Infección de prótesis aórtica abdominal: tratamiento alternativo / Infected abdominal aortic prosthesis: an alternative therapy

Introducción: la infección de prótesis aórtica en la cirugía vascular convencional es un evento catastrófico, con una alta tasa de morbilidad y de mortalidad. El tratamiento tradicional ha sido la remoción de la prótesis y la reconstrucción con bypass extraanatómico. En algunos casos, se ha llevado a cabo el reemplazo con prótesis impregnadas en antibiótico; en otros, el reemplazo con vena femoral superficial y también la cirugía abierta con drenaje de las colecciones asociadas y antibioticoterapia de por vida. Caso clínico: se presenta el reporte de un caso de infección protésica tratada con drenajes de las colecciones y antibioticoterapia de larga duración, con un resultado favorable un año después de su complicación. Discusión: en algunos casos, dada la severidad del paciente, es posible intentar un tratamiento conservador de esta nefasta complicación.(AU)

Introduction: in traditional vascular surgery, aortic prosthesis infection is a catastrophic event with high morbidity andmortality rates. Traditional treatment is the removal of the valve followed by extra-anatomic bypass reconstruction. Insome cases, antibiotic-impregnated prosthesis replacement has been performed. In others, superficial femoral veinreplacement, and open surgery with drainage of the associated collections and lifelong antibiotic therapy.Case report: this is the case of a patient with aortic prosthesis infection undergoing draining collections and lifelongantibiotic therapy with a favorable outcome 1 year after the complication.Discussion: in some cases, given the severity of the patient, we can try to treat this dreaded complication conservativel.(AU)

Future trends of additive manufacturing in medical applications: An overview.

Additive Manufacturing (AM) has recently demonstrated significant medical progress. Due to advancements in materials and methodologies, various processes have been developed to cater to the medical sector's requirements, including bioprinting and 4D, 5D, and 6D printing. However, only a few studies have captured these emerging trends and their medical applications. Therefore, this overview presents an analysis of the advancements and achievements obtained in AM for the medical industry, focusing on the principal trends identified in the annual report of AM3DP.

The rise and fall of stretched bond errors: Extending the analysis of Perdew-Zunger self-interaction corrections of reaction barrier heights beyond the LSDA.

Incorporating self-interaction corrections (SIC) significantly improves chemical reaction barrier height predictions made using density functional theory methods. We present a detailed orbital-by-orbital analysis of these corrections for three semi-local density functional approximations (DFAs) situated on the three lowest rungs of Jacob's ladder of approximations. The analysis is based on Fermi-Löwdin Orbital Self-Interaction Correction (FLOSIC) calculations performed at several steps along the reaction pathway from the reactants (R) to the transition state (TS) to the products (P) for four representative reactions selected from the BH76 benchmark set. For all three functionals, the major contribution to self-interaction corrections of the barrier heights can be traced to stretched bond orbitals that develop near the TS configuration. The magnitude of the ratio of the self-exchange-correlation energy to the self-Hartree energy (XC/H) for a given orbital is introduced as an indicator of one-electron self-interaction error. XC/H = 1.0 implies that an orbital's self-exchange-correlation energy exactly cancels its self-Hartree energy and that the orbital, therefore, makes no contribution to the SIC in the FLOSIC scheme. For the practical DFAs studied here, XC/H spans a range of values. The largest values are obtained for stretched or strongly lobed orbitals. We show that significant differences in XC/H for corresponding orbitals in the R, TS, and P configurations can be used to identify the major contributors to the SIC of barrier heights and reaction energies. Based on such comparisons, we suggest that barrier height predictions made using the strongly constrained and appropriately normed meta-generalized gradient approximation may have attained the best accuracy possible for a semi-local functional using the Perdew-Zunger SIC approach.

Pre-Infection Innate Immunity Attenuates SARS-CoV-2 Infection and Viral Load in iPSC-Derived Alveolar Epithelial Type 2 Cells.

A large portion of the heterogeneity in coronavirus disease 2019 (COVID-19) susceptibility and severity of illness (SOI) remains poorly understood. Recent evidence suggests that SARS-CoV-2 infection-associated damage to alveolar epithelial type 2 cells (AT2s) in the distal lung may directly contribute to disease severity and poor prognosis in COVID-19 patients. Our in vitro modeling of SARS-CoV-2 infection in induced pluripotent stem cell (iPSC)-derived AT2s from 10 different individuals showed interindividual variability in infection susceptibility and the postinfection cellular viral load. To understand the underlying mechanism of the AT2's capacity to regulate SARS-CoV-2 infection and cellular viral load, a genome-wide differential gene expression analysis between the mock and SARS-CoV-2 infection-challenged AT2s was performed. The 1393 genes, which were significantly (one-way ANOVA FDR-corrected p ≤ 0.05; FC abs ≥ 2.0) differentially expressed (DE), suggest significant upregulation of viral infection-related cellular innate immune response pathways (p-value ≤ 0.05; activation z-score ≥ 3.5), and significant downregulation of the cholesterol- and xenobiotic-related metabolic pathways (p-value ≤ 0.05; activation z-score ≤ -3.5). Whilst the effect of post-SARS-CoV-2 infection response on the infection susceptibility and postinfection viral load in AT2s is not clear, interestingly, pre-infection (mock-challenged) expression of 238 DE genes showed a high correlation with the postinfection SARS-CoV-2 viral load (FDR-corrected p-value ≤ 0.05 and r2-absolute ≥ 0.57). The 85 genes whose expression was negatively correlated with the viral load showed significant enrichment in viral recognition and cytokine-mediated innate immune GO biological processes (p-value range: 4.65 × 10-10 to 2.24 × 10-6). The 153 genes whose expression was positively correlated with the viral load showed significant enrichment in cholesterol homeostasis, extracellular matrix, and MAPK/ERK pathway-related GO biological processes (p-value range: 5.06 × 10-5 to 6.53 × 10-4). Overall, our results strongly suggest that AT2s' pre-infection innate immunity and metabolic state affect their susceptibility to SARS-CoV-2 infection and viral load.

Metabolic syndrome traits exhibit genotype-by-environment interaction in relation to socioeconomic status in the Mexican American family heart study.

Background: Socioeconomic Status (SES) is a potent environmental determinant of health. To our knowledge, no assessment of genotype-environment interaction has been conducted to consider the joint effects of socioeconomic status and genetics on risk for metabolic disease. We analyzed data from the Mexican American Family Studies (MAFS) to evaluate the hypothesis that genotype-by-environment interaction (GxE) is an essential determinant of variation in risk factors for metabolic syndrome (MS). Methods: We employed a maximum likelihood estimation of the decomposition of variance components to detect GxE interaction. After excluding individuals with diabetes and individuals on medication for diabetes, hypertension, or dyslipidemia, we analyzed 12 MS risk factors: fasting glucose (FG), fasting insulin (FI), 2-h glucose (2G), 2-h insulin (2I), body mass index (BMI), waist circumference (WC), leptin (LP), high-density lipoprotein-cholesterol (HDL-C), triglycerides (TG), total serum cholesterol (TSC), systolic blood pressure (SBP), and diastolic blood pressure (DBP). Our SES variable used a combined score of Duncan's socioeconomic index and education years. Heterogeneity in the additive genetic variance across the SES continuum and a departure from unity in the genetic correlation coefficient were taken as evidence of GxE interaction. Hypothesis tests were conducted using standard likelihood ratio tests. Results: We found evidence of GxE for fasting glucose, 2-h glucose, 2-h insulin, BMI, and triglycerides. The genetic effects underlying the insulin/glucose metabolism component of MS are upregulated at the lower end of the SES spectrum. We also determined that the household variance for systolic blood pressure decreased with increasing SES. Conclusion: These results show a significant change in the GxE interaction underlying the major components of MS in response to changes in socioeconomic status. Further mRNA sequencing studies will identify genes and canonical gene pathways to support our molecular-level hypotheses.

Bond length alternation of π-conjugated polymers predicted by the Fermi-Löwdin orbital self-interaction correction method.

π-conjugated polymers have been used in a wide range of practical applications, partly due to their unique properties that originate in the delocalization of electrons through the polymer backbone. The level of delocalization can be characterized by the induced bond length alternation (BLA), with shorter BLA connected with strong delocalization and vice versa. The accurate description of this structural parameter can be considered a benchmark for testing the capability of different electronic structure methods for self-interaction error (SIE) removal and electron correlation inclusion. Density functional theory (DFT), in its local or semi-local flavors, suffers from SIE and, thus, underestimates the BLA compared to self-interaction-free methods. In this work, we utilize the Fermi-Löwdin orbital self-interaction correction (FLOSIC) method for one-electron self-interaction removal to characterize the BLA of five oligomers with increasing length extrapolated to the polymeric limit. We compare the self-interaction-free BLA to several DFT approximations, Møller-Plesset second-order perturbation theory (MP2), and the BLA obtained with the domain based local pair natural orbital CCSD(T) [DLPNO-CCSD(T)] approximation. Our findings show that FLOSIC corrects for the small BLA given by (semi-)local DFT approximations, but it tends to overcorrect with respect to CAM-B3LYP, MP2, and DLPNO-CCSD(T).

Assessment of calcium alginate gels as wall materials for encapsulation systems.

BACKGROUND: Calcium alginate gels are widely used to encapsulate active compounds. Some characteristic parameters of these gels are necessary to describe the release of active compounds through mechanistic mathematical models. In this work, transport and kinetics properties of calcium alginate gels were determined through simple experimental techniques. RESULTS: The weight-average molecular weight ( M ¯ w = 192 × 103 Da) and the fraction of residues of α-l-guluronic acid ( F G = 0.356) of sodium alginate were determined by capillary viscometry and 1 H-nuclear magnetic resonance at 25 °C, respectively. Considering the half egg-box model, both values were used to estimate the molecular weight of calcium alginate as M g = 2.02 × 105 Da. An effective diffusion coefficient of water ( D eff , w = 2.256 × 10-9 m2 s-1 ) in calcium alginate was determined using a diffusion cell at 37 °C. Finally, a kinetics constant of depolymerization ( k m = 9.72 × 10-9 m3 mol-1 s-1 ) of calcium alginate was obtained considering dissolution of calcium to a medium under intestinal conditions. CONCLUSION: The experimental techniques used are simple and easily reproducible. The obtained values may be useful in the design, production, and optimization of the alginate-based delivery systems that require specific release kinetics of the encapsulated active compounds. © 2023 Society of Chemical Industry.

Generalized spin σ-SCF method.

We introduce a generalization of the σ-SCF method to approximate noncollinear spin ground and excited single-reference electronic states by minimizing the Hamiltonian variance. The new method is based on the σ-SCF method, originally proposed by Ye et al. [J. Chem. Phys. 147, 214104 (2017)], and provides a prescription to determine ground and excited noncollinear spin states on an equal footing. Our implementation was carried out utilizing an initial simulated annealing stage followed by a mean-field iterative self-consistent approach to simplify the cumbersome search introduced by generalizing the spin degrees of freedom. The simulated annealing stage ensures a broad exploration of the Hilbert space spanned by the generalized spin single-reference states with random complex element-wise rotations of the generalized density matrix elements in the simulated annealing stage. The mean-field iterative self-consistent stage employs an effective Fockian derived from the variance, which is utilized to converge tightly to the solutions. This process helps us to easily find complex spin structures, avoiding manipulating the initial guess. As proof-of-concept tests, we present results for Hn (n = 3-7) planar rings and polyhedral clusters with geometrical spin frustration. We show that most of these systems have noncollinear spin excited states that can be interpreted in terms of geometric spin frustration. These states are not directly targeted by energy minimization methods, which are meant to converge to the ground state. This stresses the capability of the σ-SCF methodology to find approximate noncollinear spin structures as mean-field excited states.

Comparison of five commercial kits for isolation of total RNA in samples of WSSV-infected shrimp.

Viral diseases are the most serious threat to the expansion and development of shrimp aquaculture. Rapid diagnosis of the white spot syndrome virus (WSSV), a lethal shrimp pathogen, is essential to restrict its spread and reduce the mortality of infected shrimp. This virus has globally affected the shrimp farming industry, with a devastating economic impact. Several studies have focused on the expression of WSSV transcripts to understand the molecular mechanisms governing the pathological development of the disease. Since gene expression studies and molecular diagnostics at the early stages of infection depend on the efficient isolation of high-quality RNA, the extraction methods should be carefully selected. However, previous comparisons of the performance of RNA isolation kits have yet to be systematically investigated. In this study, 5 commercial RNA extraction methods were compared in WSSV-infected shrimp. The highest total RNA yield (ng mg-1 tissue) was obtained using TRIzol. Even though the 260/280 nm absorption ratios showed significant differences, the methods showed good purity values (>2.0). RNA integrity was evaluated in a denaturing agarose gel electrophoresis, and degradation was observed after the total RNA samples were treated with DNase I. Finally, the method that allowed the earlier detection of WSSV transcripts by qRT-PCR was the Zymo Direct-zol RNA MiniPrep kit. This study shows that the amount of observed (or estimated) WSSV transcripts might be affected because of the RNA isolation method. In addition, these results may contribute to improve the accuracy of the results obtained in gene expression studies, for more sensitive and robust detection of WSSV.

Electron Dynamics in Open Quantum Systems: The Driven Liouville-von Neumann Methodology within Time-Dependent Density Functional Theory.

A first-principles approach to describe electron dynamics in open quantum systems driven far from equilibrium via external time-dependent stimuli is introduced. Within this approach, the driven Liouville-von Neumann methodology is used to impose open boundary conditions on finite model systems whose dynamics is described using time-dependent density functional theory. As a proof of concept, the developed methodology is applied to simple spin-compensated model systems, including a hydrogen chain and a graphitic molecular junction. Good agreement between steady-state total currents obtained via direct propagation and those obtained from the self-consistent solution of the corresponding Sylvester equation indicates the validity of the implementation. The capability of the new computational approach to analyze, from first principles, non-equilibrium dynamics of open quantum systems in terms of temporally and spatially resolved current densities is demonstrated. Future extensions of the approach toward the description of dynamical magnetization and decoherence effects are briefly discussed.

Use of FLOSIC for understanding anion-solvent interactions.

An Achille's heel of lower-rung density-functional approximations is that the highest-occupied-molecular-orbital energy levels of anions, known to be stable or metastable in nature, are often found to be positive in the worst case or above the lowest-unoccupied-molecular-orbital levels on neighboring complexes that are not expected to accept charge. A trianionic example, [Cr(C2O4)3]3-, is of interest for constraining models linking Cr isotope ratios in rock samples to oxygen levels in Earth's atmosphere over geological timescales. Here we describe how crowd sourcing can be used to carry out self-consistent Fermi-Löwdin-Orbital-Self-Interaction corrected calculations (FLOSIC) on this trianion in solution. The calculations give a physically correct description of the electronic structure of the trianion and water. In contrast, uncorrected local density approximation (LDA) calculations result in approximately half of the anion charge being transferred to the water bath due to the effects of self-interaction error. Use of group-theory and the intrinsic sparsity of the theory enables calculations roughly 125 times faster than our initial implementation in the large N limit reached here. By integrating charge density densities and Coulomb potentials over regions of space and analyzing core-level shifts of the Cr and O atoms as a function of position and functional, we unambiguously show that FLOSIC, relative to LDA, reverses incorrect solute-solvent charge transfer in the trianion-water complex. In comparison to other functionals investigated herein, including Hartree-Fock and the local density approximation, the FLOSIC Cr 1s eigenvalues provide the best agreement with experimental core ionization energies.

A Scan of Pleiotropic Immune Mediated Disease Genes Identifies Novel Determinants of Baseline FVIII Inhibitor Status in Hemophilia-A.

Hemophilia-A (HA) is caused by heterogeneous loss-of-function factor (F)VIII gene (F8)-mutations and deficiencies in plasma-FVIII-activity that impair intrinsic-pathway-mediated coagulation-amplification. The standard-of-care for severe-HA-patients is regular infusions of therapeutic-FVIII-proteins (tFVIIIs) but ~30% develop neutralizing-tFVIII-antibodies called "FVIII-inhibitors (FEIs)" and become refractory. We used the PATH study and ImmunoChip to scan immune-mediated-disease (IMD)-genes for novel and/or replicated genomic-sequence-variations associated with baseline-FEI-status while accounting for non-independence of data due to genetic-relatedness and F8-mutational-heterogeneity. The baseline-FEI-status of 450 North American PATH subjects-206 with black-African-ancestry and 244 with white-European-ancestry-was the dependent variable. The F8-mutation-data and a genetic-relatedness matrix were incorporated into a binary linear-mixed model of genetic association with baseline-FEI-status. We adopted a gene-centric-association-strategy to scan, as candidates, pleiotropic-IMD-genes implicated in the development of either ³2 autoimmune-/autoinflammatory-disorders (AADs) or ³1 AAD and FEIs. Baseline-FEI-status was significantly associated with SNPs assigned to NOS2A (rs117382854; p=3.2E-6) and B3GNT2 (rs10176009; p=5.1E-6), which have functions in anti-microbial-/-tumoral-immunity. Among IMD-genes implicated in FEI-risk previously, we identified strong associations with CTLA4 assigned SNPs (p=2.2E-5). The F8-mutation-effect underlies ~15% of the total heritability for baseline-FEI-status. Additive genetic heritability and SNPs in IMD-genes account for >50% of the patient-specific variability in baseline-FEI-status. Race is a significant determinant independent of F8-mutation-effects and non-F8-genetics.

Genotype-by-socioeconomic status interaction influences heart disease risk scores and carotid artery thickness in Mexican Americans: the predominant role of education in comparison to household income and socioeconomic index.

Background: Socioeconomic status (SES) is a potent environmental determinant of health. To our knowledge, no assessment of genotype-environment interaction has been conducted to consider the joint effects of socioeconomic status and genetics on risk for cardiovascular disease (CVD). We analyzed Mexican American Family Studies (MAFS) data to evaluate the hypothesis that genotype-by-environment interaction (GxE) is an important determinant of variation in CVD risk factors. Methods: We employed a linear mixed model to investigate GxE in Mexican American extended families. We studied two proxies for CVD [Pooled Cohort Equation Risk Scores/Framingham Risk Scores (FRS/PCRS) and carotid artery intima-media thickness (CA-IMT)] in relation to socioeconomic status as determined by Duncan's Socioeconomic Index (SEI), years of education, and household income. Results: We calculated heritability for FRS/PCRS and carotid artery intima-media thickness. There was evidence of GxE due to additive genetic variance heterogeneity and genetic correlation for FRS, PCRS, and CA-IMT measures for education (environment) but not for household income or SEI. Conclusion: The genetic effects underlying CVD are dynamically modulated at the lower end of the SES spectrum. There is a significant change in the genetic architecture underlying the major components of CVD in response to changes in education.

Comparative Density Functional Theory Study of Magnetic Exchange Couplings in Dinuclear Transition-Metal Complexes.

Multicenter transition-metal complexes (MCTMs) with magnetically interacting ions have been proposed as components for information-processing devices and storage units. For any practical application of MCTMs as magnetic units, it is crucial to characterize their magnetic behavior, and in particular, the isotropic magnetic exchange coupling, J, between its magnetic centers. Due to the large size of typical MCTMs, density functional theory is the only practical electronic structure method for evaluating the J coupling. Here, we assess the accuracy of different density functional approximations for predicting the magnetic couplings of eight dinuclear transition-metal complexes, including five dimanganese, two dicopper, and one divanadium with known reliable experimental J couplings spanning from ferromagnetic to strong antiferromagnetic. The density functionals considered include global hybrid functionals which mix semilocal density functional approximations and exact exchange with a fixed admixing parameter, six local hybrid functionals where the admixing parameters are extended to be spatially dependent, the SCAN and r2SCAN meta-generalized gradient approximations (GGAs), and two widely used GGAs. We found that global hybrids tested in this work have a tendency to over-correct the error in magnetic coupling parameters from the Perdew-Burke-Ernzerhof (PBE) GGA as seen for manganese complexes. The performance of local hybrid density functionals shows no improvement in terms of bias and is scattered without a clear trend, suggesting that more efforts are needed for the extension from global to local hybrid density functionals for this particular property. The SCAN and r2SCAN meta-GGAs are found to perform as well as benchmark global hybrids on most tested complexes. We further analyze the charge density redistribution of meta-GGAs as well as global and local hybrid density functionals with respect to that of PBE, in connection to the self-interaction error or delocalization error.

Convolutional Neural Networks to Assist the Assessment of Lattice Parameters from X-ray Powder Diffraction.

This article presents the development of convolutional neural networks (CNNs) for the estimation of lattice parameters in organic compounds across various crystal systems. A comprehensive collection of 92,085 organic compounds was utilized to train the CNNs, encompassing crystals with unit cells containing up to 512 atoms and a maximum unit cell volume of 8000 Å3. Simulated diffraction patterns were generated for each compound, comprising four diffraction patterns with different crystal sizes. These diffraction patterns were generated within a 2θ window of 3-60°, employing a step size of 0.02051°. Two distinct CNN architectures were developed with differing input data. The first CNN, referred to as XRD-CNN, was trained solely on diffraction patterns. In the test set, XRD-CNN demonstrated a mean absolute percentage error (MAPE) of 11.04% for unit cell vectors, 7.40% for angles, and 26.83% for unit cell volume. The second CNN, XRDElem-CNN, incorporated a binary representation of atoms within the unit cell as an additional input. XRDElem-CNN achieved improved performance, yielding MAPE values of 4.73% for unit vectors, 6.49% for angles, and 6.05% for the unit cell volume. To validate the performance of XRDElem-CNN, real diffraction patterns obtained from a conventional laboratory diffractometer (Cu Kα wavelength) were employed. Various representations of atoms within the unit cell were proposed, which were computationally efficient for evaluation with the CNNs. The assessed lattice parameters by XRDElem-CNN were validated using the Lp-search method, showing agreement with the reported values.

Cocktail-party listening and cognitive abilities show strong pleiotropy.

Introduction: The cocktail-party problem refers to the difficulty listeners face when trying to attend to relevant sounds that are mixed with irrelevant ones. Previous studies have shown that solving these problems relies on perceptual as well as cognitive processes. Previously, we showed that speech-reception thresholds (SRTs) on a cocktail-party listening task were influenced by genetic factors. Here, we estimated the degree to which these genetic factors overlapped with those influencing cognitive abilities. Methods: We measured SRTs and hearing thresholds (HTs) in 493 listeners, who ranged in age from 18 to 91 years old. The same individuals completed a cognitive test battery comprising 18 measures of various cognitive domains. Individuals belonged to large extended pedigrees, which allowed us to use variance component models to estimate the narrow-sense heritability of each trait, followed by phenotypic and genetic correlations between pairs of traits. Results: All traits were heritable. The phenotypic and genetic correlations between SRTs and HTs were modest, and only the phenotypic correlation was significant. By contrast, all genetic SRT-cognition correlations were strong and significantly different from 0. For some of these genetic correlations, the hypothesis of complete pleiotropy could not be rejected. Discussion: Overall, the results suggest that there was substantial genetic overlap between SRTs and a wide range of cognitive abilities, including abilities without a major auditory or verbal component. The findings highlight the important, yet sometimes overlooked, contribution of higher-order processes to solving the cocktail-party problem, raising an important caveat for future studies aiming to identify specific genetic factors that influence cocktail-party listening.

Genome-wide significant risk loci for mood disorders in the Old Order Amish founder population.

Genome-wide association studies (GWAS) of mood disorders in large case-control cohorts have identified numerous risk loci, yet pathophysiological mechanisms remain elusive, primarily due to the very small effects of common variants. We sought to discover risk variants with larger effects by conducting a genome-wide association study of mood disorders in a founder population, the Old Order Amish (OOA, n = 1,672). Our analysis revealed four genome-wide significant risk loci, all of which were associated with >2-fold relative risk. Quantitative behavioral and neurocognitive assessments (n = 314) revealed effects of risk variants on sub-clinical depressive symptoms and information processing speed. Network analysis suggested that OOA-specific risk loci harbor novel risk-associated genes that interact with known neuropsychiatry-associated genes via gene interaction networks. Annotation of the variants at these risk loci revealed population-enriched, non-synonymous variants in two genes encoding neurodevelopmental transcription factors, CUX1 and CNOT1. Our findings provide insight into the genetic architecture of mood disorders and a substrate for mechanistic and clinical studies.

Density Matrix Implementation of the Fermi-Löwdin Orbital Self-Interaction Correction Method.

The Fermi-Löwdin orbital self-interaction correction (FLOSIC) method effectively provides a transformation from canonical orbitals to localized Fermi-Löwdin orbitals which are used to remove the self-interaction error in the Perdew-Zunger (PZ) framework. This transformation is solely determined by a set of points in space, called Fermi-Löwdin descriptors (FODs), and the occupied canonical orbitals or the density matrix. In this work, we provide a detailed workflow for the implementation of the FLOSIC method for removal of self-interaction error in DFT calculations in an orbital-by-orbital basis that takes advantage of the unitary invariant nature of the FLOSIC method. In this way, it is possible to cast the self-consistent energy minimization at fixed FODs in the same manner than standard Kohn-Sham with one additional term in the Kohn-Sham Hamiltonian that introduces the PZ self-interaction correction. Each energy minimization iteration is divided in two substeps, one for the density matrix and one for the FODs. Expressions for the effective Kohn-Sham matrix and FOD gradients are provided such that its implementation is suitable for most electronic structure codes. We analyze the convergence characteristics of the algorithm and present applications for the evaluation of NMR shielding constants and real-time time-dependent DFT simulations based on the Liouville-von Neumann equation to calculate excitation energies.

Alzheimer's disease and synapse Loss: What can we learn from induced pluripotent stem Cells?

BACKGROUND: Synaptic dysfunction is a major contributor to Alzheimers disease (AD) pathogenesis in addition to the formation of neuritic ß-amyloid plaques and neurofibrillary tangles of hyperphosphorylated Tau protein. However, how these features contribute to synaptic dysfunction and axonal loss remains unclear. While years of considerable effort have been devoted to gaining an improved understanding of this devastating disease, the unavailability of patient-derived tissues, considerable genetic heterogeneity, and lack of animal models that faithfully recapitulate human AD have hampered the development of effective treatment options. Ongoing progress in human induced pluripotent stem cell (hiPSC) technology has permitted the derivation of patient- and disease-specific stem cells with unlimited self-renewal capacity. These cells can differentiate into AD-affected cell types, which support studies of disease mechanisms, drug discovery, and the development of cell replacement therapies in traditional and advanced cell culture models. AIM OF REVIEW: To summarize current hiPSC-based AD models, highlighting the associated achievements and challenges with a primary focus on neuron and synapse loss. KEY SCIENTIFIC CONCEPTS OF REVIEW: We aim to identify how hiPSC models can contribute to understanding AD-associated synaptic dysfunction and axonal loss. hiPSC-derived neural cells, astrocytes, and microglia, as well as more sophisticated cellular organoids, may represent reliable models to investigate AD and identify early markers of AD-associated neural degeneration.

Surgical mortality in patients in extremis: futility in emergency abdominal surgery.

BACKGROUND: The number of older patients with multiple comorbidities in the emergency service is increasingly frequent, which implies the risk of incurring in futile surgical interventions. Some interventions generate false expectations of survival or quality of life in patients and families and represent a negligible therapeutic benefit in patients whose chances of survival are minimal. In order to address this dilemma, we describe mortality in a cohort of patients undergoing emergency laparotomy with a risk ≥ 75% per the ACS NSQIP Surgical Risk Calculator. METHODS: A retrospective observational study was designed to analyze postoperative mortality and factors associated with postoperative mortality in a cohort of patients undergoing emergency laparotomy between January 2018 and December 2021 in a high-complexity hospital who had a mortality risk ≥ 75% per the ACS NSQIP Surgical Risk Calculator. RESULTS: A total of 890 emergency laparotomies were performed during the study period, and 50 patients were included for the analysis. Patient median age was 82.5 (IQR: 18.25) years old and 33 (66.00%) were male. The most frequent diagnoses were mesenteric ischemia 21 (42%) and secondary peritonitis 18 (36%). Mortality in the series was 92%. Twenty-four (54.34%) died within the first 24 h of the postoperative period; 11 (23.91%) within 72 h and 10 (21.73%) within 30 days. APACHE II and SOFA scores were statistically significantly higher in patients who died. CONCLUSIONS: All available tools should be used to make decisions, with the most reliable and objective information possible, and be particularly vigilant in patients at extreme risk (mortality risk greater than 75% according to ACS NSQIP Surgical Risk Calculator) to avoid futility and its consequences. The available information should be shared with the patient, the family, or their guardians through an assertive and empathetic communication strategy. It is necessary to insist on a culture of surgical ethics based on reflection and continuous improvement in patient care and to know how to accompany them in order to have a proper death.