The muscle and neural architecture of Taenia crassiceps cysticerci revisited; implications on head-tail polarization of the larvae.

Taenia crassiceps has been used for decades as an experimental model for the study of human and porcine cysticercosis. Even though, its life cycle, tissue organization, ultrastructure and immune response elicited in the host, have been extensively described, there are many other biological questions remaining to be addressed. In the present study we revisited the muscle and neural architecture of cysticerci in two of the most frequently used strains (WFU and ORF), using conventional staining and confocal microscopy imaging, aiming to assemble an updated anatomy. Differences between both strains, including polarization processes during development of the young budding larvae, are emphasized. We also performed a search for genes that have been related to peptidergic neural processes in other related flatworms. These findings can help to understand the anatomical and molecular consequences of the scolex presence or absence in both strains.

Low-Scaling Algorithms for GW and Constrained Random Phase Approximation Using Symmetry-Adapted Interpolative Separable Density Fitting.

We present low-scaling algorithms for GW and constrained random phase approximation based on a symmetry-adapted interpolative separable density fitting (ISDF) procedure that incorporates the space-group symmetries of crystalline systems. The resulting formulations scale cubically, with respect to system size, and linearly with the number of k-points, regardless of the choice of single-particle basis and whether a quasiparticle approximation is employed. We validate these methods through comparisons with published literature and demonstrate their efficiency in treating large-scale systems through the construction of downfolded many-body Hamiltonians for carbon dimer defects embedded in hexagonal boron nitride supercells. Our work highlights the efficiency and general applicability of ISDF in the context of large-scale many-body calculations with k-point sampling beyond density functional theory.

Metal-Insulator Transition in a Semiconductor Heterobilayer Model.

Transition metal dichalcogenide superlattices provide an exciting new platform for exploring and understanding a variety of phases of matter. The moiré continuum Hamiltonian, of two-dimensional jellium in a modulating potential, provides a fundamental model for such systems. Accurate computations with this model are essential for interpreting experimental observations and making predictions for future explorations. In this work, we combine two complementary quantum Monte Carlo (QMC) methods, phaseless auxiliary field quantum Monte Carlo and fixed-phase diffusion Monte Carlo, to study the ground state of this Hamiltonian. We observe a metal-insulator transition between a paramagnet and a 120° Néel ordered state as the moiré potential depth and the interaction strength are varied. We find significant differences from existing results by Hartree-Fock and exact diagonalization studies. In addition, we benchmark density-functional theory, and suggest an optimal hybrid functional which best approximates our QMC results.

Low-Scaling Algorithm for the Random Phase Approximation Using Tensor Hypercontraction with k-point Sampling.

We present a low-scaling algorithm for the random phase approximation (RPA) with k-point sampling in the framework of tensor hypercontraction (THC) for electron repulsion integrals (ERIs). The THC factorization is obtained via a revised interpolative separable density fitting (ISDF) procedure with a momentum-dependent auxiliary basis for generic single-particle Bloch orbitals. Our formulation does not require preoptimized interpolating points or auxiliary bases, and the accuracy is systematically controlled by the number of interpolating points. The resulting RPA algorithm scales linearly with the number of k-points and cubically with the system size without any assumption on sparsity or locality of orbitals. The errors of ERIs and RPA energy show rapid convergence with respect to the size of the THC auxiliary basis, suggesting a promising and robust direction to construct efficient algorithms of higher order many-body perturbation theories for large-scale systems.

Association between Love Breakup and Suicidal Ideation in Peruvian Medical Students: A Cross-Sectional Study during the COVID-19 Pandemic.

Objective: We aimed to determine the association between a major romantic breakup and suicidal ideation in medical students from three universities in Peru. Methods: A cross-sectional study was conducted during the first pandemic wave in 2021 on medical students from three universities in northern Peru. The outcome was suicidal ideation, measured with question nine of the PHQ-9. The exposure was the experience of a major love breakup during the pandemic. In addition, its association with other covariates (age, sex, family members infected with COVID-19, deceased family members with COVID-19, insomnia, and anxiety, among others) was examined. Results and discussions: Out of 370 students, 19.5% reported a major love breakup during the pandemic (95%CI: 15.5-23.8), and 34.3% had suicidal ideation (95%CI: 29.4-39.4). Having a major love breakup was associated with a higher prevalence of suicidal ideation (PR: 1.49, 95%CI: 1.32-1.67). Moderate insomnia (PR: 2.56, 95%CI: 1.70-3.87) and anxiety symptoms (PR: 1.94, 1.10-3.44) were also associated with suicidal ideation. Conclusion: Our study provides evidence of a significant association between a major love breakup and suicidal ideation. This finding emphasizes the need for further research to better understand this association and inform the development of effective suicide prevention policies in medical education.

Long-term potentiation and its neurotrophin-dependent modulation in the superior cervical ganglion of the rat are influenced by KCNQ channel function.

Ganglionic long-term potentiation (gLTP) in the rat superior cervical ganglion (SCG) is differentially modulated by neurotrophic factors (Nts): brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF). KCNQ/M channels, key regulators of neuronal excitability, and firing pattern are modulated by Nts; therefore, they might contribute to gLTP expression and to the Nts-dependent modulation of gLTP. In the SCG of rats, we characterized the presence of the KCNQ2 isoform and the effects of opposite KCNQ/M channel modulators on gLTP in control condition and under Nts modulation. Immunohistochemical and reverse transcriptase polymerase chain reaction analyses showed the expression of the KCNQ2 isoform. We found that 1 µmol/L XE991, a channel inhibitor, significantly reduced gLTP (∼50%), whereas 5 µmol/L flupirtine, a channel activator, significantly increased gLTP (1.3- to 1.7-fold). Both modulators counterbalanced the effects of the Nts on gLTP. Data suggest that KCNQ/M channels are likely involved in gLTP expression and in the modulation exerted by BDNF and NGF.

Association between diabetes and cancer. Current mechanistic insights into the association and future challenges.

Compelling pieces of epidemiological, clinical, and experimental research have demonstrated that Diabetes mellitus (DM) is a major risk factor associated with increased cancer incidence and mortality in many human neoplasms. In the pathophysiology context of DM, many of the main classical actors are relevant elements that can fuel the different steps of the carcinogenesis process. Hyperglycemia, hyperinsulinemia, metabolic inflammation, and dyslipidemia are among the classic contributors to this association. Furthermore, new emerging actors have received particular attention in the last few years, and compelling data support that the microbiome, the epigenetic changes, the reticulum endoplasmic stress, and the increased glycolytic influx also play important roles in promoting the development of many cancer types. The arsenal of glucose-lowering therapeutic agents used for treating diabetes is wide and diverse, and a growing body of data raised during the last two decades has tried to clarify the contribution of therapeutic agents to this association. However, this research area remains controversial, because some anti-diabetic drugs are now considered as either promotors or protecting elements. In the present review, we intend to highlight the compelling epidemiological shreds of evidence that support this association, as well as the mechanistic contributions of many of these potential pathological mechanisms, some controversial points as well as future challenges.

Association between love breakup and suicidal ideation in Peruvian medical students: a cross-sectional study during the COVID-19 pandemic.

Objective: We aimed to determine the association between a major romantic breakup and suicidal ideation in medical students from three universities in Peru. Methods: A cross-sectional study was conducted during the first pandemic wave in 2021 on medical students from three universities in northern Peru. The outcome was suicidal ideation, measured with question nine of the Patient Health Questionnaire-9 (PHQ-9). Generalized Anxiety Disorder Scale-7 (GAD-7) and Insomnia Severity Index (ISI) were also used to assess mental health symptoms. The exposure was the experience of a major love breakup during the pandemic. In addition, its association with other covariates (age, sex, family members infected with COVID-19, deceased family members with COVID-19, insomnia, and anxiety, among others) was examined. Results and discussions: Out of 370 students, 19.5% reported a major love breakup during the pandemic (95%CI: 15.5-23.8), and 34.3% had suicidal ideation (95%CI: 29.4-39.4). Having a major love breakup was associated with a higher prevalence of suicidal ideation (PR: 1.49, 95%CI: 1.32-1.67, p < 0.001). Moderate insomnia (PR: 2.56, 95%CI: 1.70-3.87, p < 0.001) and anxiety symptoms (PR: 1.94, 1.10-3.44, p = 0.023) were also associated with suicidal ideation. Conclusion: Our study provides evidence of a significant association between a major love breakup and suicidal ideation. This finding emphasizes the need for further research to better understand this association and inform the development of effective suicide prevention policies in medical education.

Smartphone overuse, depression & anxiety in medical students during the COVID-19 pandemic.

INTRODUCTION: Medical students have made particular use of smartphones during the COVID-19 pandemic. Although higher smartphone overuse has been observed, its effect on mental disorders is unclear. This study aimed to assess the association between smartphone overuse and mental disorders in Peruvian medical students during the COVID-19 pandemic. METHODS: A cross-sectional study was conducted in 370 students aged between 16 and 41 years (median age: 20) in three universities from July to October 2020. A survey including Smartphone Dependence and Addiction Scale, PHQ-9, and GAD-7 was applied. Prevalence ratios were estimated using generalized linear models. RESULTS: Smartphone overuse was a common feature among students (n = 291, 79%). Depressive symptoms were present in 290 (78%) students and anxiety symptoms in 255 (69%). Adjusted for confounders, addictive/dependent smartphone use was significantly associated with presence of depressive symptoms (PR = 1.29, 95% CI: 1.20-1.38 for dependent use; PR = 1.30, 95% CI: 1.12-1.50 for addictive use). Also, addictive/dependent smartphone use was significantly associated with presence of anxiety symptoms (PR = 1.59, 95% CI: 1.14-2.23 for dependent use; PR = 1.61, 95% CI: 1.07-2.41 for addictive use). CONCLUSIONS: Our findings suggest that medical students exposed to smartphone overuse are vulnerable to mental disorders. Overuse may reflect an inappropriate way of finding emotional relief, which may significantly affect quality of life and academic performance. Findings would assist faculties to establish effective measures for prevention of smartphone overuse.

The RAGE/multiligand axis: a new actor in tumor biology.

The receptor for advanced glycation end-products (RAGE) is a multiligand binding and single-pass transmembrane protein which actively participates in several chronic inflammation-related diseases. RAGE, in addition to AGEs, has a wide repertoire of ligands, including several damage-associated molecular pattern molecules or alarmins such as HMGB1 and members of the S100 family proteins. Over the last years, a large and compelling body of evidence has revealed the active participation of the RAGE axis in tumor biology based on its active involvement in several crucial mechanisms involved in tumor growth, immune evasion, dissemination, as well as by sculpturing of the tumor microenvironment as a tumor-supportive niche. In the present review, we will detail the consequences of the RAGE axis activation to fuel essential mechanisms to guarantee tumor growth and spreading.

Spectral Functions from Auxiliary-Field Quantum Monte Carlo without Analytic Continuation: The Extended Koopmans' Theorem Approach.

We explore the extended Koopmans' theorem (EKT) within the phaseless auxiliary-field quantum Monte Carlo (AFQMC) method. The EKT allows for the direct calculation of electron addition and removal spectral functions using reduced density matrices of the N-particle system and avoids the need for analytic continuation. The lowest level of EKT with AFQMC, called EKT1-AFQMC, is benchmarked using atoms, small molecules, 14-electron and 54-electron uniform electron gas supercells, and a minimal unit cell model of diamond at the Γ-point. Via comparison with numerically exact results (when possible) and coupled-cluster methods, we find that EKT1-AFQMC can reproduce the qualitative features of spectral functions for Koopmans-like charge excitations with errors in peak locations of less than 0.25 eV in a finite basis. We also note the numerical difficulties that arise in the EKT1-AFQMC eigenvalue problem, especially when back-propagated quantities are very noisy. We show how a systematic higher-order EKT approach can correct errors in EKT1-based theories with respect to the satellite region of the spectral function. Our work will be of use for the study of low-energy charge excitations and spectral functions in correlated molecules and solids where AFQMC can be reliably performed for both energy and back propagation.

Racial and Ethnic Disparities in Perceived Barriers to Health Care Among U.S. Adults With Intellectual and Developmental Disabilities.

Barriers to health care access can greatly affect one's health status. Research shows that U.S. adults with intellectual and developmental disabilities (IDD) have poor health and face barriers such as long waits for appointments. However, whether barriers differ by race and ethnicity has not been examined. We conducted a secondary data analysis using the 2002-2011 Medical Expenditure Panel Survey dataset, and compared perceived barriers of community-living U.S. adults with IDD in three racial and ethnic groups (White, Black, and Latinx). Specifically, we examined the top reasons for not having usual source of care, delaying or foregoing medical care. For Black and Latinx adults with IDD, the most-mentioned reasons for not having usual source of care, delaying or foregoing medical care were "don't like/don't trust doctors," "don't use doctors," and "don't know where to get care." In comparison, the White adults with IDD group's biggest perceived barriers were location and insurance related. All groups cited that being unable to afford care was a top reason for delaying or foregoing care. Policies/interventions to improve health care access in racial/ethnic minorities with IDD must first address the topic of developing trust between patients and the health professions. Insurance and the rising costs of care are also key areas that need attention.

Reduction in the potential distribution of bumble bees (Apidae: Bombus) in Mesoamerica under different climate change scenarios: Conservation implications.

Bumble bees are an ecologically and economically important group of pollinating insects worldwide. Global climate change is predicted to affect bumble bee ecology including habitat suitability and geographic distribution. Our study aims to estimate the impact of projected climate change on 18 Mesoamerican bumble bee species. We used ecological niche modeling (ENM) using current and future climate emissions scenarios (representative concentration pathway 4.5, 6.0, and 8.5) and models (CCSM4, HadGEM2-AO, and MIROC-ESM-CHEM). Regardless of the scenario and model applied, our results suggest that all bumble bee species are predicted to undergo a reduction in their potential distribution and habitat suitability due to projected climate change. ENMs based on low emission scenarios predict a distribution loss ranging from 7% to 67% depending on the species for the year 2050. Furthermore, we discovered that the reduction of bumble bee geographic range shape will be more evident at the margins of their distribution. The reduction of suitable habitat is predicted to be accompanied by a 100-500 m upslope change in altitude and 1-581 km shift away from the current geographic centroid of a species' distribution. On average, protected natural areas in Mesoamerica cover ~14% of each species' current potential distribution, and this proportion is predicted to increase to ~23% in the high emission climate change scenarios. Our models predict that climate change will reduce Mesoamerican bumble bee habitat suitability, especially for rare species, by reducing their potential distribution ranges and suitability. The small proportion of current and future potential distribution falling in protected natural areas suggests that such areas will likely have marginal contribution to bumble bee habitat conservation. Our results have the capacity to inform stakeholders in designing effective landscape management for bumble bees, which may include developing restoration plans for montane pine oak forests habitats and native flowering plants.

A phaseless auxiliary-field quantum Monte Carlo perspective on the uniform electron gas at finite temperatures: Issues, observations, and benchmark study.

We investigate the viability of the phaseless finite-temperature auxiliary-field quantum Monte Carlo (ph-FT-AFQMC) method for ab initio systems using the uniform electron gas as a model. Through comparisons with exact results and FT coupled cluster theory, we find that ph-FT-AFQMC is sufficiently accurate at high to intermediate electronic densities. We show, both analytically and numerically, that the phaseless constraint at FT is fundamentally different from its zero-temperature counterpart (i.e., ph-ZT-AFQMC), and generally, one should not expect ph-FT-AFQMC to agree with ph-ZT-AFQMC in the low-temperature limit. With an efficient implementation, we are able to compare exchange-correlation energies to the existing results in the thermodynamic limit and find that the existing parameterizations are highly accurate. In particular, we found that ph-FT-AFQMC exchange-correlation energies are in better agreement with a known parameterization than is restricted path-integral MC in the regime of Θ ≤ 0.5 and rs ≤ 2, which highlights the strength of ph-FT-AFQMC.

Comparison of dilute acid pretreatment of agave assisted by microwave versus ultrasound to enhance enzymatic hydrolysis.

A comparison between microwave and ultrasound irradiations in the agave pretreatment using dilute sulfuric acid as catalyst was assessed for the first time. Pretreatments were performed using a Taguchi Orthogonal Array L9 (34) to improve the hemicellulose removal and the agave digestibility. The results showed that under optimal conditions, the hemicellulose removal was superior in the pretreatment assisted with microwave (77.5%) compared to ultrasound (28.2%). Enzymatic hydrolysis yield of agave pretreated with microwave (MWOC) was 2-fold higher than agave pretreated with ultrasound (USOC). The relatively mild conditions of pretreatment with MWOC allowed to obtain a hydrolyzed free of inhibitors with a high glucose concentration (47.7 g/L) at low solids loading (10% w/v). However, these conditions did not have a significant effect over the agave pretreated with ultrasound. The pretreatment assisted with MWOC allowed to reduce time and temperature of the process compared to pretreatment with conventional heating.

Accelerating the convergence of auxiliary-field quantum Monte Carlo in solids with optimized Gaussian basis sets.

We investigate the use of optimized correlation-consistent Gaussian basis sets for the study of insulating solids with auxiliary-field quantum Monte Carlo (AFQMC). The exponents of the basis set are optimized through the minimization of the second-order Møller-Plesset perturbation theory (MP2) energy in a small unit cell of the solid. We compare against other alternative basis sets proposed in the literature, namely, calculations in the Kohn-Sham basis and in the natural orbitals of an MP2 calculation. We find that our optimized basis sets accelerate the convergence of the AFQMC correlation energy compared to a Kohn-Sham basis and offer similar convergence to MP2 natural orbitals at a fraction of the cost needed to generate them. We also suggest the use of an improved, method independent, MP2-based basis set correction that significantly reduces the required basis set sizes needed to converge the correlation energy. With these developments, we study the relative performance of these basis sets in LiH, Si, and MgO and determine that our optimized basis sets yield the most consistent results as a function of volume. Using these optimized basis sets, we systematically converge the AFQMC calculations to the complete basis set and thermodynamic limit and find excellent agreement with experiment for the systems studied. Although we focus on AFQMC, our basis set generation procedure is independent of the subsequent correlated wavefunction method used.

QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion quantum Monte Carlo.

We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility. The auxiliary field QMC (AFQMC) implementation has been greatly expanded to include k-point symmetries, tensor-hypercontraction, and accelerated graphical processing unit (GPU) support. These scaling and memory reductions greatly increase the number of orbitals that can practically be included in AFQMC calculations, increasing the accuracy. Advances in real space methods include techniques for accurate computation of bandgaps and for systematically improving the nodal surface of ground state wavefunctions. Results of these calculations can be used to validate application of more approximate electronic structure methods, including GW and density functional based techniques. To provide an improved foundation for these calculations, we utilize a new set of correlation-consistent effective core potentials (pseudopotentials) that are more accurate than previous sets; these can also be applied in quantum-chemical and other many-body applications, not only QMC. These advances increase the efficiency, accuracy, and range of properties that can be studied in both molecules and materials with QMC and QMCPACK.

Accelerating Auxiliary-Field Quantum Monte Carlo Simulations of Solids with Graphical Processing Units.

We outline how auxiliary-field quantum Monte Carlo (AFQMC) can leverage graphical processing units (GPUs) to accelerate the simulation of solid state systems. By exploiting conservation of crystal momentum in the one- and two-electron integrals, we show how to efficiently formulate the algorithm to best utilize current GPU architectures. We provide a detailed description of different optimization strategies and profile our implementation relative to standard approaches, demonstrating a factor of 40 speedup over a CPU implementation. With this increase in computational power, we demonstrate the ability of AFQMC to systematically converge solid state calculations with respect to basis set and system size by computing the cohesive energy of carbon in the diamond structure to within 0.02 eV of the experimental result.