Miracle-dz/UniFAR-FTUs huggingface dataset:
Combined everolimus and endocrine therapy in advanced HR-positive, HER2-negative Chinese breast cancer patients: a retrospective study

Background Everolimus (EVE) is an inhibitor of the mammalian target of rapamycin (mTOR) pathway, and it is approved for the treatment of advanced breast cancer (ABC). However, there is still little real-world data on using EVE in Chinese breast cancer patients. We retrospectively analyzed real-world data to determine the factors affecting EVE treatment efficacy and patient outcomes. Methods We retrospectively collected the treatment information of ABC patients treated with EVE from 2013 to 2020 in Zhejiang Cancer Hospital. Kaplan-Meier analysis and Cox regression methods were used to calculate and compare the progression-free survival (PFS), and identify the factors associated with EVE treatment efficacy. Results The study finally enrolled 84 patients meeting the requirement; the median PFS in all 84 patients was 6.87 months. Multivariate analysis showed that liver metastasis [hazard ratio, 1.69; 95% confidence interval (CI), 1.00–2.84; P=0.049], and brain metastasis (hazard ratio, 2.65; 95% CI, 1.07–6.58; P=0.036) were independent risk factors. Subgroup analyses demonstrated EVE + fulvestrant (FUL) was not superior to EVE + aromatase inhibitors (AIs) for PFS (5.77 vs. 7.97 months, P=0.0735). Furthermore, it showed EVE + AI was superior to EVE + FUL in some subgroups: postmenopausal group (hazard ratio, 0.50; 95% CI, 0.26–0.98); without bone metastasis group (hazard ratio, 0.22; 95% CI, 0.06–0.80); visceral disease group (hazard ratio, 0.37; 95% CI, 0.20–0.69). Conclusions EVE combined with endocrine therapy is an effective treatment option for Chinese patients with hormone-receptor-positive (HR+), human epidermal growth factor receptor-2-negative (HER2−) breast cancer, although EVE + FUL was not superior to EVE + AI. Liver metastasis and brain metastasis were independent risk factors for successful EVE + endocrine therapy.
Conventional measures of intrinsic excitability are poor estimators of neuronal activity under realistic synaptic inputs

Activity-dependent regulation of intrinsic excitability has been shown to greatly contribute to the overall plasticity of neuronal circuits. Such neuroadaptations are commonly investigated in patch clamp experiments using current step stimulation and the resulting input-output functions are analyzed to quantify alterations in intrinsic excitability. However, it is rarely addressed, how such changes translate to the function of neurons when they operate under natural synaptic inputs. Still, it is reasonable to expect that a strong correlation and near proportional relationship exist between static firing responses and those evoked by synaptic drive. We challenge this view by performing a high-yield electrophysiological analysis of cultured mouse hippocampal neurons using both standard protocols and simulated synaptic inputs via dynamic clamp. We find that under these conditions the neurons exhibit vastly different firing responses with surprisingly weak correlation between static and dynamic firing intensities. These contrasting responses are regulated by two intrinsic K-currents mediated by Kv1 and Kir channels, respectively. Pharmacological manipulation of the K-currents produces differential regulation of the firing output of neurons. Static firing responses are greatly increased in stuttering type neurons under blocking their Kv1 channels, while the synaptic responses of the same neurons are less affected. Pharmacological blocking of Kir-channels in delayed firing type neurons, on the other hand, exhibit the opposite effects. Our subsequent computational model simulations confirm the findings in the electrophysiological experiments and also show that adaptive changes in the kinetic properties of such currents can even produce paradoxical regulation of the firing output.
Effects of N-Methyl-D-aspartate receptor (NMDAR) and Ca2+/calmodulin-dependent protein kinase IIα (CaMKIIα) on learning and memory impairment in depressed rats with different charge by modified electroconvulsive shock

Background With the development of modified electroshock therapy (MECT), it has become necessary to increase the electric quantity in order to achieve a good antidepressant effect, but this increase will lead to more serious learning and memory impairment. The purpose of this study was to investigate the intrinsic mechanism of cognitive impairment induced by high-energy electroconvulsive shock (MECS, an animal model of MECT). Methods Rats were randomly divided into 6 groups: control (C, n=6), M0, M60, M120, M180, and M240 groups (MECS at 0, 60, 120, 180, and 240 mC stimulation intensity after 80 mg/kg propofol, with 12 rats in each group). Their depression-like behavior and learning and memory ability were evaluated by sucrose preference test (SPT), open field test (OFT), and Morris water maze test (MWM). The expression of phospho-NMDA receptor 1 (GluN1), GluN2A, GluN2B, Ca2+/calmodulin-dependent protein kinase IIα (CaMKIIα), p-T305-CaMKII, and postsynaptic densities-95 (PSD-95) in hippocampus were detected by western blot. The co-expression of CaMKIIα and GluN2B subunit was detected by co-immunoprecipitation (CO-IP). Results The chronic unpredictable mild stresses (CUMS) procedure successfully induced depression-like behavior in rats, which was improved in varying degrees after MECS. The results showed that the expression of GluN1, GluN2A, GluN2B, and PSD-95 decreased with the increase of charge, while p-T305-CaMKII increased, which led to the deterioration of learning and memory ability, but the expression change of CaMKIIα was not statistically significant. Conclusions Increase in the MECS charge adjusts the synaptic plasticity by changing the binding amount of CaMKIIα and its subunit GluN2B and the level of CaMKII autophosphorylation, thereby impairing learning and memory functions.
Metabolic syndrome and hidradenitis suppurativa: epidemiological, molecular, and therapeutic aspects

Hidradenitis suppurativa (HS) is a chronic, suppurative condition of the pilosebaceous unit. Patients suffering from HS demonstrate a molecular profile in keeping with a state of systemic inflammation and are often found to fit the criteria for a diagnosis of metabolic syndrome (MetS). In this paper, we review the literature with regards to established data on the prevalence of MetS in HS patients and revise the odds ratio of comorbid disease. Furthermore, we attempt to draw parallels between inflammatory pathways in HS and MetS and evaluate how convergences may explain the risk of comorbid disease, necessitating the need for multidisciplinary care.
Misidentification of meticillin-resistant Staphylococcus aureus by the Cepheid Xpert MRSA NxG assay, the Netherlands, February to March 2021

We describe two false-negative results in the detection of meticillin-resistant Staphylococcus aureus (MRSA) of sequence type 398 and spa type t011 using the Cepheid Xpert MRSA NxG assay. The isolates were recovered in late February and early March 2021 from two patients in different hospitals in the northern Netherlands. Variations between the two isolate genomes indicate that this MRSA strain might have been spreading for some time and could have disseminated to other regions of the Netherlands and other European countries.
PARROT is a flexible recurrent neural network framework for analysis of large protein datasets

The rise of high-throughput experiments has transformed how scientists approach biological questions. The ubiquity of large-scale assays that can test thousands of samples in a day has necessitated the development of new computational approaches to interpret this data. Among these tools, machine learning approaches are increasingly being utilized due to their ability to infer complex nonlinear patterns from high-dimensional data. Despite their effectiveness, machine learning (and in particular deep learning) approaches are not always accessible or easy to implement for those with limited computational expertise. Here we present PARROT, a general framework for training and applying deep learning-based predictors on large protein datasets. Using an internal recurrent neural network architecture, PARROT is capable of tackling both classification and regression tasks while only requiring raw protein sequences as input. We showcase the potential uses of PARROT on three diverse machine learning tasks: predicting phosphorylation sites, predicting transcriptional activation function of peptides generated by high-throughput reporter assays, and predicting the fibrillization propensity of amyloid beta with data generated by deep mutational scanning. Through these examples, we demonstrate that PARROT is easy to use, performs comparably to state-of-the-art computational tools, and is applicable for a wide array of biological problems.
Concentric versus eccentric cycling at equal power output or effort perception: Neuromuscular alterations and muscle pain

This study aimed to compare neuromuscular alterations and perceptions of effort and muscle pain induced by concentric and eccentric cycling performed at the same power output or effort perception. Fifteen participants completed three 30‐min sessions: one in concentric at 60% peak power output (CON) and two in eccentric, at the same power output (ECCPOWER) or same perceived effort (ECCEFFORT). Muscle pain, perception of effort, oxygen uptake as well as rectus femoris and vastus lateralis electromyographic activities were collected when pedaling. The knee extensors maximal voluntary contraction (MVC) torque, the torque evoked by double stimulations at 100 Hz and 10 Hz (Dt100; Dt10), and the voluntary activation level (VAL) were evaluated before and after exercise. Power output was higher in ECCEFFORT than CON (89.1 ± 23.3% peak power). Muscle pain and effort perception were greater in CON than ECCPOWER (p < 0.03) while muscle pain was similar in CON and ECCEFFORT (p > 0.43). MVC torque, Dt100, and VAL dropped in all conditions (p < 0.04). MVC torque (p < 0.001) and the Dt10/ Dt100 ratio declined further in ECCEFFORT (p < 0.001). Eccentric cycling perceived as difficult as concentric cycling caused similar muscle pain but more MVC torque decrease. A given power output induced lower perceptions of pain and effort in eccentric than in concentric yet similar MVC torque decline. While neural impairments were similar in all conditions, eccentric cycling seemed to alter excitation‐contraction coupling. Clinicians should thus be cautious when setting eccentric cycling intensity based on effort perception.
Biology of primordial germ cells in vertebrates with emphasis in urodeles amphibians

Primordial germ cells (PGCs) are highly specialized cells that play a relevant role in the maintenance and evolution of the species, since they create new combinations of genetic information between the organisms. Amphibians are a class of amniote vertebrates that are divided into three subclasses, the anurans (frogs and toads), the urodeles (salamanders and newts), and the gymnophiones (caecilians). The study of PGCs in amphibians has been addressed in more detail in anurans while little is known about the biology of this cell lineage in urodeles. Studies in some urodeles species have suggested that PGCs are of mesodermal origin, specifying in the lateral plate mesoderm at the late gastrula stage. With classical experiments it shown that, there is an induction of mesoderm, therefore most likely urodeles PGCs develop from unspecialized mesodermal tissue that responds to extracellular signals. However, some fundamental biological processes of PGCs such as the analysis of their specification, arrival, and colonization to the gonads, and their maintenance and differentiation into mature and fertile gametes remain to be elucidated. Therefore, knowledge about the biology of PGCs is of great importance to ensure the perpetuation of urodeles amphibians, as some species are in danger of becoming extinct.
Identification of diagnostic and prognostic signatures derived from preoperative blood parameters for oral squamous cell carcinoma

Background We aimed to develop novel diagnostic and prognostic signatures based on preoperative inflammatory, immunological, and nutritional parameters in blood (PIINPBs) by machine learning algorithms for patients with oral squamous cell carcinoma (OSCC). Methods A total of 486 OSCC patients and 200 age and gender-matched non-OSCC patients who were diagnosed and treated at our institution for noninfectious, nontumor diseases were retrospectively enrolled and divided into training and validation cohorts. Based on PIINPB, 6 machine learning classifiers including random forest, support vector machine, extreme gradient boosting, naive Bayes, neural network, and logistic regression were used to derive diagnostic models, while least absolute shrinkage and selection operator (LASSO) analyses were employed to construct prognostic signatures. A novel prognostic nomogram integrating a PIINPB-derived prognostic signature and selected clinicopathological parameters was further developed. Performances of these signatures were assessed by receiver operating characteristic (ROC) curves, calibrating curves, and decision tree. Results Diagnostic models developed by machine learning algorithms from 13 PIINPBs, which included counts of white blood cells (WBC), neutrophils (N), monocytes (M), lymphocytes (L), platelets (P), albumin (ALB), and hemoglobin (Hb), along with albumin-globulin ratio (A/G), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI), displayed satisfactory discriminating capabilities in patients with or without OSCC, and among OSCC patients with diverse pathological grades and clinical stages. A prognostic signature based on 6 survival-associated PIINPBs (L, P, PNI, LMR, SII, A/G) served as an independent factor to predict patient survival. Moreover, a novel nomogram integrating prognostic signature and tumor size, pathological grade, cervical node metastasis, and clinical stage significantly enhanced prognostic power [3-year area under the curve (AUC) =0.825; 5-year AUC =0.845]. Conclusions Our results generated novel and robust diagnostic and prognostic signatures derived from PIINPBs by machine learning for OSCC. Performance of these signatures suggest the potential for PIINPBs to supplement current regimens and provide better patient stratification and prognostic prediction.
Predicting a therapeutic cut‐off serum level of itraconazole in recalcitrant tinea corporis and cruris—A prospective trial

With rising resistance to terbinafine, and consistently high MICs to fluconazole and griseofulvin, itraconazole is being increasingly used as a first line drug for tinea corporis/cruris. However, inadequate clinical responses are often seen with it in spite of in vitro susceptibility. This is possibly related to a variable pharmacokinetic profile of itraconazole. The drug serum levels associated with the therapeutic outcome have not been defined in dermatophytic infections.
The impact of liver fibrosis on microvascular invasion and prognosis of hepatocellular carcinoma with a solitary nodule: a Surveillance, Epidemiology, and End Results (SEER) database analysis

Background The pathogenesis of non-cirrhotic hepatocellular carcinoma (HCC) with a high recurrence remains controversial, while microvascular invasion (MVI) is highly suggestive of tumor recurrence. This study aimed to investigate the effects of liver fibrosis on MVI and prognosis in HCC. Methods Based on the data of HCC in the Surveillance, Epidemiology, and End Results (SEER) database [2004–2015], multivariate logistic regression was used for correlation analysis. Survival was analyzed by Log-Rank test and Cox regression, and decision curve analysis and receiver operating characteristic curves were established to evaluate alternative diagnostic and prognostic strategies. Results The study included 1,492 patients with MVI (17.8%) or without MVI (82.2%) for HCC with a solitary nodule. Liver fibrosis was significantly correlated with the occurrence of MVI, and the risk of MVI in patients with a fibrosis score F5–6 was lower than in those with a score of F0–4 (OR =0.651, 95% CI: 0.492–0.860). Combining liver fibrosis could improve the prediction performance of MVI risk models, but liver fibrosis was less associated with survival outcomes in comparison with other tumor characteristics. Conclusions Lower liver fibrosis correlated with a higher risk of MVI in HCC with a solitary nodule and was a good indicator for improving the performance of MVI risk models. However, it was not a prognostic sensitive indicator.
LXA4 protects against blue-light induced retinal degeneration in human A2E-laden RPE cells and Balb-c mice

Background Age-related macular degeneration (AMD) is one of the leading causes of permanent visual impairment in the elderly. Blue light (BL) has been reported to cause retinal damage and contribute to the onset and development of severe AMD. N-retinylidene-N-retinylethanolamine (A2E), a lipofuscin fluorophore, accumulates with ageing in the retinal pigment epithelium (RPE) cells. Once exposed to BL, A2E easily oxidizes to A2E-epoxides, causing oxidative-stress injury to the retina. Lipoxin A4 (LXA4), an endogenous anti-antioxidant lipid, plays a key role in multiple organs by binding to the formyl-peptide receptor-like 1 (FPRL1). This study examined the protective effects of LXA4 on oxidative–stress injury induced by BL exposure, and clarified the underlying mechanisms in cultured RPE cells and Balb-c mice. Methods LXA4 diluent was orally administered to mice before retinal degeneration was established. Optical coherence tomography, retinal histology, and RPE cell injury were assessed. Results LXA4 administration significantly ameliorated retinal damage as evidenced by the thicknesses of the retinal layers and the tight junctions of RPE cells in vivo. LXA4 inhibited BL-induced reactive oxygen species (ROS) production, reduced tight junctions, and the death of A2E-laden RPE cells. LXA4 also potently increased the expression of haem oxygenase-1 (HO1) and NAD(P)H quinone oxidoreductase 1 (NQO1), probably by decreasing the association between nuclear factor erythroid 2-related factor 2 (NRF2) and Kelch-like ECH (Epichlorohydrin) -associated protein 1 (Keap1), and ameliorating NRF2 nuclear translocation and the antioxidant response element (ARE) deoxyribonucleic acid (DNA) binding activity. Conclusions Our results showed that LXA4 ameliorated retinal degeneration, and should be considered in the prevention and treatment of AMD.
Where is the social in the biopsychosocial model of suicide prevention?

Background: Each year, around 800,000 people die by suicide. The prevalence of suicidal behaviors is much higher when suicidal attempts and persistent self-injurious ideation are included. Therefore, suicide is a public health concern. Research has been sensitive to this problem, deepening the study of risk factors and the development of theoretical frameworks of suicidal behavior, with the aim of generating effective suicide prevention policies around the biopsychosocial model. Aim: We aimed to explore the role of relational, community, and social factors in current suicide prevention strategies. Method: Studies of risk and protective factors for suicidal behavior and the consequent development of theoretical frameworks were reviewed to verify if this knowledge was really used in suicide prevention policies. Results: Studies of risk and protective factors focus mainly on the individual, while theoretical frameworks emphasize the role of the relational, community, and social. Suicide prevention strategies more closely follow individual models derived from studies of risk factors. Conclusions: Suicide prevention strategies should broaden their individual narrative to include relational, community, and social interventions as anti-suicide measures.
Modification of Poly(dimethylsiloxane) by Mesostructured Siliceous Films for Constructing Protein-Interactive Surfaces

We investigated the coating process of mesostructured triblock copolymer-tetraethoxysilane (P123-TEOS) and mesoporous silica (MPS) films on a bioinert poly(dimethylsiloxane) (PDMS) with the different cross-linker concentrations through an oxygen-plasma treatment to evaluate the mesostructure formation and adsorption ability of proteins (albumin, fibrinogen, γ-globulin, fetal bovine serum). In the PDMS preparation, the cross-linker concentration affected the polymer network formation and the siliceous layer was formed on the most-surfaces by the plasma treatment. The transparent siliceous films of P123-TEOS and MPS were successfully covered on the cross-linked PDMS without voiding and the coating film thicknesses were ca. 100 nm. The FT-IR spectra indicated that the change from P123-TEOS to MPS occurred with preserving the PDMS chemical bonds by the calcination. Especially, the XRD patterns and nitrogen adsorption and desorption isotherms of the MPS on PDMS indicated the mesostructured film formation with preserving the ordered nanopore structures (BJH pore sizes: 1.6–4.2 nm, BET surface areas: 394–602 m/g). The hydrophobic PDMS surfaces became more wettable by the coating. The adsorption amounts of acidic proteins (albumin, fibrinogen) were changed by the coating. For the fibrinogen, the P123-TEOS on PDMS exhibited the most adsorption sites. Therefore, the bio-interactive properties of the PDMS surfaces were demonstrated based on the coating processes. [DOI: 10.1380/ejssnt.2018. 41]
Whole-object effects in visual word processing: Parallels with and differences from face recognition

ABSTRACT Visual words and faces differ in their structural properties, but both are objects of high expertise. Holistic processing is said to characterize expert face recognition, but the extent to which whole-word processes contribute to word recognition is unclear, particularly as word recognition is thought to proceed by a component-based process. We review the evidence for experimental effects in word recognition that parallel those used to support holistic face processing, namely inversion effects, the part-whole task, and composite effects, as well as the status of whole-word processing in pure alexia and developmental dyslexia, contrasts between familiar and unfamiliar languages, and the differences between handwriting and typeset font. The observations support some parallels in whole-object influences between face and visual word recognition, but do not necessarily imply similar expert mechanisms. It remains to be determined whether and how the relative balance between part-based and whole-object processing differs for visual words and faces.
The Importance of Cutaneous Innervation in Wound Healing: From Animal Studies to Clinical Applications

The skin is a neuroimmunoendocrine organ that regularly undergoes injury and repair. The complex process of wound healing relies heavily on the cutaneous nervous system. Despite the observation that wound healing deficiencies cause significant morbidity and mortality for patients with nervous dysfunction across many disciplinaries, the role of cutaneous innervation in wound repair has not been well elucidated. In a previous article, we learned the basics of cutaneous neuroanatomy and the important neuropeptides involved in the wound healing process. Currently, we aim to synthesize the basics with observations from animal models and human studies for a more comprehensive understanding of nervous system involvement in cutaneous wound healing. We have demonstrated in this review, the importance of the cutaneous nervous system in each phase of wound healing through basic science research, animal experiments, and human studies.