Miracle-dz/UniFAR-FTUs huggingface dataset:
Ring-arrayed forward-viewing ultrasound imaging system: a feasibility study

Current standard workflows of ultrasound (US)-guided needle insertion require physicians to use their both hands: holding the US probe to locate interested areas with the non-dominant hand and the needle with the dominant hand. This is due to the separation of functionalities for localization and needle insertion. This requirement does not only make the procedure cumbersome, but also limits the reliability of guidance given that the positional relationship between the needle and US images is interpreted with their experience and assumption. Although the US-guided needle insertion may be assisted through navigation systems, the recovery of the positional relationship between the needle and US images requires the usage of external tracking systems and image-based tracking algorisms that may involve the registration inaccuracy. Therefore, there is an unmet need for the solution that provides a simple and intuitive needle localization and insertion to improve the conventional US-guided procedure. In this work, we propose a new device concept based on the ring-arrayed forward-viewing (RAF) ultrasound imaging system. The proposed system is comprised with ring-arrayed transducers and an open whole inside the ring where the needle can be inserted. The ring array provides forward-viewing US images, where the needle can be visualized at the center of the reconstructed image without any registration. As the proof of concept, we designed several ring-arrayed configurations and visualized point targets using the forward-viewing US imaging through simulations and phantom experiments. The results demonstrated the successful target visualization and indicates the ring-arrayed US imaging has a potential to improve the US-guided needle insertion procedure to be simpler and more intuitive.
Modified Doo-Sabin modeling of the right ventricle

Accurate modelling of the right ventricle of the human heart is important for both diagnosis and treatment planning. The right ventricle (RV) has a compound convex-concave shape with several sharp edges. While the RV has previously been modeled using the Doo-Sabin method, these models require several extra control nodes to accurately reproduce the relatively sharp edges. The current paper proposes a modified Doo-Sabin method which introduces weighting of vertices and edges rather than extra nodes to control sharpness. This work compares standard vs sharp Doo-Sabin models on modeling the RV from 16 3D ultrasound scans, compared to a ground truth mesh model manually drawn by a cardiologist. The modified, sharp Doo-Sabin method came closer to the ground truth RV model in 11 out of 16 cases and on average showed an 11.54 % improvement.
Guided ultrasound imaging using a deep regression network

In this work, we present a machine learning method to guide an ultrasound operator towards a selected area of interest. Unlike other automatic medical imaging methods, ultrasound imaging is one of the few imaging modalities where the operator’s skill and training are critical in obtaining high quality images. Additionally, due to recent advances in affordability and portability of ultrasound technology, its utilization by non-experts has increased. Thus, there is a growing need for intelligent systems that have the ability to assist ultrasound operators in both clinical and non-clinical scenarios. We propose a system that leverages machine learning to map real time ultrasound scans to transformation vectors that can guide a user to a target organ or anatomical structure. We present a unique training system that passively collects supervised training data from an expert sonographer and uses this data to train a deep regression network. Our results show that we are able to recognize anatomical structure through the use of ultrasound imaging and give the user guidance toward obtaining an ideal image.
Impact of Irrigation Strategies on Tomato Root Distribution and Rhizosphere Processes in an Organic System

Root exploitation of soil heterogeneity and microbially mediated rhizosphere nutrient transformations play critical roles in plant resource uptake. However, how these processes change under water-saving irrigation technologies remains unclear, especially for organic systems where crops rely on soil ecological processes for plant nutrition and productivity. We conducted a field experiment and examined how water-saving subsurface drip irrigation (SDI) and concentrated organic fertilizer application altered root traits and rhizosphere processes compared to traditional furrow irrigation (FI) in an organic tomato system. We measured root distribution and morphology, the activities of C-, N-, and P-cycling enzymes in the rhizosphere, the abundance of rhizosphere microbial N-cycling genes, and root mycorrhizal colonization rate under two irrigation strategies. Tomato plants produced shorter and finer root systems with higher densities of roots around the drip line, lower activities of soil C-degrading enzymes, and shifts in the abundance of microbial N-cycling genes and mycorrhizal colonization rates in the rhizosphere of SDI plants compared to FI. SDI led to 66.4% higher irrigation water productivity than FI, but it also led to excessive vegetative growth and 28.3% lower tomato yield than FI. Our results suggest that roots and root-microbe interactions have a high potential for coordinated adaptation to water and nutrient spatial patterns to facilitate resource uptake under SDI. However, mismatches between plant needs and resource availability remain, highlighting the importance of assessing temporal dynamics of root–soil–microbe interactions to maximize their resource-mining potential for innovative irrigation systems.
Predicting Long-Term After-Effects of Theta-Burst Stimulation on Supplementary Motor Network Through One-Session Response

To understand the neural mechanism of repetitive transcranial magnetic stimulation (rTMS), the after-effects following one session or multiple days of stimulation have been widely investigated. However, the relation between the short-term effect (STE) and long-term effect (LTE) of rTMS is largely unknown. This study aims to explore whether the after-effects of 5-day rTMS on supplementary motor area (SMA) network could be predicted by one-session response. A primary cohort of 38 healthy participants underwent five daily sessions of real or sham continuous theta-burst stimulation (cTBS) on the left SMA. Resting-state functional magnetic resonance imaging (fMRI) data were acquired at the first (before and after the first stimulation) and sixth experimental day. The SMA connectivity changes after the first cTBS and after 5 days of stimulation were defined as STE and LTE, respectively. Compared to the baseline, significant STE and LTE were found in the bilateral paracentral gyrus (ParaCG) after real stimulation, suggesting shared neural correlates of short- and long-term stimulations. Region-of-interest analysis indicated that the resting-state functional connectivity between SMA and ParaCG increased after real stimulation, while no significant change was found after sham stimulation. Leave-one-out cross-validation indicated that the LTE in ParaCG could be predicted by the STE after real but not sham stimulations. In an independent cohort, the after-effects of rTMS on ParaCG and short- to long-term prediction were reproduced at the region-of-interest level. These imaging evidences indicate that one-session rTMS can aid to predict the regions responsive to long-term stimulation and the individualized response degree.
2-Hydroxy-Docosahexaenoic Acid Is Converted Into Heneicosapentaenoic Acid via α-Oxidation: Implications for Alzheimer’s Disease Therapy

Alzheimer’s disease (AD) is a neurodegenerative disease with as yet no efficient therapies, the pathophysiology of which is still largely unclear. Many drugs and therapies have been designed and developed in the past decade to stop or slow down this neurodegenerative process, although none has successfully terminated a phase-III clinical trial in humans. Most therapies have been inspired by the amyloid cascade hypothesis, which has more recently come under question due to the almost complete failure of clinical trials of anti-amyloid/tau therapies to date. To shift the perspective for the design of new AD therapies, membrane lipid therapy has been tested, which assumes that brain lipid alterations lie upstream in the pathophysiology of AD. A hydroxylated derivative of docosahexaenoic acid was used, 2-hydroxy-docosahexaenoic acid (DHA-H), which has been tested in a number of animal models and has shown efficacy against hallmarks of AD pathology. Here, for the first time, DHA-H is shown to undergo α-oxidation to generate the heneicosapentaenoic acid (HPA, C21:5, n-3) metabolite, an odd-chain omega-3 polyunsaturated fatty acid that accumulates in cell cultures, mouse blood plasma and brain tissue upon DHA-H treatment, reaching higher concentrations than those of DHA-H itself. Interestingly, DHA-H does not share metabolic routes with its natural analog DHA (C22:6, n-3) but rather, DHA-H and DHA accumulate distinctly, both having different effects on cell fatty acid composition. This is partly explained because DHA-H α-hydroxyl group provokes steric hindrance on fatty acid carbon 1, which in turn leads to diminished incorporation into cell lipids and accumulation as free fatty acid in cell membranes. Finally, DHA-H administration to mice elevated the brain HPA levels, which was directly and positively correlated with cognitive spatial scores in AD mice, apparently in the absence of DHA-H and without any significant change in brain DHA levels. Thus, the evidence presented in this work suggest that the metabolic conversion of DHA-H into HPA could represent a key event in the therapeutic effects of DHA-H against AD.
High Temporal Variability of Total Organic Carbon in the Deep Northeastern Pacific

The interseasonal and interannual variability of total organic carbon (TOC) was assessed in the deep northeastern Pacific Ocean, an area characterized by high primary production and organic matter export. Samples were collected from throughout the deeper water column (>250 m) seasonally in 2017 and 2018 along the Line P transect, as well as one distribution of dissolved organic carbon (DOC) in spring 2018. High heterogeneity was observed in TOC concentrations at depths greater than 1,000 m, both within seasons (concentration differences of ∼2–6 μmol kg–1) and across seasons (∼2–12 μmol kg–1), coinciding with changes in fluorescence in the overlying waters. Such observations suggest that biogenic particles sinking from the upper ocean are seasonally delivering observable TOC to depth. The presence of these particles also appeared to contribute to the DOC pool, as suggested by differences in the TOC and DOC distributions in spring 2018. Seasonal TOC net accumulation and removal rates differed between the years: 0.5 and 2.1 μmol kg–1 day–1 (accumulation) and 0.6 and 2.1 μmol kg–1 day–1 (removal) for 2017 and 2018, respectively. The rate estimates indicated that introduction of organic carbon to the bathypelagic occurred at approximately the same rate as removal post-bloom, demonstrating the efficient removal of seasonally produced organic carbon. High abundances of gelatinous zooplankton in spring 2018, supported by higher abundances of phytoplankton, enhanced the export of organic carbon to the bathypelagic zone during the seasonal bloom, resulting in localized TOC concentrations up to 148 μmol kg–1 in the bathypelagic. These results indicate high variability in bathypelagic TOC concentrations at high latitude, unlike oligotrophic systems.
Esculetin Inhibits Cancer Cell Glycolysis by Binding Tumor PGK2, GPD2, and GPI

Glycolysis can improve the tolerance of tissue cells to hypoxia, and its intermediates provide raw materials for the synthesis and metabolism of the tumor cells. If it can inhibit the activity of glycolysis-related enzymes and control the energy metabolism of tumor, it can be targeted for the treatment of malignant tumor. The target proteins phosphoglycerate kinase 2 (PGK2), glycerol-3-phosphate dehydrogenase (GPD2), and glucose-6-phosphate isomerase (GPI) were screened by combining transcriptome, proteomics, and reverse docking. We detected the binding constant of the active compound using microscale thermophoresis (MST). It was found that esculetin bound well with three potential target proteins. Esculetin significantly inhibited the rate of glycolysis, manifested by differences of cellular lactate production and glucose consumption in HepG2 cells with or without esculetin. It was found that GPD2 bound strongly to GPI, revealing the direct interaction between the two glycolysis-related proteins. Animal tests have further demonstrated that esculetin may have anticancer effects by affecting the activity of PGK2, GPD2, and GPI. The results of this study demonstrated that esculetin can affect the glucose metabolism by binding to glycolytic proteins, thus playing an anti-tumor role, and these proteins which have direct interactions are potential novel targets for tumor treatment by esculetin.
Pathological Aspects of Neuronal Hyperploidization in Alzheimer’s Disease Evidenced by Computer Simulation

When subjected to stress, terminally differentiated neurons are susceptible to reactivate the cell cycle and become hyperploid. This process is well documented in Alzheimer’s disease (AD), where it may participate in the etiology of the disease. However, despite its potential importance, the effects of neuronal hyperploidy (NH) on brain function and its relationship with AD remains obscure. An important step forward in our understanding of the pathological effect of NH has been the development of transgenic mice with neuronal expression of oncogenes as model systems of AD. The analysis of these mice has demonstrated that forced cell cycle reentry in neurons results in most hallmarks of AD, including neurofibrillary tangles, Aβ peptide deposits, gliosis, cognitive loss, and neuronal death. Nevertheless, in contrast to the pathological situation, where a relatively small proportion of neurons become hyperploid, neuronal cell cycle reentry in these mice is generalized. We have recently developed an in vitro system in which cell cycle is induced in a reduced proportion of differentiated neurons, mimicking the in vivo situation. This manipulation reveals that NH correlates with synaptic dysfunction and morphological changes in the affected neurons, and that membrane depolarization facilitates the survival of hyperploid neurons. This suggests that the integration of synaptically silent, hyperploid neurons in electrically active neural networks allows their survival while perturbing the normal functioning of the network itself, a hypothesis that we have tested in silico. In this perspective, we will discuss on these aspects trying to convince the reader that NH represents a relevant process in AD.
Quantitative Identification of Major Depression Based on Resting-State Dynamic Functional Connectivity: A Machine Learning Approach

Introduction Developing a machine learning-based approach which could provide quantitative identification of major depressive disorder (MDD) is essential for the diagnosis and intervention of this disorder. However, the performances of traditional algorithms using static functional connectivity (SFC) measures were unsatisfactory. In the present work, we exploit the hidden information embedded in dynamic functional connectivity (DFC) and developed an accurate and objective image-based diagnosis system for MDD. Methods MRI images were collected from 99 participants including 56 healthy controls and 43 MDD patients. DFC was calculated using a sliding-window algorithm. A non-linear support vector machine (SVM) approach was then used with the DFC matrices as features to distinguish MDD patients from healthy controls. The spatiotemporal characteristics of the most discriminative features were then investigated. Results The area under the curve (AUC) of the SVM classifier with DFC measures reached 0.9913, while this value is only 0.8685 for the algorithm using SFC measures. Spatially, the most discriminative 28 connections distributed in the visual network (VN), somatomotor network (SMN), dorsal attention network (DAN), ventral attention network (VAN), limbic network (LN), frontoparietal network (FPN), and default mode network (DMN), etc. Notably, a large portion of these connections were associated with the FPN, DMN, and VN. Temporally, the most discriminative connections transited from the cortex to deeper regions. Conclusion The results clearly suggested that DFC is superior to SFC and provide a reliable quantitative identification method for MDD. Our findings may furnish a better understanding of the neural mechanisms of MDD as well as improve accurate diagnosis and early intervention of this disorder.
Molecular Epidemiology and Antimicrobial Resistance of Haemophilus influenzae in Adult Patients in Shanghai, China

Background: The serotype and antimicrobial resistance of Haemophilus influenzae in adult patients have changed due to the application of antimicrobials and H. influenzae type b (Hib) vaccine worldwide. However, the epidemiologic characteristics of H. influenzae in Shanghai are still unavailable. Objective: To determine the serotype distribution, antimicrobial resistance and multilocus sequence type (MLST) of H. influenzae in adult patients in Shanghai. Methods: A total of 51 clinical isolates from adult patients were consecutively collected. Serotypes were determined according to specific capsule gene, bexA, amplified by PCR. Antimicrobial susceptibility test was carried out by the broth microdilution method. β-lactamase production was detected by cefinase disk and the ftsI gene were amplified and sequenced to determine the penicillin binding protein 3 (PBP3) mutation. Molecular epidemiology was performed by MLST analyses. Results: All isolates studied were nontypeable H. influenzae (NTHi) and three of them (5.88%) caused invasive infection. The resistant rates of ampicillin and trimethoprim/sulfamethoxazole were both 45.10%. One third of these isolates produced TEM-1 type β-lactamase and 11.76% were β-lactamase negative ampicillin resistant strains (BLNAR). The PBP3 mutation was detected in 74.51% of the isolates, of which 12 belonged to group III. A total of 36 sequence types (STs) were identified among all isolates. Four isolates of ST103 (7.84%) all produced β-lactamase without mutation of PBP3. Conclusion: H. influenzae infections among adults in Shanghai are predominately caused by NTHi with genetic diversity among adult patients. The prevalence of both β-lactamase production and PBP3 mutation may contribute to high ampicillin resistance rate in Shanghai.
A Comparison of Co-expression Networks in Silk Gland Reveals the Causes of Silk Yield Increase During Silkworm Domestication

Long-term domestication and selective breeding have increased the silk yield of the domestic silkworm (Bombyx mori) by several times the amount of the silk yield of its wild ancestor (Bombyx mandarina). However, little is known about the molecular mechanisms behind the increase in silk yield during domestication. Based on dynamic patterns of functional divergence in the silk gland between domestic and wild silkworms, we found that at early and intermediate stages of silk gland development, the up-regulated genes of the domestic silkworm were mainly involved in DNA integration, nucleic acid binding, and transporter activity, which are related to the division and growth of cells. This has led to the posterior silk gland (PSG) of the domestic silkworm having significantly more cells (“factories” of fibroin protein synthesis) than that of the wild silkworm. At the late stage of silk gland development, the up-regulated genes in the domestic silkworm was enriched in protein processing and ribosome pathways, suggesting protein synthesis efficiency is greatly improved during silkworm domestication. While there was an increase in fibroin protein synthesis, the production of sericin protein was simultaneously reduced in the silk gland of the domestic silkworm. This reflects that domestic and wild silkworms have been under different selection pressures. Importantly, we found that the network co-expressed with the silk-coding genes of the domestic silkworm was larger than that of the wild silkworm. Furthermore, many more genes co-expressed with silk-coding genes in the domestic silkworm were subjected to artificial selection than those in the wild silkworm. Our results revealed that the increase of silk yield during silkworm domestication is involved in improvement of a biological system which includes not only expansion of “factories” (cells of PSG) of protein synthesis, but also a high expression of silk-coding genes and silk production-related genes such as biological energy, transport, and ribosome pathway genes.
The Natural Growth of Subsolid Nodules Predicted by Quantitative Initial CT Features: A Systematic Review

Background: The detection rate for pulmonary nodules, particularly subsolid nodules (SSNs), has been significantly improved. The purpose of this review is to summarize the relationship between quantitative features of initial CT imaging and the subsequent natural growth of SSNs to explore potential reasons for these findings. Methods: Relevant studies were collected from a literature search of PubMed, Embase, Web of Science, and Cochrane. Data extraction was performed on the patients' basic information, CT methods, and acquisition methods, including quantitative CT features, and statistical methods. Results: A total of 10 relevant articles were included in our review, which included 850 patients with 1,026 SSNs. Overall, the results were variable, and the key findings were as follows. Seven studies looked at the relationship between the diameter and growth of SSNs, showing that SSNs with larger diameters were associated with increased growth. An additional three studies which focused on the relationship between CT attenuation and the growth of SSNs showed that SSNs with a high CT attenuation were associated with increased growth. Conclusion: CT attenuation may be useful in predicting the natural growth of SSNs, and mean CT attenuation may be more useful in predicting the natural growth of pure ground glass nodules (GGNs) than part-solid GGNs. While evaluation by diameter did have some limitations, it demonstrates value in predicting the growth of SSNs.