Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative MODS-Wayne Assay for Rapid Detection of Pyrazinamide Resistance in Mycobacterium tuberculosis from Sputum Samples

Background: Tuberculosis (TB) remains a significant global health challenge, particularly with the rise of drug-resistant strains, such as Pyrazinamide (PZA)-resistant TB. This resistance hampers treatment effectiveness. Currently, there's a lack of affordable and precise quantitative tests for detecting PZA resistance, highlighting the need for accessible diagnostic tools. Our study introduces a direct, accurate, and accessible susceptibility test for PZA resistance by quantifying pirazinoic acid (POA). Methods: We analyzed 264 TB-positive samples (MP and TBN) to assess PZA susceptibility by measuring POA production. This was done using the MODS-Wayne qualitative assay and our developed quantitative approach (MODS-WQ). For MODS-WQ, TBN samples were processed in 7H9 media (MODS-WQ 7H9) and MP samples in citrate buffer (MODS-WQ CB). We measured POA levels using spectrophotometry against a calibration curve, with PZA susceptibility determined by a composite standard. We also investigated the correlation between POA levels and pyrazinamidase mutations. Multidrug-resistant samples were assessed using the MODS test, and statistical analyses were conducted. Results:Approximately 23.48% of the samples showed PZA resistance, which included 62.8% of the multidrug-resistant (MDR) samples. The MODS-Wayne assay demonstrated an 87.8% sensitivity and 95.9% specificity for MP samples, and 62.5% sensitivity with 93.7% specificity for TBN samples. The MODS-WQ identified specific cut-off points: 123.25 M for MODS-WQ 7H9 and 664.7 M for MODS-WQ CB, with corresponding sensitivities of 81.25% and 92.31%, and specificities of 77.22% and 95.93%. Significantly lower POA levels were observed in samples with mutations in the metal binding site compared to mutations on the enzyme's periphery. Conclusions: The citrate-buffered MODS-WQ demonstrates high sensitivity and specificity in quantifying POA. It offers a significant improvement over qualitative methods, effectively overcoming their subjectivity limitations in PZA resistance detection.
Prevalence of Hypertension, awareness, treatment, and blood pressure control in Sierra Leone: A systematic review and meta-analysis

Background: In recent years, the prevalence of Hypertension (HTN) has increased in sub-Saharan countries. However, reports on the prevalence of HTN in Sierra Leone are limited. Therefore, we conducted a systematic review and meta-analysis to assess the overall estimates of the prevalence of HTN in Sierra Leone. Method: A systematic search of electronic databases (PubMed, Embase, African Journal Online and Google Scholar) was conducted by three independent investigators using keywords such as hypertension, prevalence, blood pressure, and Sierra Leone. A random-effects model was used to estimate the prevalence across studies. Heterogeneity among studies was assessed using the Cochran Q test and I2 statistic, and publication bias was assessed using funnel plots and the Egger test. Results: We pooled the data from 15 studies (n=14,707) that met the inclusion criteria. The overall prevalence of HTN in Sierra Leone was 27.64% [95% CI = 27.45, 27.82], with significant heterogeneity observed among studies (I2 =99.82%, p-value < 0.001). The pooled prevalence of Hypertension among males was higher than that among females (25.11% [95% CI = 24.90-25.32], I2 =99.79%, p-value < 0.001) and 24.11% [95% CI = 23.92,24.31, I2 =99.67%, p-value < 0.001]). The prevalence of HTN among urban residents (29.76%) was almost twice that among their rural counterparts (15.77%). Of those with HTN, 37.21% were aware of their illness, 12.87% received treatment, and only 29.73% had blood pressure control. Conclusion: More than 1 in 4 adults aged [≥] 15 years are living with HTN in Sierra Leone, with a low awareness rate and even lower treatment and control rates. Our findings highlighted the need for robust and comprehensive hypertension prevention, treatment and control policies. Keywords: Prevalence, Hypertension, Treatment, Systematic review, Meta-analysis, Sierra Leone
Borneol promotes autophagic degradation of HIF-1α and enhances chemotherapy sensitivity in malignant glioma

Background Gliomas are characterized by high mortality rates and resistance. Even with conventional chemotherapy the prognosis of glioblastoma remains poor. Many medications are not optimally effective due to limited bioavailability. The bioavailability of medicine can be enhanced by borneol, a monoterpenoid substance. In this study, we investigated the effect of borneol, a commonly used Chinese medicine, on chemosensitivity in C6 glioma and U251 human glioma cell lines and elucidated its therapeutic molecular targets. Methods The chemosensitivity-inducing effects of borneol in C6 and U251 cells were examined using CCK8 and clonal formation assays. The mechanism underlying the effect of borneol was evaluated through immunohistochemistry and western blotting assays. Further, the number of autophagosomes was determined via transmission electron microscopy. Finally, the chemical sensitization effect of borneol was evaluated in SD rats after C6 orthotopic tumor transplantation. Results Borneol increased cytotoxicity in C6 and U251 cells in response to temozolomide (TMZ). In addition, through transmission electron microscopy, western blotting, and immunohistochemical tests, we found that borneol combined with TMZ significantly increased the level of autophagy and that hypoxia inducible factor-1(HIF-1α) is a candidate target through which borneol enhances the cytotoxic effect of TMZ. Borneol’s ability to enhance HIF-1α degradation was counteracted following the administration of autophagy inhibitors. In vivo, borneol treatment was found to enhance the anticancer effect of TMZ and delay tumor progression, and this effect was closely related to its ability to promote the autophagic degradation of HIF-1α. Conclusions HIF-1α might be a valid therapeutic target of borneol, which can be potentially applied as a chemosensitizing drug used for glioma treatment.
A Case of Late-Onset Neutropenia in Relapsing-Remitting Multiple Sclerosis Following Ocrelizumab Therapy

Ocrelizumab, a monoclonal antibody, has proven effective in treating both primary progressive and relapsing-remitting multiple sclerosis. Common adverse effects observed in clinical studies include flushing, sore throat, pruritus, and rash. This abstract discusses a case of severe, late-onset neutropenia in a patient with relapsing-remitting multiple sclerosis undergoing ocrelizumab treatment. The neutropenia emerged 46 days following the patient's most recent ocrelizumab dose. The patient responded well to treatment with intravenous meropenem and filgrastim. This rare and unforeseen adverse effect highlights the importance of regular blood monitoring for early detection of severe neutropenia in patients treated with ocrelizumab.
THE EFFECTS OF FOOD AID ON AGRICULTURAL PRACTICES IN JUMLA, NEPAL

A scoping review was conducted to obtain a greater understanding of the literature related to international food aid, food aid in Nepal, and agricultural change in Nepal. Out of more than 5,000 articles, 444 were identified as relevant, with 165 articles related to food aid and developing countries, 203 related to Nepal in general, and 167 related to agricultural change in Nepal. The debate about disincentives to agriculture is the most common theme in literature on international food aid; however, no universally applicable conclusions were ascertained. Rather, impacts of food aid are country, region and location specific, and consistently are influenced by many dynamically shifting variables. The process of food aid has also changed over the years. Instead of large shipments of food aid delivered to a country through program food aid, developing countries are more likely to receive project and emergency food aid, targeted towards the areas of greatest need. As a result, direct comparison of findings among different food aid studies is problematic. A handful of strongly empirical analyses of food
Analysis on the early immigration of rice planthoppers in southern Guangxi in 2008

Southern China experienced unusually cold conditions in February 2008 which caused an obvious decline in the number of brown planthoppers(BPH,Nilaparvata lugens(Stl)) and white-backed planthoppers(WBPH,Sogatella furcifera(Horvath)) overwintering in the region.However,mass immigration of WBPH occurred in late March and April 2008 in the Guangxi Zhuang Autonomous Region.Based on the analysis of daily light-trap catches,field surveys,overwintering,immigration trajectory simulation and meteorological background analysis,the following conclusions can be drawn:(1) The main source areas of the early immigration of WBPH into Qinzhou in 2008 were in central Vietnam and southern Laos,with very few sites in northern Vietnam. (2) High temperature at 850 hPa,lower level jet stream winds and premature typhoons were the key factors affecting the settlment of both BPH and WBPH in Qinzhou.Therefore,central as well as northern Vietnam must be regarded as potential sourced of rice planthoppers in southern China.
Selection of phytotoxicity tests for use in ecological risk assessments

Background 516 Approach to phytotoxicity 517 Standardized methods 518 Terrestrial plant tests 518 Aquatic macrophyte tests 520 Terrestrial test species 521 Regulatory guidance 521 Published standards 526 General literature 526 Endpoints 527 Regulatory guidance and published standards 527 General literature 527 Rationale 527 Percentage germination 528 Percentage survival 530 Growth 530 Photosynthesis 533 Reproduction 535 Morbidity 535 Tissue concentration 536 Analytical approaches 536 Effect level estimates 537 NOAEC and LOAEC 537 Median effects estimates 538 Hypotheses testing 538 Single vs. multiple endpoints 539
A phenylalanine at the extracellular side of Kir1.1 facilitates potassium permeation

ABSTRACT The Kir1.1 (ROMK) family of weak inward rectifiers controls K secretion in the renal CCT and K recycling in the renal TALH. A single point mutant of the inward rectifier, F127V-Kir1.1b was used to investigate the K transition between the selectivity filter and the outer mouth of the channel. We hypothesize that normally an aromatic Phe at the external entryway of Kir1.1b facilitates outward K secretion. We tested this by replacing F127-Kir1.1b with a small aliphatic Val. Results indicate that removal of the Phe at 127 suppresses outward currents that normally contribute to K secretion. Results with the F127V mutant could be explained by increased polyamine block and/or a decrease in the avidity of Kir1.1 for K ions near the outer mouth of the channel. The latter is supported by F127V-Kir1.1b having a lower affinity (Km = 33 mM) for K than wild-type Kir1.1b (Km = 7 mM) during external K elevation. Conversely, chelation of K with 18-Crown-6 ether reduced K conductance faster in F127V (half-time = 6s) than in wt-Kir1.1b (half-time = 120s), implying that F127V is less hospitable to external K. In other experiments, positive membrane potentials gated the F127V mutant channel closed at physiological levels of external Ca, possibly by electrostatically depleting K adjacent to the membrane, suggesting that the Phe residue is critical for outward K secretion at physiological Ca. We speculate that the avidity of wt-Kir1.1b for external K could result from a cation-Pi interaction between K and the aromatic F127.
The shape of the change: Cumulative and incremental changes in daily mood during mobile-app-supported mindfulness training.

Understanding of the exact trajectories of mood improvements during mindfulness practice helps to optimize mindfulness-based interventions. The Mindfulness-to-Meaning model expects mood improvements to be linear, incremental, and cumulative. Our findings align with this expectation. We used multilevel growth curve models to analyze daily changes in positive mood reported by 190 Polish participants during 42 days of a mobile-app-supported, mindfulness-based intervention. The daily positive mood increased among 83.68% of participants. Participants who started the training reported worse mood improved more and faster than participants with better mood at the baseline. Dispositional mindfulness and narcissism - individual difference variables associated with high vs. low emotion regulation ability, respectively - were not associated with mood improvement trajectories. A small group of participants (16.32%) showed a steady decline in positive mood during the intervention. The results underscore the importance of a more comprehensive understanding of individual variability in benefiting from mindfulness-based interventions.
Hybrid-renewable processes for biofuels production: concentrated solar pyrolysis of biomass residues

The viability of thermochemically-derived biofuels can be greatly enhanced by reducing the process parasitic energy loads. Integrating renewable power into biofuels production is one method by which these efficiency drains can be eliminated. There are a variety of such potentially viable "hybrid-renewable" approaches; one is to integrate concentrated solar power (CSP) to power biomass-to-liquid fuels (BTL) processes. Barriers to CSP integration into BTL processes are predominantly the lack of fundamental kinetic and mass transport data to enable appropriate systems analysis and reactor design. A novel design for the reactor has been created that can allow biomass particles to be suspended in a flow gas, and be irradiated with a simulated solar flux. Pyrolysis conditions were investigated and a comparison between solar and non-solar biomass pyrolysis was conducted in terms of product distributions and pyrolysis oil quality. A novel method was developed to analyse pyrolysis products, and investigate their stability.
JWST/NIRCam Imaging of Young Stellar Objects. II. Deep Constraints on Giant Planets and a Planet Candidate Outside of the Spiral Disk Around SAO 206462

We present JWST/NIRCam F187N, F200W, F405N, and F410M direct imaging data of the disk surrounding SAO 206462. Previous images show a very structured disk, with a pair of spiral arms thought to be launched by one or more external perturbers. The spiral features are visible in three of the four filters, with the nondetection in F410M due to the large detector saturation radius. We detect with a signal-to-noise ratio of 4.4 a companion candidate that, if on a coplanar circular orbit, would orbit SAO 206462 at a separation of ∼300 au, 2.25σ away from the predicted separation for the driver of the eastern spiral. No other companion candidates were detected. At the location predicted by simulations of both spirals generated by a single massive companion, the NIRCam data exclude objects more massive than ∼2.2 M J assuming the BEX evolutionary models. In terms of temperatures, the data are sensitive to objects with T eff ∼ 650–850 K, when assuming planets emit like blackbodies (R p between 1 and 3R J). From these results, we conclude that if the spirals are driven by gas giants, these must be either cold or embedded in circumplanetary material. In addition, the NIRCam data provide tight constraints on ongoing accretion processes. In the low extinction scenario we are sensitive to mass accretion rates of the order M ̇ ∼ 10 − 9 M J yr−1. Thanks to the longer wavelengths used to search for emission lines, we reach unprecedented sensitivities to processes with M ̇ ∼ 10 − 7 M J yr−1 even toward highly extincted environments (A V ≈ 50 mag).
Kinematic Base State Estimation for Humanoid using Invariant Extended Kalman Filter

This paper presents the design and implementation of a Right Invariant Extended Kalman Filter (RIEKF) for estimating the states of the kinematic base of the Surena V humanoid robot. The state representation of the robot is defined on the Lie group $SE_{4}$ (3), encompassing the position, velocity, and orientation of the base, as well as the position of the left and right feet. In addition, we incorporated IMU biases as concatenated states within the filter.The prediction step of the RIEKF utilizes IMU equations, while the update step incorporates forward kinematics. To evaluate the performance of the RIEKF, we conducted experiments using the Choreonoid dynamic simulation framework and compared it against a Quaternion-based Extended Kalman Filter (QEKF). The results of the analysis demonstrate that the RIEKF exhibits reduced drift in localization and achieves estimation convergence in a shorter time compared to the QEKF. These findings highlight the effectiveness of the proposed RIEKF for accurate state estimation of the kinematic base in humanoid robotics.
Simple Hierarchical Planning with Diffusion

Diffusion-based generative methods have proven effective in modeling trajectories with offline datasets. However, they often face computational challenges and can falter in generalization, especially in capturing temporal abstractions for long-horizon tasks. To overcome this, we introduce the Hierarchical Diffuser, a simple, fast, yet surprisingly effective planning method combining the advantages of hierarchical and diffusion-based planning. Our model adopts a"jumpy"planning strategy at the higher level, which allows it to have a larger receptive field but at a lower computational cost -- a crucial factor for diffusion-based planning methods, as we have empirically verified. Additionally, the jumpy sub-goals guide our low-level planner, facilitating a fine-tuning stage and further improving our approach's effectiveness. We conducted empirical evaluations on standard offline reinforcement learning benchmarks, demonstrating our method's superior performance and efficiency in terms of training and planning speed compared to the non-hierarchical Diffuser as well as other hierarchical planning methods. Moreover, we explore our model's generalization capability, particularly on how our method improves generalization capabilities on compositional out-of-distribution tasks.
Neuronal Auditory Machine Intelligence (NEURO-AMI) In Perspective

The recent developments in soft computing cannot be complete without noting the contributions of artificial neural machine learning systems that draw inspiration from real cortical tissue or processes that occur in human brain. The universal approximability of such neural systems has led to its wide spread use, and novel developments in this evolving technology has shown that there is a bright future for such Artificial Intelligent (AI) techniques in the soft computing field. Indeed, the proliferation of large and very deep networks of artificial neural systems and the corresponding enhancement and development of neural machine learning algorithms have contributed immensely to the development of the modern field of Deep Learning as may be found in the well documented research works of Lecun, Bengio and Hinton. However, the key requirements of end user affordability in addition to reduced complexity and reduced data learning size requirement means there still remains a need for the synthesis of more cost-efficient and less data-hungry artificial neural systems. In this report, we present an overview of a new competing bio-inspired continual learning neural tool Neuronal Auditory Machine Intelligence (Neuro-AMI) as a predictor detailing its functional and structural details, important aspects on right applicability, some recent application use cases and future research directions for current and prospective machine learning experts and data scientists.
A Community Detection and Graph Neural Network Based Link Prediction Approach for Scientific Literature

This study presents a novel approach that synergizes community detection algorithms with various Graph Neural Network (GNN) models to bolster link prediction in scientific literature networks. By integrating the Louvain community detection algorithm into our GNN frameworks, we consistently enhanced the performance across all models tested. For example, integrating the Louvain model with the GAT model resulted in an AUC score increase from 0.777 to 0.823, exemplifying the typical improvements observed. Similar gains were noted when the Louvain model was paired with other GNN architectures, confirming the robustness and effectiveness of incorporating community-level insights. This consistent increase in performance—reflected in our extensive experimentation on bipartite graphs of scientific collaborations and citations—highlights the synergistic potential of combining community detection with GNNs to overcome common link prediction challenges such as scalability and resolution limits. Our findings advocate for the integration of community structures as a significant step forward in the predictive accuracy of network science models, offering a comprehensive understanding of scientific collaboration patterns through the lens of advanced machine learning techniques.
Denoising Vision Transformers

We delve into a nuanced but significant challenge inherent to Vision Transformers (ViTs): feature maps of these models exhibit grid-like artifacts, which detrimentally hurt the performance of ViTs in downstream tasks. Our investigations trace this fundamental issue down to the positional embeddings at the input stage. To address this, we propose a novel noise model, which is universally applicable to all ViTs. Specifically, the noise model dissects ViT outputs into three components: a semantics term free from noise artifacts and two artifact-related terms that are conditioned on pixel locations. Such a decomposition is achieved by enforcing cross-view feature consistency with neural fields in a per-image basis. This per-image optimization process extracts artifact-free features from raw ViT outputs, providing clean features for offline applications. Expanding the scope of our solution to support online functionality, we introduce a learnable denoiser to predict artifact-free features directly from unprocessed ViT outputs, which shows remarkable generalization capabilities to novel data without the need for per-image optimization. Our two-stage approach, termed Denoising Vision Transformers (DVT), does not require re-training existing pre-trained ViTs and is immediately applicable to any Transformer-based architecture. We evaluate our method on a variety of representative ViTs (DINO, MAE, DeiT-III, EVA02, CLIP, DINOv2, DINOv2-reg). Extensive evaluations demonstrate that our DVT consistently and significantly improves existing state-of-the-art general-purpose models in semantic and geometric tasks across multiple datasets (e.g., +3.84 mIoU). We hope our study will encourage a re-evaluation of ViT design, especially regarding the naive use of positional embeddings.
Application of low molecular peptide-based biomarkers for the rapid identification of Echinochloa species

The objective of the present study was to determine the low molecular peptides in Echinochloa seeds as biomarkers for classification. Some peptide-based biomarkers for the classification of Echinochloa species were identified using SELDI-TOF, a mass spectrometry (MS) technique. Proteomic profiling using SELDI-TOF MS techniques could be a useful and powerful tool to discover peptide biomarkers and to discriminate and classify Echinochloa species, especially under 20 kDa. In 12 Echinochloa species, a total of 72 peptides were significantly detected on strong anion exchanger (CM10) and weak cation exchanger (Q10) arrays. Sixteen peptides on CM10 and 12 peptides on Q10 were selected as peptide biomarkers. The hierarchical heat map analysis of the peptide-based biomarkers indicated that Echinochloa species were classified into two groups and then more precisely subdivided. One major cluster group included early barnyard grass (ECOR), large barnyard grass (ECREC), jungle ricegrass (ECOLON), meadow barnyard grass (EPRAT), and barnyard grass (ECHCG). Hairless barnyard grass (ECGL), cockspur (ECRCR), awned billion-dollar grass (ECFRAW), awnless billion-dollar grass (ECFRAWL), awnless barnyard grass (EMITIS), awnless Japanese barnyard millet (EESCAWL), and awned Japanese barnyard millet (EESCAW) belonged to the other group.