Miracle-dz/UniFAR-FTUs huggingface dataset:
Unraveling the mechanisms of intrinsic drug resistance in Mycobacterium tuberculosis

Tuberculosis (TB) is among the most difficult infections to treat, requiring several months of multidrug therapy to produce a durable cure. The reasons necessitating long treatment times are complex and multifactorial. However, one major difficulty of treating TB is the resistance of the infecting bacterium, Mycobacterium tuberculosis (Mtb), to many distinct classes of antimicrobials. This review will focus on the major gaps in our understanding of intrinsic drug resistance in Mtb and how functional and chemical-genetics can help close those gaps. A better understanding of intrinsic drug resistance will help lay the foundation for strategies to disarm and circumvent these mechanisms to develop more potent antitubercular therapies.
Evolution of intrinsic ellipticity correlations due to peculiar motion

Topic of this paper is the time-evolution of intrinsic correlations of galaxy ellipticities due to peculiar motion. In our model, the galaxy ellipticities are determined from the angular momentum of their host haloes, which can be computed from the fluctuations statistics of a Gaussian random field. Subsequent peculiar motion distorts the ellipticity field and causes changes in the ellipticity correlations. Using analogies between this problem of shifted ellipticity tensors and the displacements of polarisation tensors in gravitational lensing of the cosmic microwave background we compute E-mode and B-mode spectra of the time-evolved ellipticity field, where the displacements are modelled with first and second order Lagrangian perturbation theory. For EUCLID, ellipticity correlations are decreased on large multipoles l >1000, amounting to up to 10% in the E-mode spectrum C_E^epsilon(l) and up to 60% in the B-mode spectrum C_B^epsilon(l) at l~3000 due to the dispersing effect of peculiar motion. E/B-mode conversion in analogy to CMB-lensing is present but small. We conclude that distortions of the ellipticity field due to peculiar motion is not affecting the prediction of ellipticity models on the scales relevant for lensing in the case of EUCLID's galaxy distribution, but should affect larger scales for surveys at lower redshifts.
Anatomical labeling of intracranial arteries with deep learning in patients with cerebrovascular disease

Brain arteries are routinely imaged in the clinical setting by various modalities, e.g., time-of-flight magnetic resonance angiography (TOF-MRA). These imaging techniques have great potential for the diagnosis of cerebrovascular disease, disease progression, and response to treatment. Currently, however, only qualitative assessment is implemented in clinical applications, relying on visual inspection. While manual or semi-automated approaches for quantification exist, such solutions are impractical in the clinical setting as they are time-consuming, involve too many processing steps, and/or neglect image intensity information. In this study, we present a deep learning-based solution for the anatomical labeling of intracranial arteries that utilizes complete information from 3D TOF-MRA images. We adapted and trained a state-of-the-art multi-scale Unet architecture using imaging data of 242 patients with cerebrovascular disease to distinguish 24 arterial segments. The proposed model utilizes vessel-specific information as well as raw image intensity information, and can thus take tissue characteristics into account. Our method yielded a performance of 0.89 macro F1 and 0.90 balanced class accuracy (bAcc) in labeling aggregated segments and 0.80 macro F1 and 0.83 bAcc in labeling detailed arterial segments on average. In particular, a higher F1 score than 0.75 for most arteries of clinical interest for cerebrovascular disease was achieved, with higher than 0.90 F1 scores in the larger, main arteries. Due to minimal pre-processing, simple usability, and fast predictions, our method could be highly applicable in the clinical setting.
Perioperative and short-term outcomes of laparoscopic liver resection for recurrent hepatocellular carcinoma: A retrospective study comparing open hepatectomy

Background To compare the perioperative and short-term outcomes of laparoscopic liver resection (LLR) and open liver resection (OLR) in recurrent hepatocellular carcinoma (rHCC) based on propensity score matching (PSM) to investigate therapeutic safety, efficacy, and value for clinical application. Methods Forty-nine patients with rHCC who underwent surgery at Wenzhou People’s Hospital between January 2017 and March 2022 were retrospectively analyzed and classified into LLR (n=30) and OLR (n=22) cases based on the surgical method. Thirty-eight patients were screened using PSM for data analysis to compare basic clinical characteristics, perioperative outcomes, and postoperative recurrence in both groups. Results Before PSM, the tumour diameter was larger, tumor staging (BCLC staging system), intraoperative blood loss, units of blood transfused, constituent ratio of liver cirrhosis, incidence of MVI and intravascular tumour thrombus and postoperative complication were higher, and duration of hospital stay was significantly longer in the OLR group compared to those in the LLR group (p < 0.05). After PSM, there were no significant differences regarding tumour diameter, MVI incidence, blood transfusion amount or postoperative complication rate in the LLR and OLR groups. The tumor staging, incidence of vascular cancer thrombus, intraoperative blood loss and postoperative duration of hospitalisation were significantly higher in the OLR group than in the LLR group (p<0.05). The difference in recurrence-free survival (RFS) between the two groups was not statistically significant (p = 0.383). Conclusion LLR for recurrent hepatocellular carcinoma can reduce intraoperative blood loss and postoperative complication rate, shorten the duration of hospitalisation, and is superior to OLR regarding perioperative and short-term efficacy, demonstrating good safety and feasibility.
Responses of soil bacterial communities to precipitation change in the semi-arid alpine grassland of Northern Tibet

A change in precipitation can profoundly change the structure of soil microbial communities, especially in arid and semi-arid areas which are limited by moisture conditions. Therefore, it is crucial to explore how soil bacterial community composition and diversity will respond to variation in precipitation. Here we conducted a precipitation control experiment to simulate precipitation change by reducing and increasing rainfall by 25%, 50%, and 75% in the alpine grasslands of northern Tibet. The composition, diversity, and species interaction network of soil microbial community were studied by high-throughput sequencing, and the relationship between microbial community species and soil environmental factors was analyzed. Our results showed that Proteobacteria (45%–52%) and Actinobacteria (37%–45%) were the dominant bacteria in the soil. The alpha diversity index based on Shannon, Chao1, and Simpson indices revealed that precipitation change had no significant effect on richness and evenness of soil microbial communities. Non-metric multidimensional scaling (NMDS) and analysis of similarities (ANOSIM) showed that a clear separation of soil microbial communities between D2(-50%),D3(-75%) and W2(+50%), W3(+75%) treatments. The microbial interaction network indicated that the water-increasing treatment group had closer connections, and Proteobacteria and Actinomycetes were the core species. Furthermore, there was a stronger positive correlation between species in the water-reducing treatment group, the contribution of Proteobacteria decreased significantly, the role of connecting hub decreased, and Actinomycetes became the most important core microbial species. In addition, soil water content (SWC) and available phosphorus (AP) were closely related to the variations in soil microbial compositions. The findings of this study provide a theoretical basis for the driving mechanism of global climate change on soil microbial community and grassland ecosystem in alpine grassland.
Mitochondria and sensory processing in inflammatory and neuropathic pain

Rheumatic diseases, such as osteoarthritis and rheumatoid arthritis, affect over 750 million people worldwide and contribute to approximately 40% of chronic pain cases. Inflammation and tissue damage contribute to pain in rheumatic diseases, but pain often persists even when inflammation/damage is resolved. Mechanisms that cause this persistent pain are still unclear. Mitochondria are essential for a myriad of cellular processes and regulate neuronal functions. Mitochondrial dysfunction has been implicated in multiple neurological disorders, but its role in sensory processing and pain in rheumatic diseases is relatively unexplored. This review provides a comprehensive understanding of how mitochondrial dysfunction connects inflammation and damage-associated pathways to neuronal sensitization and persistent pain. To provide an overall framework on how mitochondria control pain, we explored recent evidence in inflammatory and neuropathic pain conditions. Mitochondria have intrinsic quality control mechanisms to prevent functional deficits and cellular damage. We will discuss the link between neuronal activity, mitochondrial dysfunction and chronic pain. Lastly, pharmacological strategies aimed at reestablishing mitochondrial functions or boosting mitochondrial dynamics as therapeutic interventions for chronic pain are discussed. The evidence presented in this review shows that mitochondria dysfunction may play a role in rheumatic pain. The dysfunction is not restricted to neuronal cells in the peripheral and central nervous system, but also includes blood cells and cells at the joint level that may affect pain pathways indirectly. Pre-clinical and clinical data suggest that modulation of mitochondrial functions can be used to attenuate or eliminate pain, which could be beneficial for multiple rheumatic diseases.
Joint together: The etiology and pathogenesis of ankylosing spondylitis

Spondyloarthritis (SpA) refers to a group of diseases with inflammation in joints and spines. In this family, ankylosing spondylitis (AS) is a rare but classic form that mainly involves the spine and sacroiliac joint, leading to the loss of flexibility and fusion of the spine. Compared to other diseases in SpA, AS has a very distinct hereditary disposition and pattern of involvement, and several hypotheses about its etiopathogenesis have been proposed. In spite of significant advances made in Th17 dynamics and AS treatment, the underlying mechanism remains concealed. To this end, we covered several topics, including the nature of the immune response, the microenvironment in the articulation that is behind the disease’s progression, and the split between the hypotheses and the evidence on how the intestine affects arthritis. In this review, we describe the current findings of AS and SpA, with the aim of providing an integrated view of the initiation of inflammation and the development of the disease.
Exogenous salicylic acid regulates organic acids metabolism in postharvest blueberry fruit

Fruit acidity is an essential factor affecting blueberry organoleptic quality. The organic acid content in blueberry fruit mainly contributes to fruit acidity. This study aims to evaluate the effect of exogenous salicylic acid (SA), the principal metabolite of aspirin, on the organoleptic quality and organic acid metabolism in rabbiteye blueberry (Vaccinium virgatum Ait, ‘Powderblue’) during cold storage (4 °C). Results showed that SA-treated fruit reduced fruit decay and weight loss delayed fruit softening, and decline of total soluble solids (TSS). TA and total organic acid amounts stayed the same during the late storage period in SA-treated fruit. Four kinds of organic acid components, malic acid, quinic acid, citric acid, and succinic acid, were at higher levels in fruit treated by SA as compared to control. SA enhanced the activities of PEPC, NAD-MDH, and CS to promote the synthesis of malic acid and citric acid. Meanwhile, the activities of NADP-ME, ACL, and ACO, which participated in the degradation of malic acid and citric acid, were inhibited by SA. qPCR results also showed that the expression of VcPEPC, VcNAD-MDH, and VcCS genes were upregulated. In contrast, SA downregulated the expression of VcNADP-ME, VcACL, and VcACO genes. In conclusion, SA could regulate the key genes and enzymes that participated in organic acids metabolism to maintain the freshness of blueberry during cold storage, therefore minimizing the economic loss.
A novel 3D deep learning model to automatically demonstrate renal artery segmentation and its validation in nephron-sparing surgery

Purpose Nephron-sparing surgery (NSS) is a mainstream treatment for localized renal tumors. Segmental renal artery clamping (SRAC) is commonly used in NSS. Automatic and precise segmentations of renal artery trees are required to improve the workflow of SRAC in NSS. In this study, we developed a tridimensional kidney perfusion (TKP) model based on deep learning technique to automatically demonstrate renal artery segmentation, and verified the precision and feasibility during laparoscopic partial nephrectomy (PN). Methods The TKP model was established based on convolutional neural network (CNN), and the precision was validated in porcine models. From April 2018 to January 2020, TKP model was applied in laparoscopic PN in 131 patients with T1a tumors. Demographics, perioperative variables, and data from the TKP models were assessed. Indocyanine green (ICG) with near-infrared fluorescence (NIRF) imaging was applied after clamping and dice coefficient was used to evaluate the precision of the model. Results The precision of the TKP model was validated in porcine models with the mean dice coefficient of 0.82. Laparoscopic PN was successfully performed in all cases with segmental renal artery clamping (SRAC) under TKP model’s guidance. The mean operation time was 100.8 min; the median estimated blood loss was 110 ml. The ischemic regions recorded in NIRF imaging were highly consistent with the perfusion regions in the TKP models (mean dice coefficient = 0.81). Multivariate analysis revealed that the feeding lobar artery number was strongly correlated with tumor size and contact surface area; the supplying segmental arteries number correlated with tumor size. Conclusions Using the CNN technique, the TKP model is developed to automatically present the renal artery trees and precisely delineate the perfusion regions of different segmental arteries. The guidance of the TKP model is feasible and effective in nephron-sparing surgery.
The lead-lag relationship among select regional islamic equity markets

This study investigates the issue of integration in regional Islamic equity markets. For this purpose, four of the Dow Jones Islamic indexes, namely USA, UK, Euro Zone, and Asia Pacific have been selected for analysis. The issue is approached from two perspectives: (i) whether these markets move together (ii) and the dynamic linkages from the lead-lag relationships. Our analysis finds one significant cointegrating relationship among the selected Islamic equity markets, with the U.K Islamic equity market being the follower and the U.S Islamic equity market being the most leading one. These findings may suggest that Islamic equity markets also have a strong long-run equilibrium relationship mostly driven by fundamental element of the economy. In addition, the strong leading role of the U.S. Islamic equity index means that the U.S. market has a strong influence over the other regional markets even within the context of Islamic finance. The global bullish financial market driven by the U.S. market, which was followed by the subprime crisis, may explain this evidence.
Golden point of no-scale and no-parameter F-SU(5)

The F-lipped SU(5) x U(1)(X) grand unified theory supplemented by TeV-scale vectorlike particles from F-theory, together dubbed F-SU(5), offers a natural multiphase unification process which suggests an elegant implementation of the no-scale supergravity boundary conditions at the unification scale M(F) similar or equal to 7 x 10(17) GeV. Enforcing the no-scale boundary conditions, including B(mu)(M(F)) = 0 on the Higgs bilinear soft term, with the precision 7-year WMAP value on the dark matter relic density isolates a highly constrained "golden point" located near M(1/2) = 455 GeV and tan beta = 15 in the tan beta-M(1/2) plane, which simultaneously satisfies all known experiments, and moreover corresponds to an imminently observable proton decay rate. Because the universal gaugino mass is actually determined from established low energy data via renormalization group equation running, there are no surviving arbitrary scale parameters in the present model.
A neural machine translation system for Galician from transliterated Portuguese text

We present a neural machine translation (NMT) system for translating both Spanish and English to Galician ( 𝐸𝑆 – 𝐺𝐿 and 𝐸𝑁 – 𝐺𝐿 ). Galician is a language closely related to Portuguese, with low to medium resources, spoken in northwestern Spain. Our NMT system is trained on large-scale synthetic 𝐸𝑆 → 𝑃𝑇 → 𝐺𝐿 and 𝐸𝑁 → 𝑃𝑇 → 𝐺𝐿 parallel corpora created by the spelling transliteration of Portuguese to Galician from a high-quality Spanish to Portuguese ( 𝐸𝑆 – 𝑃𝑇 ) and English to Portuguese ( 𝐸𝑁 – 𝑃𝑇 ) translation memories. The NMT system is then made available via a public web interface at https://demos.citius. usc.es/nos_tradutor.
Intellectualism and the argument from cognitive science in Philosophical Psychology please published version

Theoretical knowledge, such as knowing that Paris is the capital of France or that water freezes at zero degrees Celsius, is widely accepted to be a propositional attitude. Is practical knowledge, such as knowing how to play the piano or how to ride a bike, also a propositional attitude? The Intellectualist says yes: when someone knows how to play the piano, or knows how to ride a bike, there is a proposition that they know. Two different kinds of evidence have been invoked in the debate over Intellectualism: semantic evidence and scientific evidence. Those who appeal to semantic evidence are concerned with whether our ascriptions of practical knowledge (‘knowing-how’) follow the same truth-conditional semantics as our ascriptions of theoretical knowledge (‘knowing-that’). Those who appeal to scientific evidence are concerned with whether our best theories in cognitive science posit propositions to play similar explanatory roles in both practical knowledge and theoretical knowledge. In this paper, we are primarily interested in the relationship between Stanley and Williamson’s (2001) semantic argument for Intellectualism and the ‘argument from cognitive science’ against it: the anti-Intellectualist response from philosophers (including Noë 2005, Devitt 2011, Roth and Cummins 2011) who use scientific evidence to suggest that practical knowledge is non-propositional.
Effect of alcohol and smoking on semen analysis parameters

Background: Infertility affects close to 10%–15% of all couples in reproductive age group. A myriad of life style variables including consumption of alcohol, smoking along with increased exposure to electromagnetic waves emitting from cell phones and personal computers for prolonged durations, have had a negative impact on the quality of semen in males. Materials and Methods: This cross-sectional study was conducted on 250 male patients under evaluation for infertility. Physical and macroscopic examination was carried out followed by in detail microscopic examination according to the World Health Organization 2010 guidelines. Results: Fertility scoring was done for all 250 subjects and 67.2% of cases were found to be fertile, 14.4% were subfertile, and 18.4% of cases were found to be infertile. Among the 168 fertile subjects, majority 75.6% of cases were young in the age group of 20–30 years, 85.1% of cases did not consume alcohol, and 86.3% of cases did not smoke. Among the 46 infertile subjects, majority 54.3% of cases were in the age group of 20–30 years, 84.8% of cases consumed some amount of alcohol, and 54.3% of cases had a history of tobacco smoking. Majority 64.1% of the subjects having a combination of all three lifestyle factors were found to be infertile, whereas only 2.6% of such subjects were found to be fertile. Conclusion: This study shows that the consumption of alcohol and cigarette smoking has a significant deleterious effect on the process of sperm production and male reproductive potential; therefore, counseling regarding this negative impact needs to be focused upon by all clinicians and infertility specialists while handling such cases.
Playful Participatory Mapping: Co-creating Games to Foster Systems Thinking

This paper presents a currently evolving hybrid research, teaching and public engagement methodology that uses game design principles and elements to overcome established limitations of participatory research methodologies and pedagogies (such as lack of transferability of findings and difficulties in comparing outcomes and datasets) through the inclusion of game design elements and a focus on systems thinking. Game design is inherently rooted in systems thinking, which has been highlighted a key competence in addressing the “wicked” problems and Sustainable Development Goals, a linkage which is still weakly explored by research. The paper will discuss the methodology’s theoretical groundings and inspirations, with a particular focus on linking participatory approaches, game design and Donella Meadows’s work on “Leverage Points” for systems-oriented interventions. The paper will then discuss how the methodology builds on and moves beyond established community mapping approaches by working with participants to progressively and co-creatively add more formalised game-like elements and dynamics (simulation, goal-setting, player-mapping, turn-taking, role-playing) that organically scaffold participants in moving towards more abstract systems modelling. Following an articulation of the process and its underlying theoretical framework, the paper will also present brief, reflective accounts of a number of experiments in playful participatory community mapping facilitated over a 18-month period, with diverse groups of participants across different countries engaging with the methodology and informing its evolution. These accounts will showcase how the game design lens has allowed participant communities to develop systems thinking and engage in systems mapping, moving from materially grounded and culturally relevant categories towards more systematised models, which include possible, practical “leverage points” for intervention.