Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential calcium channel‐mediated dopaminergic modulation in the subthalamonigral synapse

Dopamine (DA) modulates basal ganglia (BG) activity for initiation and execution of goal‐directed movements and habits. While most studies are aimed to striatal function, the cellular and molecular mechanisms underlying dopaminergic regulation in other nuclei of the BG are not well understood. Therefore, we set to analyze the dopaminergic modulation occurring in subthalamo‐nigral synapse, in both pars compacta (SNc) and pars reticulata (SNr) neurons, because these synapses are important for the integration of information previously processed in striatum and globus pallidus. In this study, electrophysiological and pharmacological evidence of dopaminergic modulation on glutamate release through calcium channels is presented. Using paired pulse ratio (PPR) measurements and selective blockers of these ionic channels, together with agonists and antagonists of DA D2‐like receptors, we found that blockade of the CaV3 family occludes the presynaptic inhibition produced by the activation of DA receptors pharmacologically profiled as D3‐type in the STh‐SNc synapses. On the contrast, the blockade of CaV2 channels, but not CaV3, occlude with the effect of the D3 agonist, PD 128907, in the STh‐SNr synapse. The functional role of this differential distribution of calcium channels that modulate the release of glutamate in the SN implies a fine adjustment of firing for both classes of neurons. Dopaminergic neurons of the SNc establish a DA tone within the SN based on the excitatory/inhibitory inputs; such tone may contribute to processing information from subthalamic nucleus and could also be involved in pathological DA depletion that drives hyperexcitation of SNr neurons.
PointNetLK: Robust & Efficient Point Cloud Registration Using PointNet

PointNet has revolutionized how we think about representing point clouds. For classification and segmentation tasks, the approach and its subsequent variants/extensions are considered state-of-the-art. To date, the successful application of PointNet to point cloud registration has remained elusive. In this paper we argue that PointNet itself can be thought of as a learnable "imaging" function. As a consequence, classical vision algorithms for image alignment can be brought to bear on the problem -- namely the Lucas & Kanade (LK) algorithm. Our central innovations stem from: (i) how to modify the LK algorithm to accommodate the PointNet imaging function, and (ii) unrolling PointNet and the LK algorithm into a single trainable recurrent deep neural network. We describe the architecture, and compare its performance against state-of-the-art in several common registration scenarios. The architecture offers some remarkable properties including: generalization across shape categories and computational efficiency -- opening up new paths of exploration for the application of deep learning to point cloud registration. Code and videos are available at https://github.com/hmgoforth/PointNetLK.
Current understanding of the role of gut dysbiosis in type 1 diabetes

Type 1 diabetes (T1D) is a chronic autoimmune disorder that results from destruction of the insulin‐producing pancreatic β‐cells. The disease mainly affects juveniles. Changes in the composition of the gut microbiota (dysbiosis) and changes in the properties of the gut barrier have been documented in T1D subjects. Because these factors affect immune system functions, they are likely to play a role in disease pathogenesis. However, their exact role is currently not fully understood and is under intensive investigation. In this article we discuss recent advancements depicting the role of intestinal dysbiosis on immunity and autoimmunity in T1D. We also discuss therapies aimed at maintaining a healthy gut barrier as prevention strategies for T1D.
Interleukin‐1β and tumor necrosis factor are essential in controlling an experimental orthopedic implant‐associated infection

Orthopedic implant‐associated infection (OIAI) is a major complication that leads to implant failure. In preclinical models of Staphylococcus aureus OIAI, osteomyelitis and septic arthritis, interleukin‐1α (IL‐1α), IL‐1β, and tumor necrosis factor (TNF) are induced, but whether they have interactive or distinctive roles in host defense are unclear. Herein, a S. aureus OIAI model was performed in mice deficient in IL‐1α, IL‐1β, or TNF. Mice deficient in IL‐1β or TNF (to a lesser extent) but not IL‐1α had increased bacterial burden at the site of the OIAI throughout the 28‐day experiment. IL‐1β and TNF had a combined and critical role in host defense as mice deficient in both IL‐1R and TNF (IL‐1R/TNF‐deficient mice) had a 40% mortality rate, which was associated with markedly increased bacterial burden at the site of the OIAI infection. Finally, IL‐1α‐ and IL‐1β‐deficient mice had impaired neutrophil recruitment whereas IL‐1β‐, TNF‐, and IL‐1R/TNF‐deficient mice all had impaired recruitment of both neutrophils and monocytes. Therefore, IL‐1β and TNF contributed to host defense against S. aureus OIAI and neutrophil recruitment was primarily mediated by IL‐1β and monocyte recruitment was mediated by both IL‐1β and TNF.
Incidence of second primary malignancy after breast cancer and related risk factors—Is breast‐conserving surgery safe? A nested case–control study

Risk of second primary malignancy (SPM) is increasing. We aimed to assess the incidence and related risk factors of SPM among breast cancer (BC) patients from this nested case–control study using the SEER database. BC patients with SPM were identified as the case group and SPM‐free patients were defined as the control group. Propensity score matching of cases with controls by the year of the first primary BC diagnosis was conducted at the ratio of 1:5, and 97,242 BC patients were enrolled from 1998 to 2013 after the matching. The incidence of SPM in BC patients stratified by age groups and cancer sites was compared to the general population using the adjusted standardized incidence ratio (SIR) and the risk factors for SPM were examined using Cox proportional hazard regressions. Our study showed BC patients had excess risk for SPM than the general population (adjusted SIR for all cancer sites = 12.94, p < 0.001) and the incidence of SPM among them decreased with age. The risk of SPM was significantly related to the following demographical and clinical variables: age (40–59 vs. 18–39, HR = 1.33; 60–79 vs. 18–39, HR = 2.39; ≥80 vs. 18–39, HR = 2.84), race (black vs. white, HR = 1.12), histological type (lobular BC vs. ductal BC, HR = 1.15), radiotherapy (HR = 1.33), marital status (married vs. single, HR = 0.88) and estrogen receptor status (positive vs. negative, HR = 0.85). Consistent results were found in subgroup analysis stratified by contralateral‐breast SPMs and nonbreast SPMs.
Association of toll‐like receptor 10 polymorphisms with pediatric pneumococcal meningitis

We aimed to investigate whether the gene polymorphisms of TLR10 were associated with risk and severity of pneumococcal meningitis (PM) and serum cytokine levels in children. Three single nucleotide polymorphisms (SNPs) of TLR10 rs4129009 (2676A > G), rs10004195 (1018T > A) and rs11466617 (40735A > G) were studied in 95 laboratory‐confirmed PM pediatric patients and 330 healthy controls by PCR‐based sequencing. Ten serum cytokines were determined by multiplex immunoassay. The frequency of variant haplotype GAG of TLR10 was significantly lower in patients than controls (11.3% vs 33.3%, p < 0.001), although frequencies of the genotypes and alleles of the three SNPs did not differ between patients and controls. Frequency of variant haplotype GAG was significantly lower in patients who had CSF protein >1000 mg/L than those who had CSF protein ≤1000 mg/L (3.50% vs 32.4%, p < 0.001). Moreover, higher frequency of the haplotype GAG was found in patients who had higher levels of inflammatory cytokines such as IFN‐γ, TNF‐α and IL‐1β. Our finding suggested that the variant haplotype GAG in TLR10 is associated with decreased risk of PM in Chinese children.
Yeast centrosome components form a noncanonical LINC complex at the nuclear envelope insertion site

Bipolar spindle formation in yeast requires insertion of centrosomes (known as spindle pole bodies [SPBs]) into fenestrated regions of the nuclear envelope (NE). Using structured illumination microscopy and bimolecular fluorescence complementation, we map protein distribution at SPB fenestrae and interrogate protein–protein interactions with high spatial resolution. We find that the Sad1-UNC-84 (SUN) protein Mps3 forms a ring-like structure around the SPB, similar to toroids seen for components of the SPB insertion network (SPIN). Mps3 and the SPIN component Mps2 (a Klarsicht-ANC-1-Syne-1 domain [KASH]–like protein) form a novel noncanonical linker of nucleoskeleton and cytoskeleton (LINC) complex that is connected in both luminal and extraluminal domains at the site of SPB insertion. The LINC complex also controls the distribution of a soluble SPIN component Bbp1. Taken together, our work shows that Mps3 is a fifth SPIN component and suggests both direct and indirect roles for the LINC complex in NE remodeling.
Reply to Effectiveness of radical prostatectomy with adjuvant radiotherapy versus radiotherapy plus androgen deprivation therapy for men with advanced prostate cancer: Do we have certainties today?

The optional initial treatments and their best combination for men affected by locally advanced prostate cancer are widely debated. In a newly published retrospective study, Jang et al had compared the survival outcomes and associated adverse effects for a large cohort of patients affected by local or regional advanced prostate cancer who underwent radical prostatectomy followed by radiotherapy (XRT) or XRT plus androgen deprivation therapy (ADT) from 1992 to 2009, and they had showed a significantly lower risk of prostate cancer–specific death and improved overall survival in the first group of patients in comparison with those men treated with XRT plus ADT. I emphasize that the retrospective nature of the study, despite statistical adjustments, may have led to an important population selection bias. We should consider that some of the patients with locally or regionally advanced disease who underwent XRT plus ADT could have been treated for purely palliative purposes, unlike those undergoing radical prostatectomy followed by adjuvant XRT, with doses and volumes of XRT adequate for providing symptomatic relief but not for prolonging survival. Even for the patients who underwent XRT plus ADT with radical intent, we must keep in mind that XRT in the period ranging from 1992 to 2009 was different from current XRT: most of the patients treated from 1992 to 2009 were probably subjected to 3-dimensional conformal XRT. Today, because of the evolution of skills and technologies, the mainly adopted radiation treatment in this patient setting is intensity-modulated or volumetric arc therapy, which are associated with image-guided targeting. These new techniques lead to better target tracking and dose escalation in radical-intent XRT. It would also be interesting to know what percentages of patients in the 2 groups were considered eligible for a second line of therapy (eg, systemic chemotherapy) in light of advanced age and comorbidity and were subjected to the same. This could have affected survival. Prospective randomized studies are mandatory for men affected by locally advanced prostate cancer so that the best combination of primary treatments can be defined.
An automated, machine learning–based detection algorithm for spike‐wave discharges (SWDs) in a mouse model of absence epilepsy

Objective Manual detection of spike-wave discharges (SWDs) from EEG records is time intensive, costly, and subject to inconsistencies/biases. Additionally, manual scoring often omits information on SWD confidence/intensity which may be important for the investigation of mechanistic-based research questions. Our objective is to develop an automated method for the detection of SWDs in a mouse model of absence epilepsy that is focused on the characteristics of human scoring of pre-selected events to establish a confidence-based, continuous-valued scoring. Methods We develop a support vector machine (SVM)-based algorithm for the automated detection of SWDs in the γ2R43Q mouse model of absence epilepsy. The algorithm first identifies putative SWD events using frequency- and amplitude-based peak detection. Four humans scored a set of 2500 putative events identified by the algorithm. Then, using predictors calculated from the wavelet transform of each event and the labels from human scoring, we trained a SVM to classify (SWD/nonSWD) and assign confidence scores to each event identified from 60 24-hour EEG records. We provide a detailed assessment of intra- and inter-rater scoring that demonstrates advantages of automated scoring. Results The algorithm scored SWDs along a continuum that is highly correlated with human confidence and that allows us to more effectively characterize ambiguous events. We demonstrate that events along our scoring continuum are temporally and proportionately correlated with abrupt changes in spectral power bands relevant to normal behavioral states including sleep. Significance While there are automated and semi-automated methods for the detection of SWDs in humans and rats, we contribute to the need for continued development of SWD detection in mice. Our results demonstrate the value of viewing detection of SWDs as a continuous classification problem to better understand ‘ground truth’ in SWD detection (i.e., the most reliable features agreed upon by humans that also correlate with objective physiological measures). Key Point Box Clinicians and researchers may benefit from an automated method of SWD detection that provides a framework for the quantitative description of SWDs and how they relate to other electrographic events. We present an algorithm for the automated, consistent, and rapid scoring of SWDs that assigns a confidence to detected events that is highly correlated with human scoring confidence. We characterize the human inter- and intra-rater consistency in the scoring of potential SWD events and compare them with the algorithm. Events along the scoring continuum generated by the algorithm are temporally and proportionately correlated with changes in spectral power bands relevant to behavioral states including sleep.
When one phenotype is not enough: divergent evolutionary trajectories govern venom variation in a widespread rattlesnake species

Understanding the origin and maintenance of phenotypic variation, particularly across a continuous spatial distribution, represents a key challenge in evolutionary biology. For this, animal venoms represent ideal study systems: they are complex, variable, yet easily quantifiable molecular phenotypes with a clear function. Rattlesnakes display tremendous variation in their venom composition, mostly through strongly dichotomous venom strategies, which may even coexist within a single species. Here, through dense, widespread population-level sampling of the Mojave rattlesnake, Crotalus scutulatus, we show that genomic structural variation at multiple loci underlies extreme geographical variation in venom composition, which is maintained despite extensive gene flow. Unexpectedly, neither diet composition nor neutral population structure explain venom variation. Instead, venom divergence is strongly correlated with environmental conditions. Individual toxin genes correlate with distinct environmental factors, suggesting that different selective pressures can act on individual loci independently of their co-expression patterns or genomic proximity. Our results challenge common assumptions about diet composition as the key selective driver of snake venom evolution and emphasize how the interplay between genomic architecture and local-scale spatial heterogeneity in selective pressures may facilitate the retention of adaptive functional polymorphisms across a continuous space.
Urban Egyptian Women Aged 19–30 Years Display Nutrition Transition-Like Dietary Patterns, with High Energy and Sodium Intakes, and Insufficient Iron, Vitamin D, and Folate Intakes

ABSTRACT Background Recent changes in Egyptian dietary habits can be attributed to more urban and sedentary lifestyles and to alterations in the dietary and economic context. The mean BMI of Egyptian women is one of the highest worldwide, and 50% have iron deficiency. Objective The aim was to quantify food and nutrient intakes of urban Egyptian women and conduct a detailed analysis of micronutrients commonly consumed in inadequate amounts, such as iron, vitamin D, and folate. Methods Urban Egyptian women aged 19–30 y (n = 130) were recruited during 2016–2017. Energy needs were estimated using the Henry equation, assuming a low physical activity level (1.4). Dietary intakes and iron bioavailability were estimated from a 4-d food diary. Macronutrient intakes were compared with WHO/FAO population goals and micronutrient intakes with Egyptian recommendations. Iron needs were determined for each subject. Results The mean BMI (kg/m2) was 27.9 ± 4.9. The mean total energy intake (TEI; 2389 ± 715 kcal/d) was significantly higher than needs (2135 ± 237 kcal/d; P = 0.00018). Total fat (33%TEI) and SFA (11%TEI) intakes were slightly higher than population goals (15–30%TEI and <10%TEI, respectively). Diets provided 18 ± 8 g/d of fiber, 98 ± 54 g/d of total sugars, and nearly twice the recommended sodium intake (intake: 2787 ± 1065 mg/d; recommendation: <1500 mg/d). Estimated dietary iron bioavailability was low (9.2% ± 1.6%), and 79% of women consumed less iron than the average requirement (17.5 ± 7 mg/d). Overall, 82% and 80% of women consumed less vitamin D and folate, respectively, than recommended. Conclusions Egyptian women aged 19–30 y have high intakes of energy and sodium, whereas iron, vitamin D, and folate intakes are insufficient, with only low concentrations of bioavailable iron. These results call for further investigation into measures that would improve this population's diet quality.
Automatic Speaker Recognition with Limited Data

Automatic speaker recognition (ASR) is a stepping-stone technology towards semantic multimedia understanding and benefits versatile downstream applications. In recent years, neural network-based ASR methods have demonstrated remarkable power to achieve excellent recognition performance with sufficient training data. However, it is impractical to collect sufficient training data for every user, especially for fresh users. Therefore, a large portion of users usually has a very limited number of training instances. As a consequence, the lack of training data prevents ASR systems from accurately learning users acoustic biometrics, jeopardizes the downstream applications, and eventually impairs user experience. In this work, we propose an adversarial few-shot learning-based speaker identification framework (AFEASI) to develop robust speaker identification models with only a limited number of training instances. We first employ metric learning-based few-shot learning to learn speaker acoustic representations, where the limited instances are comprehensively utilized to improve the identification performance. In addition, adversarial learning is applied to further enhance the generalization and robustness for speaker identification with adversarial examples. Experiments conducted on a publicly available large-scale dataset demonstrate that \model significantly outperforms eleven baseline methods. An in-depth analysis further indicates both effectiveness and robustness of the proposed method.
Tumour‐specific and organ‐specific protein synthesis rates in patients with pancreatic cancer

Living tissues maintain a fine balance between protein synthesis and protein breakdown rates. Animal studies indicate that protein synthesis rates are higher in organs when compared with skeletal muscle tissue. As such, organ and tumour protein synthesis could have major effects on whole‐body protein metabolism in wasting disorders such as cancer cachexia. We aimed to assess protein synthesis rates in pancreatic tumour tissue and healthy pancreas, liver, and skeletal muscle tissue in vivo in humans.
Dasatinib can enhance paclitaxel and gemcitabine inhibitory activity in human pancreatic cancer cells

ABSTRACT SRC and its activated form, phospho-SRC (pSRC), are aberrantly activated in pancreatic cancer and SRC represents a potential target for pancreatic cancer therapy. In this paper, we examined the inhibitory effect of dasatinib, a potent SRC inhibitor in combination with paclitaxel or gemcitabine on human and murine pancreatic cancer cell lines. The results showed that p-SRC can be highly expressed in most human and mouse pancreatic cancer cell lines compared with normal human cell lines and can be induced by paclitaxel or gemcitabine in HPAC cells. Dasatinib can enhance the efficacy of paclitaxel or gemcitabine by reducing the cell viability and inhibiting the cell proliferation. Dasatinib with paclitaxel combination exhibits statistically greater inhibition of the cell migration ability than single agent alone, paclitaxel with gemcitabine or FOLFIRINOX (combination of fluorouracil, leucovorin, irinotecan, and oxaliplatin) in HAPC, PANC-1, and BXPC-3 human pancreatic cancer cell lines as well as 8–285 APR and 8–365 APR mouse pancreatic cancer cell lines. In addition, dasatinib with gemcitabine combination also showed statistically greater inhibition of cell migration than single agent alone, paclitaxel with gemcitabine, or FOLFIRINOX in HAPC, PANC-1 and 8–285 APR cells. The combination of dasatinib with paclitaxel or gemcitabine also showed greater inhibition of the colony formation ability of pancreatic cancer cells compared with single-agent monotherapy or FOLFIRINOX. Dasatinib with paclitaxel or gemcitabine combination also inhibits p-SRC, p-STAT3, p-AKT, and/or p-ERK in these pancreatic cancer cells. Therefore, our results support that combined dasatinib and paclitaxel or gemcitabine therapy may be a viable therapeutic approach for human pancreatic cancer.
Increase of arginine dimethylation correlates with the progression and prognosis of ALS

Objective To investigate whether arginine methylation is altered in patients with amyotrophic lateral sclerosis (ALS) and how it affects disease severity, progression, and prognosis. Methods We compared the immunoreactivity of protein arginine methyltransferase 1 (PRMT1) and its products, asymmetric dimethylated proteins (ASYM), in postmortem spinal cord. We also measured the concentrations of total l-arginine and methylated arginine residues, including asymmetric dimethyl l-arginine (ADMA), symmetric dimethyl arginine, and monomethyl arginine, in CSF samples from 52 patients with ALS using liquid chromatography-tandem mass spectrometry, and we examined their relationship with the progression and prognosis of ALS. Results The immunoreactivity of both PRMT1 (p < 0.0001) and ASYM (p = 0.005) was increased in patients with ALS. The concentration of ADMA in CSF was substantially higher in patients with ALS than in disease controls. The ADMA/l-arginine ratio was correlated with the change of decline in the ALS Functional Rating Scale at 12 months after the time of measurement (r = 0.406, p = 0.010). A Cox proportional hazards model showed that the ADMA/l-arginine ratio was an independent predictor for overall survival. Moreover, a high ADMA/l-arginine ratio predicted poor prognosis, even in a group with normal percentage forced vital capacity. Conclusion There was an enhancement of arginine dimethylation in patients with ALS, and the ADMA/l-arginine ratio predicted disease progression and prognosis in such patients.