Role In Recent Advances Research Articles

Antenatal diagnosis of thoracopagus and thoraco-omphalopagus conjoined twins: case series

BackgroundConjoined twin pregnancy is a rare variety, which occurs due to incomplete separation of the embryonic plate after 13 days. Each type of this entity is linked to distinct levels of organ sharing, structural abnormalities, complications, and difficulties concerning the potential for separation. So a comprehensive multidisciplinary prenatal assessment of conjoined twins is crucial for providing accurate parental counseling, effectively managing the pregnancy, and formulating an appropriate delivery strategy. The purpose of our study was to early diagnosis of conjoined twins using ultrasound, describing the various types of conjoined twins and the role of recent advances like 3D ultrasound in aiding their management.Case presentationHere, we are describing the case series of four conjoined twins, which were diagnosed antenatally by using ultrasound between the period of January 2019 and December 2019. Four cases of conjoined twins (two thoracopagus and two thoraco-omphalopagus) were accurately diagnosed on antenatal ultrasound. After detailed counseling of the parents regarding the risks and benefits of this complicated pregnancy and obtaining written consent, all four cases were terminated. Ultrasound plays a vital role in the early diagnosis and management of conjoined twins. Also, 3D ultrasound and MRI help in better characterization of fused body parts and connection between vital organs, thus it aids in the management.ConclusionsIt is important to detect these cases early as termination of pregnancy is less risky in the early stages as compared to the late stages for proper management.

Review of the Use of Animal Models of Human Polycystic Kidney Disease for the Evaluation of Experimental Therapeutic Modalities.

Autosomal dominant polycystic kidney disease, autosomal recessive polycystic kidney disease, and nephronophthisis are hereditary disorders with the occurrence of numerous cysts in both kidneys, often causing chronic and end-stage renal failure. Animal models have played an important role in recent advances in research not only on disease onset and progressive mechanisms but also on the development of therapeutic interventions. For a long time, spontaneous animal models have been used as the primary focus for human diseases; however, after the identification of the nucleotide sequence of the responsible genes, PKD1, PKD2, PKHD1, and NPHPs, various types of genetically modified models were developed by genetic and reproductive engineering techniques and played the leading role in the research field. In this review, we present murine models of hereditary renal cystic diseases, discussing their potential benefits in the development of therapeutic strategies.

Circuit Complexity in Topological Quantum Field Theory

AbstractQuantum circuit complexity has played a central role in recent advances in holography and many‐body physics. Within quantum field theory, it has typically been studied in a Lorentzian (real‐time) framework. In a departure from standard treatments, we aim to quantify the complexity of the Euclidean path integral. In this setting, there is no clear separation between space and time, and the notion of unitary evolution on a fixed Hilbert space no longer applies. As a proof of concept, we argue that the pants decomposition provides a natural notion of circuit complexity within the category of 2‐dimensional bordisms and use it to formulate the circuit complexity of states and operators in 2‐dimensional topological quantum field theory. We comment on analogies between our formalism and others in quantum mechanics, such as tensor networks and second quantization.

Advances in numerical approaches for microfluidic cell analysis platforms

Microfluidics has demonstrated enormous potential through its role in recent advances in biological sciences. However, designing a new and customized microfluidic platform, gaining a better understanding of its function and the underlying physics still pose significant technical challenges. On the one hand, experimental approaches have been commonly used for the development of microfluidic devices since they are accurate and evidence-based methods. However, these approaches are expensive and laborious. Numerical approaches, on the other hand, are now recognized as a reliable complementary method to reducing cost, time, and effort and being relatively accurate. This paper systematically reviews the capability of numerical approaches in developing efficient microfluidic technologies for cell analysis. Moreover, this paper provides an initial insight for researchers who are interested in establishing numerical approaches for microfluidic cell analysis platforms.

P-Chiral Phosphorus Ligands Based on a 2,3-Dihydrobenzo[ d][1,3]oxaphosphole Motif for Asymmetric Catalysis.

Despite the rapid progress in the field of asymmetric catalysis, the search for new, efficient, and practical asymmetric catalytic transformations to facilitate the green synthesis of chiral natural products and drugs will continue to be a major ongoing effort in organic chemistry. Chiral phosphorus ligands have played a significant role in recent advances in transition-metal-catalyzed asymmetric transformations. However, there remain numerous challenging issues of reactivity and selectivity in catalysis. The development of new and efficient chiral phosphorus ligands with new structural motifs remains highly desirable. P-Chiral phosphorus ligands have been overlooked and are underdeveloped, except for the early success of DIPAMP, introduced first by Knowles in the early 1970s. It was not until the late 1990s that the development of P-chiral phosphorus ligands regained attention with the advent of bisP*, TangPhos, etc. Nonetheless, most P-chiral phosphorus ligands were either difficult to prepare or operationally inconvenient. The development of efficient, practical, and operationally convenient P-chiral phosphorus ligands with new structural motifs remains an important subject of research. This Account introduces the design and development of a series of practical and efficient P-chiral bis- and monophosphorus ligands based on a 2,3-dihydrobenzo[ d][1,3]oxaphosphole motif. Their unique structural and physical properties include conformational unambiguousness, high tunability of electronic and steric properties, and operational simplicity as air-stable solids, which make them practical and exceptional ligands for asymmetric catalysis. Chiral bisphosphorus ligands such as MeO-BIBOP (L3), WingPhos (L4), and iPr-BABIBOP (L7) have demonstrated excellent enantioselectivities and unprecedented turnover numbers (TONs) in various asymmetric hydrogenations and other transformations, providing practical and efficient solutions leading to chiral amines, alcohols, carboxylic acids, and α- and β-amino acids. Chiral biaryl monophosphorus ligands, including BI-DIME (L9), AntPhos (L15), iPr-BI-DIME (L11), etc., have proven to be a class of versatile and powerful ligands for a number of catalytic asymmetric transformations, including asymmetric Suzuki-Miyaura coupling, asymmetric palladium-catalyzed dearomative cyclization, asymmetric hydroboration/diboration, asymmetric nickel-catalyzed reductive coupling, asymmetric palladium-catalyzed intramolecular arylation, asymmetric alkene aryloxyarylation, asymmetric α-arylation, asymmetric Heck reaction, and asymmetric nucleophilic addition, providing efficient solutions leading to various synthetically challenging chiral structures such as chiral biaryls, chiral tertiary alcohols, chiral α-amino tertiary boronic esters, and chiral all-carbon quaternary stereocenters. The high enantioselectivities and TONs obtained with these ligands have resulted in the syntheses of several chiral natural products and therapeutic agents in concise and highly efficient manners. While our efforts on the development of P-chiral phosphorus ligands are ongoing, it should be emphasized that the development of ligands and catalysts with new structural motifs should continue in the search for new reactivity and selectivity to tackle current synthetic challenges. Such effort is destined to promote the advances of asymmetric catalysis as well as synthetic organic chemistry.

On $f$- and $h$-vectors of relative simplicial complexes

A relative simplicial complex is a collection of sets of the form $\Delta \setminus \Gamma$, where $\Gamma \subset \Delta$ are simplicial complexes. Relative complexes played key roles in recent advances in algebraic, geometric, and topological combinatorics but, in contrast to simplicial complexes, little is known about their general combinatorial structure. In this paper, we address a basic question in this direction and give a characterization of $f$-vectors of relative (multi)complexes on a ground set of fixed size. On the algebraic side, this yields a characterization of Hilbert functions of quotients of homogeneous ideals over polynomial rings with a fixed number of indeterminates. Moreover, we characterize $h$-vectors of fully Cohen--Macaulay relative complexes as well as $h$-vectors of Cohen--Macaulay relative complexes with minimal faces of given dimensions. The latter resolves a question of Bj\"orner.

From field analogues to realistic seismic modelling: a case study of an oil-producing andesitic sill complex in the Neuquén Basin, Argentina

Interpretation of seismic data has played a major role in recent advances in the studies of igneous sill complexes. Seismic modelling studies based on field analogues represent a promising tool to close the scale gap between observations from outcrops and seismic data and support seismic interpretation. Virtual outcrop models are commonly used to include high-resolution geological structures in models of seismic-scale field analogues. However, realistic seismic modelling requires not only detailed structural input, but also well-constrained elastic properties and an adequate seismic modelling technique. Here, we present a seismic modelling study of oil-producing andesitic sills in the Neuquén Basin, Argentina, which implements all modelling elements at high accuracy by combining virtual outcrop models, well data and a 2(3)D filtering method. Our results indicate that the modelled seismic signatures of intrusive bodies observed in field analogues are characterized by frequency-dependent interference and strong amplitude variations owing to highly variable elastic properties of both host rock and sills. We demonstrate that detailed waveform patterns observed in real seismic data can be linked to intrusive bodies below the traditionally assumed limit of resolution via realistic seismic modelling. This illustrates how an integrated modelling approach based on field analogues can aid seismic interpretation.

Manifold Based Low-Rank Regularization for Image Restoration and Semi-Supervised Learning

Low-rank structures play important roles in recent advances of many problems in image science and data science. As a natural extension of low-rank structures for data with nonlinear structures, the concept of the low-dimensional manifold structure has been considered in many data processing problems. Inspired by this concept, we consider a manifold based low-rank regularization as a linear approximation of manifold dimension. This regularization is less restricted than the global low-rank regularization, and thus enjoy more flexibility to handle data with nonlinear structures. As applications, we demonstrate the proposed regularization to classical inverse problems in image sciences and data sciences including image inpainting, image super-resolution, X-ray computer tomography image reconstruction and semi-supervised learning. We conduct intensive numerical experiments in several image restoration problems and a semi-supervised learning problem of classifying handwritten digits using the MINST data. Our numerical tests demonstrate the effectiveness of the proposed methods and illustrate that the new regularization methods produce outstanding results by comparing with many existing methods.

AOJ-1 - Asia as a center for global oncology drug development

We are all familiar with the fact that certain cancers, such as gastric and esophageal cancers and hepatocellular carcinoma, are more prevalent in Asia than in the West. A common misperception is that Asian expertise and access to patients is limited to these Asia-prevalent cancers. On the contrary, Japanese, Korean, and Chinese researchers have played key roles in recent advances in the treatment of geographically non-specific tumors such as non-small cell lung cancer (NSCLC). In fact, Asian investigators and Asia-led studies have been pivotal in the development of important targeted agents in diseases including EGFR mutant and ALK rearranged NSCLC. When deciding whether to pursue a worldwide integrated development plan or separate Western and Asia development plans, several key considerations should be taken into account: Is there similar etiology and histology of the disease? Are patients staged similarly with other parts of the world? Is there similar clinical utilization of surgery, radiation, chemotherapy, loco-regional therapy, targeted therapy, and immunotherapy? Are there similar outcomes in terms of response and survival? Are salvage treatments similarly available and effective in Asia as in other parts of the world? Is there any reason to believe that the tolerability or risk/benefit ratio of the drug or intervention will be different in Asian patients? Does the infrastructure exist for efficient monitoring of Asian sites? Can biological specimens be obtained from patients and, if so, can the tissue be analyzed in a laboratory outside of the region? Inclusion of Asian patients in pivotal clinical trials is a requirement for market access in many Asian countries. Global pharmaceutical companies must decide whether to include Asian sites in global pivotal trials or to pursue Asia-focused clinical development strategies. Successful companies will utilize both approaches, tailoring them to the unique characteristics of the population, disease, and product.

Paradox and promise: research on the role of recent advances in paleodemography and paleoepidemiology to the study of "health" in Precolumbian societies.

Bioarcheology has made tremendous strides since the subdiscipline's inception, subsequent syntheses, the standardization of data collection methods, and analytical advances ranging from molecular analyses through age-estimation and biodistance. Concurrently, health and the adaptive success of past populations have remained primary concerns. However, questions are routinely raised about lesions and whether or not changing frequencies are synonymous with increases or decreases in stress, morbidity, and overall health. These include how and why healed lesions can simultaneously represent stress and survival, demanding that researchers understand how population dynamics influence skeletal sample formation. In this study, methods to analyze age- and sex-specific mortality patterns prior to, and in conjunction with, the analysis of linear enamel hypoplasias are demonstrated. Paleodemographic and paleoepidemiological models are presented for late Pre-Columbian skeletal samples from the Eastern Woodlands. Results of hazard modeling demonstrate that elevated mortality rates were commonplace during the latter half of the Mississippian period (AD 1200-1450) with reproductive-age females experiencing high age-specific risk of death attributed to the development of fortified villages and novel environments for increased pathogen loads. Corollary results are presented for the age-specificity of linear enamel hypoplasias in the central Illinois River valley. The epidemiological models demonstrate that the relationship between adult mortality and early childhood stress varied through space, culture, and time. These findings highlight the need to effectively operationalize measurements related to health and stress in past populations and support the adoption of selective mortality and heterogeneity in frailty as key concepts in bioarcheological research. Am J Phys Anthropol 155:268-280, 2014. © 2014 Wiley Periodicals, Inc.

SHARPEN—Systematic Hierarchical Algorithms for Rotamers and Proteins on an Extended Network

Algorithms for discrete optimization of proteins play a central role in recent advances in protein structure prediction and design. We wish to improve the resources available for computational biologists to rapidly prototype such algorithms and to easily scale these algorithms to many processors. To that end, we describe the implementation and use of two new open source resources, citing potential benefits over existing software. We discuss CHOMP, a new object-oriented library for macromolecular optimization, and SHARPEN, a framework for scaling CHOMP scripts to many computers. These tools allow users to develop new algorithms for a variety of applications including protein repacking, protein-protein docking, loop rebuilding, or homology model remediation. Particular care was taken to allow modular energy function design; protein conformations may currently be scored using either the OPLSaa molecular mechanical energy function or an all-atom semiempirical energy function employed by Rosetta.

Real-Time Decoding of Nonstationary Neural Activity in Motor Cortex

Neural decoding has played a key role in recent advances in brain-machine interfaces (BMIs) by converting brain signals into control commands to drive external devices such as robotic limbs or computer cursors. A number of practical algorithms including the well-known linear regression and Kalman filter models have been used to predict continuous movement in a real-time online context using recordings from a chronically implanted multielectrode microarray in the motor cortex. Though effective, those models were often based on a strong assumption that the neural signal sequence is a stationary process. Recent work, however, indicates that the motor system significantly varies over time. To characterize the dynamic relationship between neural signals and hand kinematics, here we develop an adaptive approach for each of the linear regression and Kalman filter methods. Experimental results show that the new adaptive algorithms generate more accurate decoding than the nonadaptive algorithms. To make the new algorithms feasible in an online situation, we further develop a recursive update approach and theoretically demonstrate its superior efficiency. In particular, the adaptive Kalman filter is shown to be more accurate and efficient. We also test the new methods in a simulated BMI experiment where the true hand motion is not known. The successful performance suggests these methods could be useful decoding algorithms for practical applications.

Proenkephalin gene regulation in the neuroendocrine hypothalamus: a model of gene regulation in the CNS

During the past decade, a great deal of progress has been made in studying the mechanisms by which transcription of neuropeptides is regulated by second messengers and neural activity. Such investigations, which have depended to a great extent on the use of transformed cell lines, are far from complete. Yet a major challenge for the coming decade is to understand the regulation of neuropeptide genes by physiologically and pharmacologically relevant stimuli in appropriate cell types in vivo. The proenkephalin gene, a member of the opioid gene family, has served as a model to study regulated transcription, not only in cell lines, but also in central (e.g., hypothalamic) and peripheral (e.g., adrenal) neuroendocrine tissues. Here we review regulation of proenkephalin gene expression in the hypothalamus. Several approaches, including in situ hybridization, use of transgenic mice, and the adaptation of electrophoretic mobility shift assays to complex tissues, have played critical roles in recent advances. A summary of possible future developments in this field of research is also presented.