specific binding of free cholesterol by StAR would be a critical asset in understanding the molecular origin of this disease. Previous studies have led to the proposal that the C-terminal alpha-helix 4 of StAR was undergoing a folding/unfolding transition. This transition is thought to gate the cholesterol-binding site. Moreover, a conserved salt bridge (Glu169-Arg188) in the cholesterol-binding site is also proposed to be critical to the binding process. Interestingly, some of the documented clinical mutations occur at this salt bridge (E169G, E169K and R188C) and in the C-terminal alpha-helix 4 (L275P). In the present study, using rationalized mutagenesis, activity assays, CD, thermodynamic studies and molecular modelling, we characterized the alpha-helix 4 mutations L271N and L275P, as well as the salt bridge double mutant E169M/R188M. The results provide experimental validation for the gating mechanism of the cholesterol-binding site by the C-terminal alpha-helix and the importance of the salt bridge in the binding mechanism. Altogether, our results offer a molecular framework for understanding the impact of clinical mutations on the reduction of the binding affinity of StAR for free cholesterol.     

Troglitazone, a PPAR-γ activator prevents endothelial cell adhesion molecule expression and lymphocyte adhesion mediated by TNF-α

Background  

Cytokine mediated induction of the mucosal addressin cell adhesion molecule-1(MAdCAM-1) expression is associated with the onset and progression of inflammatory bowel disease (IBD).     

Mathematical modeling of cell growth in a 3D scaffold and validation of static and dynamic cultures

Tissue engineering, an immensely important field in contemporary clinical practices, aims at the repair or replacement of damaged tissues. The mathematical model proposed herein shows the distribution and growth of cells in their characteristic time in a 3D scaffold model. This study contributes to the progress of simulation techniques in static and dynamic cultures of bone tissue. Brinkman, nutrient transport, and cell growth equations are brought together to quantify the growth behavior of cells. However, when a static culture is being studied, the Brinkman equation is eliminated. The model was validated by experimental cell culture using 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assay and scanning electron microscopy. Then, static and dynamic cultures were compared to assess the cell density and cell distribution in the scaffold. Cell counting after 21 days of cell culture showed that the number of cells increased 42‐fold in static and 53.5‐fold in dynamic cultures, which was in good agreement with our model estimations (37‐fold increase in the number of cells in static and 49‐fold increase in dynamic cultures). In conclusion, our mathematical model could predict cell distribution and growth in the scaffold.     

Environmental factors–ecological species group relationships in the Surash lowland‐mountain forests in northern Iran

Identification of the primary factors that influence the ecological distribution of species groups is important to managers of lowland‐mountain forests in northern Iran. The aim of this study was to identify main ecological species groups, describe the site conditions associated with these species groups and the relationships between environmental factors and the distribution of ecological species groups using multi‐variate analysis (Detrended correspondence analysis (DCA) and Canonical correspondence analysis (CCA)). For this purpose, 50 relevés (400 m² each) were sampled using the Braun‐Blanquet method. Vegetation was classified into three ecological species groups using a modified two‐way indicator species analysis (TWINSPAN). In each relevé, environmental factors (topographic and soil variables) were measured and analysed using one‐way ANOVA and Pearson r statistics. Further, species diversity indices were determined for the identified ecological species groups. Our results show that the environmental factors, e.g. elevation, slope, slope aspect, soil texture, pH and organic matter, were the most important factors explaining the distribution of the three ecological species groups in the study area. The diversity of the ecological species groups decreased with elevation. The results provide an ecological basis for forest management and for developing strategies for forest conservation in the study area.     

Autolysis loop restricts the specificity of activated protein C: analysis by FRET and functional assays

We previously demonstrated that the substitution of the autolysis loop (residues 143-154 in chymotrypsin numbering) of APC with the corresponding loop of trypsin (APC-Tryp 143-154) has no influence on the proteolytic activity of the protease toward fVa, however, this substitution increases the reactivity of APC with plasma inhibitors so that the mutant exhibits no anticoagulant activity in plasma. To further investigate the role of the autolysis loop in APC and determine whether this loop is a target for modulation by protein S, we evaluated the activity of APC-Tryp 143-154 toward fVa and several plasma inhibitors both in the absence and presence of protein S. Furthermore, we evaluated the active-site topography of APC-Tryp 143-154 by determining the average distance of the closest approach (L) between a fluorescein dye tethered to a tripeptide inhibitor, attached to the active-site of APC-Tryp 143-154, and octadecylrhodamine dyes incorporated into PCPS vesicles both in the absence and presence of protein S. The activity of APC-Tryp 143-154 toward fVa was identical to that of wild-type APC both in the presence and absence of protein S. However, the reactivity of APC-Tryp 143-154 with plasma inhibitors was preferentially improved independent of protein S. The FRET analysis revealed a dramatic change in the active-site topography of APC both in the absence and presence of protein S. Anisotropy measurements revealed that the fluorescein dye has a remarkable degree of rotational freedom in the active-site of APC-Tryp 143-154. These results suggest that the autolysis loop of APC may not be a target for modulation by protein S. This loop, however, plays a critical role in restricting both the specificity and spatial environment of the active-site groove of APC.     

In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes

The human immune system consists of a highly intelligent network of billions of independent, self-organized cells that interact with each other. Machine learning (ML) is an artificial intelligence (AI) tool that automatically processes huge amounts of image data. Immunotherapies have revolutionized the treatment of blood cancer. Specifically, one such therapy involves engineering immune cells to express chimeric antigen receptors (CAR), which combine tumor antigen specificity with immune cell activation in a single receptor. To improve their efficacy and expand their applicability to solid tumors, scientists optimize different CARs with different modifications. However, predicting and ranking the efficacy of different "off-the-shelf" immune products (e.g., CAR or Bispecific T-cell Engager [BiTE]) and selection of clinical responders are challenging in clinical practice. Meanwhile, identifying the optimal CAR construct for a researcher to further develop a potential clinical application is limited by the current, time-consuming, costly, and labor-intensive conventional tools used to evaluate efficacy. Particularly, more than 30 years of immunological synapse (IS) research data demonstrate that T cell efficacy is not only controlled by the specificity and avidity of the tumor antigen and T cell interaction, but also it depends on a collective process, involving multiple adhesion and regulatory molecules, as well as tumor microenvironment, spatially and temporally organized at the IS formed by cytotoxic T lymphocytes (CTL) and natural killer (NK) cells. The optimal function of cytotoxic lymphocytes (including CTL and NK) depends on IS quality. Recognizing the inadequacy of conventional tools and the importance of IS in immune cell functions, we investigate a new strategy for assessing CAR-T efficacy by quantifying CAR IS quality using the glass-support planar lipid bilayer system combined with ML-based data analysis. Previous studies in our group show that CAR-T IS quality correlates with antitumor activities in vitro and in vivo. However, current manually quantified IS quality data analysis is time-consuming and labor-intensive with low accuracy, reproducibility, and repeatability. In this study, we develop a novel ML-based method to quantify thousands of CAR cell IS images with enhanced accuracy and speed. Specifically, we used artificial neural networks (ANN) to incorporate object detection into segmentation. The proposed ANN model extracts the most useful information to differentiate different IS datasets. The network output is flexible and produces bounding boxes, instance segmentation, contour outlines (borders), intensities of the borders, and segmentations without borders. Based on requirements, one or a combination of this information is used in statistical analysis. The ML-based automated algorithm quantified CAR-T IS data correlates with the clinical responder and non-responder treated with Kappa-CAR-T cells directly from patients. The results suggest that CAR cell IS quality can be used as a potential composite biomarker and correlates with antitumor activities in patients, which is sufficiently discriminative to further test the CAR IS quality as a clinical biomarker to predict response to CAR immunotherapy in cancer. For translational research, the method developed here can also provide guidelines for designing and optimizing numerous CAR constructs for potential clinical development.Trial Registration: ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00881920","term_id":"NCT00881920"}}NCT00881920.     

A multibody modelling approach to determine load sharing between passive elements of the lumbar spine

The human spinal segment is an inherently complex structure, a combination of flexible and semi-rigid articulating elements stabilised by seven principal ligaments. An understanding of how mechanical loading is shared among these passive elements of the segment is required to estimate tissue failure stresses. A 3D rigid body model of the complete lumbar spine has been developed to facilitate the prediction of load sharing across the passive elements. In contrast to previous multibody models, this model includes a non-linear, six degrees of freedom intervertebral disc, facet bony articulations and all spinal ligaments. Predictions of segmental kinematics and facet joint forces, in response to pure moment loading (flexion–extension), were compared to published in vitro data. On inclusion of detailed representation of the disc and facets, the multibody model fully captures the non-linear flexibility response of the spinal segment, i.e. coupled motions and a mobile instantaneous centre of rotation. Predicted facet joint forces corresponded well with reported values. For the loading case considered, the model predicted that the ligaments are the main stabilising elements within the physiological motion range; however, the disc resists a greater proportion of the applied load as the spine is fully flexed. In extension, the facets and capsular ligaments provide the principal resistance. Overall patterns of load distribution to the spinal ligaments are in agreement with previous predictions; however, the current model highlights the important role of the intraspinous ligament in flexion and the potentially high risk of failure. Several important refinements to the multibody modelling of the passive elements of the spine have been described, and such an enhanced passive model can be easily integrated into a full musculoskeletal model for the prediction of spinal loading for a variety of daily activities.     

NmeCas9 is an intrinsically high-fidelity genome-editing platform

Background

The development of CRISPR genome editing has transformed biomedical research. Most applications reported thus far rely upon the Cas9 protein from Streptococcus pyogenes SF370 (SpyCas9). With many RNA guides, wildtype SpyCas9 can induce significant levels of unintended mutations at near-cognate sites, necessitating substantial efforts toward the development of strategies to minimize off-target activity. Although the genome-editing potential of thousands of other Cas9 orthologs remains largely untapped, it is not known how many will require similarly extensive engineering to achieve single-site accuracy within large genomes. In addition to its off-targeting propensity, SpyCas9 is encoded by a relatively large open reading frame, limiting its utility in applications that require size-restricted delivery strategies such as adeno-associated virus vectors. In contrast, some genome-editing-validated Cas9 orthologs are considerably smaller and therefore better suited for viral delivery.

Results

Here we show that wildtype NmeCas9, when programmed with guide sequences of the natural length of 24 nucleotides, exhibits a nearly complete absence of unintended editing in human cells, even when targeting sites that are prone to off-target activity with wildtype SpyCas9. We also validate at least six variant protospacer adjacent motifs (PAMs), in addition to the preferred consensus PAM (5′-N₄GATT-3′), for NmeCas9 genome editing in human cells.

Conclusions

Our results show that NmeCas9 is a naturally high-fidelity genome-editing enzyme and suggest that additional Cas9 orthologs may prove to exhibit similarly high accuracy, even without extensive engineering.