Miracle-dz/UniFAR-FTUs huggingface dataset:
Whole‐brain neural connectivity to cholinergic neurons in the nucleus basalis of Meynert

The cholinergic neurons in the nucleus basalis of Meynert (NBM) are a key structure in cognition, the dysfunction of which is associated with various neurological disorders, especially dementias. However, the whole‐brain neural connectivity to cholinergic neurons in the NBM remains to be further and comprehensively researched. Using virus‐based, specific, retrograde, and anterograde tracing, we illustrated the monosynaptic inputs and axon projections of NBM cholinergic neurons in choline acetyltransferase (ChAT)‐Cre transgenic mice. Our results showed that NBM cholinergic neurons received mainly inputs from the caudate putamen and the posterior limb of the anterior commissure in the subcortex. Moreover, the majority of cholinergic terminals from the NBM were observed in the cortex mantle, including the motor cortex, sensory cortex, and visual cortex. Interestingly, although NBM cholinergic neurons received input projections from the caudate putamen, interstitial nucleus of the posterior limb of the anterior commissure, and central amygdaloid nucleus, NBM cholinergic neurons sparsely sent axon projection to innervate these areas. Furthermore, primary motor cortex, secondary motor cortex, and primary somatosensory cortex received abundant inputs from the NBM but sent few outputs to the NBM. Taken together, our results reveal the detailed and specific connectivity of cholinergic neurons of the NBM and provide a neuroanatomic foundation for further studies to explore the important physiological functions of NBM cholinergic neurons.
On the degree for oriented quasi-Fredholm maps: its uniqueness and its effective extension of the Leray-Schauder degree

In a previous paper, the first and third author developed a~degree theory for oriented locally compact perturbations of $C\sp{1}$ Fredholm maps of index zero between real Banach spaces. In the spirit of a celebrated Amann--Weiss paper, we prove that this degree is unique if it is assumed to satisfy three axioms: Normalization, Additivity and Homotopy invariance. Taking into account that any compact vector field has a canonical orientation, from our uniqueness result we shall deduce that the above degree provides an effective extension of the Leray--Schauder degree.
Emerging insights into ethnic-specific TP53 germline variants

Abstract The recent expansion of human genomics repositories has facilitated the discovery of novel TP53 variants in populations of different ethnic origins. Interpreting TP53 variants is a major clinical challenge because they are functionally diverse, confer highly variable predisposition to cancer (including elusive low-penetrance alleles), and interact with genetic modifiers that alter tumor susceptibility. Here, we discuss how a cancer risk continuum may relate to germline TP53 mutations on the basis of our current review of genotype–phenotype studies and an integrative analysis combining functional and sequencing datasets. Our study reveals that each ancestry contains a distinct TP53 variant landscape defined by enriched ethnic-specific alleles. In particular, the discovery and characterization of suspected low-penetrance ethnic-specific variants with unique functional consequences, including P47S (African), G334R (Ashkenazi Jewish), and rs78378222 (Icelandic), may provide new insights in terms of managing cancer risk and the efficacy of therapy. Additionally, our analysis highlights infrequent variants linked to milder cancer phenotypes in various published reports that may be underdiagnosed and require further investigation, including D49H in East Asians and R181H in Europeans. Overall, the sequencing and projected functions of TP53 variants arising within ethnic populations and their interplay with modifiers, as well as the emergence of CRISPR screens and AI tools, are now rapidly improving our understanding of the cancer susceptibility spectrum, leading toward more accurate and personalized cancer risk assessments.
Convex Optimization Algorithms for Multiple Source Localization Based on Received Signal Strength Measurements

Decaying with the increasing of signal propagation distance, Received Signal Strength (RSS) is used in the wireless localization due to its low cost and easily implementation. When the transmit power is unavailable, two convex optimization algorithms including semi definite programming (SDP), second order cone and semi definite programming (SOC/SDP) are designed to estimate the source locations by relaxing the non-convex problem as convex optimization. The corresponding CramerRao lower bound (CRLB) of the problem is derived. The simulations demonstrate that the SOC/SDP algorithm provides the similar accuracy performance compared with the SDP algorithm. However the computational complexity of SOC/SDP is lower than that of the SDP due to the less variables and equality constraints. When perfect knowledge of the path loss exponent is available, the simulations also show that the accuracy performance of the proposed convex optimization algorithms degrades as the path loss exponent increases.
Analysis of Genome-Wide Mutational Dependence in Naturally Evolving Mycobacterium tuberculosis Populations

Abstract Pathogenic microorganisms are in a perpetual struggle for survival in changing host environments, where host pressures necessitate changes in pathogen virulence, antibiotic resistance, or transmissibility. The genetic basis of phenotypic adaptation by pathogens is difficult to study in vivo. In this work, we develop a phylogenetic method to detect genetic dependencies that promote pathogen adaptation using 31,428 in vivo sampled Mycobacterium tuberculosis genomes, a globally prevalent bacterial pathogen with increasing levels of antibiotic resistance. We find that dependencies between mutations are enriched in antigenic and antibiotic resistance functions and discover 23 mutations that potentiate the development of antibiotic resistance. Between 11% and 92% of resistant strains harbor a dependent mutation acquired after a resistance-conferring variant. We demonstrate the pervasiveness of genetic dependency in adaptation of naturally evolving populations and the utility of the proposed computational approach.
Direct Fuzzy Adaptive Regulation for High-Order Delayed Systems: A Lyapunov–Razumikhin Function Method

A slow time-delay assumption restricts the application of control approaches for numerous systems which are constantly affected by multiple uncertainties, including parameters, control coefficients, and the asymmetric dead-zone input. This work presents a new adaptive method for a class of high-order nonlinear delayed systems by removing the so-called slow time-delay assumption and multiple uncertainties. Remarkably, with a novel Lyapunov–Razumikhin (L-R) function and a direct fuzzy adaptive regulation scheme, a memoryless adaptive feedback controller is skillfully constructed to guarantee that the output tracks the given reference signal while keeping the boundedness of all closed-system signals. Finally, the presented scheme is applied to control a single-link robot system.
Proportion of early extubation and short-term outcomes after esophagectomy: a retrospective cohort study

Background: The proportion of early extubation after esophagectomy varies among hospitals; however, the impact on clinical outcomes is unclear. The aim of this retrospective study was to evaluate associations between the proportion of early extubation in hospitals and short-term outcomes after esophagectomy. Because there is no consensus regarding the optimal timing for extubation, the authors considered that hospitals’ early extubation proportion reflects the hospital-level extubation strategy. Materials and methods: Data of patients who underwent oncologic esophagectomy (July 2010–March 2019) were extracted from a Japanese nationwide inpatient database. The proportion of patients who underwent early extubation (extubation on the day of surgery) at each hospital was assessed and grouped by quartiles: very low- (<11%), low- (11–37%), medium- (38–83%), and high-proportion (≥84%) hospitals. The primary outcome was respiratory complications; secondary outcomes included reintubation, anastomotic leakage, other major complications, and hospitalization costs. Multivariable regression analyses were performed, adjusting for patient demographics, cancer treatments, and hospital characteristics. A restricted cubic spline analysis was also performed for the primary outcome. Results: Among 37 983 eligible patients across 545 hospitals, early extubation was performed in 17 931 (47%) patients. Early extubation proportions ranged from 0–100% across hospitals. Respiratory complications occurred in 10 270 patients (27%). Multivariable regression analyses showed that high- and medium-proportion hospitals were significantly associated with decreased respiratory complications [odds ratio, 0.46 (95% CI, 0.36–0.58) and 0.43 (0.31–0.60), respectively], reintubation, and hospitalization costs when compared with very low-proportion hospitals. The risk of anastomotic leakage and other major complications did not differ among groups. The restricted cubic spline analysis demonstrated a significant inverse dose-dependent association between the early extubation proportion and the risk of respiratory complications. Conclusion: A higher proportion of early extubation in a hospital was associated with a lower occurrence of respiratory complications, highlighting a potential benefit of early extubation after esophagectomy.
Global, regional, and national burden and quality of care index (QCI) of bipolar disorder: A systematic analysis of the Global Burden of Disease Study 1990 to 2019

Background: Bipolar disorders (BD) are significant debilitating mental problems. Here, we introduced a novel index as a representative of the quality of care delivered to BD patients worldwide. Methods: The Global Burden of Disease (GBD) 2019 study was the primary data source on BD, including prevalence, incidence, and years lived with disability (YLDs). Secondary indices were created and transformed into a single component that accounted for most of the variation, using the Principal Component Analysis (PCA) method. This component, reported on a scale of 0 to 100, was presented as the quality of care index (QCI). The QCI was estimated in different age groups and areas within a 30-year time frame. Gender disparity ratio (GDR), as the female-to-male ratio of the QCI, was reported. Results: The Global QCI slightly increased from 50.4 in 1990 to 53.1 in 2019. The GDR value was 0.95 in 2019. The high-middle SDI quintile had the highest QCI estimate of 63.0, and the lowest QCI value of 36.9 was regarding the low SDI quintile. Western-Pacific Region and South-East Asia had the highest and lowest QCI among WHO regions, with estimates of 70.7 and 31.2, respectively. The age group of 20 to 24 years old patients reported the lowest QCI estimate of 30.2, and the highest QCI of 59.8 was regarding 40 to 44 years old patients. Conclusion: The QCI in BD had only a subtle increase from 1990 to 2019 and is in need of further improvement. Inequalities between different regions and age groups are considerable and require proper attention.
New directions in psychiatric drug development: promising therapeutics in the pipeline

ABSTRACT Introduction Psychiatric disorders are a leading cause of disability worldwide, calling for an urgent need for new treatments, early detection, early intervention, and precision medicine. Drug discovery and development in psychiatry continues to expand in new and exciting areas, with several new medications approved for psychiatric indications by the U.S. Food and Drug Administration (FDA) in the last 5 years. Areas covered In this review, the authors summarize recent new drug approvals and new molecular mechanisms in Phase 1–3 clinical development for psychiatric disorders. Advances in human genetics-driven target identification, emergent technologies such as artificial intelligence-enabled drug discovery, digital health technologies, and biomarker tools and strategies for testing novel mechanisms are highlighted. Expert opinion There continues to be a need for research focused on understanding the natural history, developmental trajectory, and pathophysiology of psychiatric disorders to identify new molecular and circuit-based targets. Looking to the future, a vision of precision psychiatry is emerging, taking advantage of advances in genetics, digital technology, and multimodal biomarkers to accelerate the development of next-generation therapies for individuals living with mental illnesses.
Granular flow modelling of rotating drum flows using positron emission particle tracking

Tumbling mills are characterized by a flowing granular mixture comprising slurry, ore and grinding media. Akin to fluid flow, a rheological description underpinning granular flow has long been expected and pursued by many researchers. Unfortunately, no single theory has hitherto been able to successfully describe all the peculiar features and flow phases of granular systems. Tumbling mills exhibit a rich coexistence of all known flow phases and is arguably the most complicated of the granular flow geometries. Not surprisingly, current comminution models are almost entirely empirical with limited predictive capability beyond their window of design. Using Positron Emission Particle Tracking (PEPT) data we recover the key ingredients (velocity, shear rate, volume concentration, bed depth) for developing, testing and calibrating granular flow models. In this regard, 5 mm and 8 mm glass beads are rotated within a 476 mm diameter mill, fitted with angled lifter bars along the inner azimuthal walls and operated in batch mode across a range of drum rotation speeds that span cascading and cataracting Froude regimes. After averaging the PEPT outputs into representative volume elements, subsequent continuum analysis of the flowing layer revealed a rich coexistence of flow regimes −(i) quasi-static, (ii) dense (liquid-like), and (iii) inertial− that are consistent with the measured volume concentrations spanning these regimes in rotating drums. Appropriately matched constitutive choices for the shear stresses then facilitated the derivation of a new granular rheology that is able to (smoothly) capture all phases of the tumbling mill flow at transition points that match leading experimental findings reported in the literature. Limiting our models to athermal boundary conditions, we then derive the power density for better understanding of flow dissipation that ultimately drives the comminution purpose of tumbling mills. The rheology and power density models were then applied to the 5 mm and 8 mm glass bead data to reveal that shear power density is an order of magnitude larger than the normal component. Notwithstanding, the effective friction coefficient −which is akin to viscosity in typical fluids− remains relatively constant across most of the flowing layer with notable exponential growth across the interface from dense-to-inertial that continued into the inertial regime.
Imported Cholera Cases, South Africa, 2023

Since February 2022, Malawi has experienced a cholera outbreak of >54,000 cases. We investigated 6 cases in South Africa and found that isolates linked to the outbreak were Vibrio cholerae O1 serotype Ogawa from seventh pandemic El Tor sublineage AFR15, indicating a new introduction of cholera into Africa from south Asia.
Improvement of FBG de-noising with the self-optimizing method of wavelet threshold

To demodulate the central wavelength precisely is the key of FBG sensor system.How to de-noising is a challenging problem.In order to gain the drift of wavelength and achieve the measurement of ambient environment parameters precisely,nonlinear de-noising methods are investigated in this paper.Wavelet threshold de-noising is usually a method of nonlinear de-noising.The selection of threshold function and threshold value is important in wavelet threshold de-noising.Firstly,this paper analyzes the problem of choosing the threshold function and threshold in traditional soft and hard threshold de-noising,and then improves the self-optimizing threshold.Secondly,the paper proposes a method of gaining the optimal value of a(regulatory factor) in the compromising threshold function.Simulation and experiment results show that the signal-to-noise ratio(SNR) changes with a.When the value of a changes between 0.40 and 0.45,the effect of de-noising will become better.Compared with the traditional soft threshold and hard threshold methods,the SNR is increased by 2-4 dB,and the mean square root error(MSE) is reduced by 0.2-0.5. While compared with the reference improved threshold method,the SNR is improved by 1 dB and the MSE is reduced by 0.1. The overall de-noising effect is better than the others.
Dielectric metasurfaces for next-generation optical biosensing: a comparison with plasmonic sensing

In the past decades, nanophotonic biosensors have been extended from the extensively studied plasmonic platforms to dielectric metasurfaces. Instead of plasmonic resonance, dielectric metasurfaces are based on Mie resonance, and provide comparable sensitivity with superior resonance bandwidth, Q factor, and figure-of-merit. Although the plasmonic photothermal effect is beneficial in many biomedical applications, it is a fundamental limitation for biosensing. Dielectric metasurfaces solve the ohmic loss and heating problems, providing better repeatability, stability, and biocompatibility. We review the high-Q resonances based on various physical phenomena tailored by meta-atom geometric designs, and compare dielectric and plasmonic metasurfaces in refractometric, surface-enhanced, and chiral sensing for various biomedical and diagnostic applications. Departing from conventional spectral shift measurement using spectrometers, imaging-based and spectrometer-less biosensing are highlighted, including single-wavelength refractometric barcoding, surface-enhanced molecular fingerprinting, and integrated visual reporting. These unique modalities enabled by dielectric metasurfaces point to two important research directions. On the one hand, hyperspectral imaging provides massive information for smart data processing, which not only achieve better biomolecular sensing performance than conventional ensemble averaging, but also enable real-time monitoring of cellular or microbial behaviour in physiological conditions. On the other hand, a single metasurface can integrate both functions of sensing and optical output engineering, using single-wavelength or broadband light sources, which provides simple, fast, compact, and cost-effective solutions. Finally, we provide perspectives in future development on metasurface nanofabrication, functionalization, material, configuration, and integration, towards next-generation optical biosensing for ultra-sensitive, portable/wearable, lab-on-a-chip, point-of-care, multiplexed, and scalable applications.
Patients with dermatomyositis shared partially similar transcriptome signature with COVID-19 infection

Abstract Dermatomyositis (DM) is an autoimmune disease that primarily affects the skin and skeletal muscle. Virus infection and type I interferon-related signaling pathways play an important role in the pathogenesis of dermatomyositis. In this study, we found that the skin of patients with DM and the skin of patients with COVID-19 have similar transcriptional profiles, and identified key genes involved in dermatomyositis based on bioinformatics analysis. These hub-genes might be served as potential biomarkers for the early diagnosis and therapy of DM, including MX1, ISG15, IFIT3, IFIT1, RSAD2, IFIT2, IFI6, XAF1, IRF9, MX2.
The application of new metrics for understanding trends in undiagnosed HIV among key populations

Objective: Investigate the utility of novel metrics for understanding trends in undiagnosed HIV. Methods: We produced estimates for the number of people with undiagnosed HIV and the number of new HIV infections using Australian surveillance data and the European Centre for Disease Prevention and Control HIV modelling tool. Using these estimates, we calculated: the total diagnosed fraction, the proportion of all people with HIV diagnosed; the yearly diagnosed fraction, the proportion of people who have not yet received a diagnosis who received a diagnosis during each year; and the case detection rate, which is the annual ratio of new HIV diagnoses to new HIV infections each year; from 2008 to 2019. We report trends in these metrics for Australian-born and overseas-born men who reported male-to-male sex and heterosexual women and men. Results: Each metric for the Australian-born male-to-male sexual contact group improved consistently. In contrast, the metrics for the overseas-born group worsened (total diagnosed fraction: 85.0–81.9%, yearly diagnosed fraction: 23.1–17.8%, and case detection rate: 0.74–0.63). In heterosexuals, women and men had consistent increasing trends for the total diagnosed fraction and yearly diagnosed fraction but with women having consistently higher estimates. Heterosexual men had a declining case detection rate, falling to less than one in 2011, compared to an increase for women. Conclusions: The additional metrics provided important information on Australia's progress toward HIV elimination. The more dynamic changes in the undiagnosed population seen highlight diverging trends for key populations not seen in the total diagnosed fraction.
9. Moment and Least-S quares Based Approaches to Meta-analytic Inference

Section i: Introduction and Planning 1. Place of Metaanalysis among Other Methods of Research Synthesis 3 Julia Koricheva and Jessica Gurevitch 2. The Procedure of Metaanalysis in a Nutshell 14 Isabelle M. Côté and Michael D. Jennions Section ii: Initiating a Metaanalysis 3. First Steps in Beginning a Metaanalysis 27 Gavin B. Stewart, Isabelle M. Côté, Hannah R. Rothstein, and Peter S. Curtis 4. Gathering Data: Searching Literature and Selection Criteria 37 Isabelle M. Côté, Peter S. Curtis, Hannah R. Rothstein, and Gavin B. Stewart 5. Extraction and Critical Appraisal of Data 52 Peter S. Curtis, Kerrie Mengersen, Marc J. Lajeunesse, Hannah R. Rothstein, and Gavin B. Stewart 6. Effect Sizes: Conventional Choices and Calculations 61 Michael S. Rosenberg, Hannah R. Rothstein, and Jessica Gurevitch 7. Using Other Metrics of Effect Size in Metaanalysis 72 Kerrie Mengersen and Jessica Gurevitch Section iii: Essential Analytic Models and Methods 8. Statistical Models and Approaches to Inference 89 Kerrie Mengersen, Christopher H. Schmid, Michael D. Jennions, and Jessica Gurevitch 9. Moment and LeastSquares Based Approaches to Metaanalytic Inference 108 Michael S. Rosenberg
A New Way to Estimate the Confidence Interval for the Mean of the Exponential Distribution Based on Grouped Data

Based on grouped data, the asymptotic nonnality of the maximum likelihood estimate (MLE) for mean of the single-parameter exponential distribution is proved from a new point of view, and the asymptotic confidence interval is derived. Comparing the results of CHEN and MIE, a Monte carlo simulation shows that it is a little more effective.