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Machine learning (ML) has become increasingly prevalent in various domains. However, ML algorithms sometimes give unfair outcomes and discrimination against certain groups. Thereby, bias occurs when our results produce a decision that is systematically incorrect. At various phases of the ML pipeline, such as data collection, pre-processing, model selection, and evaluation, these biases appear. Bias reduction methods for ML have been suggested using a variety of techniques. By changing the data or the model itself, adding more fairness constraints, or both, these methods try to lessen bias. The best technique relies on the particular context and application because each technique has advantages and disadvantages. Therefore, in this paper, we present a comprehensive survey of bias mitigation techniques in machine learning (ML) with a focus on in-depth exploration of methods, including adversarial training. We examine the diverse types of bias that can afflict ML systems, elucidate current research trends, and address future challenges. Our discussion encompasses a detailed analysis of pre-processing, in-processing, and post-processing methods, including their respective pros and cons. Moreover, we go beyond qualitative assessments by quantifying the strategies for bias reduction and providing empirical evidence and performance metrics. This paper serves as an invaluable resource for researchers, practitioners, and policymakers seeking to navigate the intricate landscape of bias in ML, offering both a profound understanding of the issue and actionable insights for responsible and effective bias mitigation.

The COVID-19 pandemic requires the rapid isolation of infected patients. Thus, high-sensitivity radiology images could be a key technique to diagnose patients besides the polymerase chain reaction approach. Deep learning algorithms are proposed in several studies to detect COVID-19 symptoms due to the success in chest radiography image classification, cost efficiency, lack of expert radiologists, and the need for faster processing in the pandemic area. Most of the promising algorithms proposed in different studies are based on pre-trained deep learning models. Such open-source models and lack of variation in the radiology image-capturing environment make the diagnosis system vulnerable to adversarial attacks such as fast gradient sign method (FGSM) attack. This study therefore explored the potential vulnerability of pre-trained convolutional neural network algorithms to the FGSM attack in terms of two frequently used models, VGG16 and Inception-v3. Firstly, we developed two transfer learning models for X-ray and CT image-based COVID-19 classification and analyzed the performance extensively in terms of accuracy, precision, recall, and AUC. Secondly, our study illustrates that misclassification can occur with a very minor perturbation magnitude, such as 0.009 and 0.003 for the FGSM attack in these models for X-ray and CT images, respectively, without any effect on the visual perceptibility of the perturbation. In addition, we demonstrated that successful FGSM attack can decrease the classification performance to 16.67% and 55.56% for X-ray images, as well as 36% and 40% in the case of CT images for VGG16 and Inception-v3, respectively, without any human-recognizable perturbation effects in the adversarial images. Finally, we analyzed that correct class probability of any test image which is supposed to be 1, can drop for both considered models and with increased perturbation; it can drop to 0.24 and 0.17 for the VGG16 model in cases of X-ray and CT images, respectively. Thus, despite the need for data sharing and automated diagnosis, practical deployment of such program requires more robustness.

Artisanal and Small-Scale Gold Mining (ASGM) is a low-cost yet highly destructive mining practice, leading to environmental disasters across the world's tropical watersheds. The topic of ASGM spans multiple domains of research and information, including natural and social systems, and knowledge is often atomized across a diversity of media and documents. We therefore introduce a knowledge graph (ASGM-KG) that consolidates and provides crucial information about ASGM practices and their environmental effects. The current version of ASGM-KG consists of 1,899 triples extracted using a large language model (LLM) from documents and reports published by both non-governmental and governmental organizations. These documents were carefully selected by a group of tropical ecologists with expertise in ASGM. This knowledge graph was validated using two methods. First, a small team of ASGM experts reviewed and labeled triples as factual or non-factual. Second, we devised and applied an automated factual reduction framework that relies on a search engine and an LLM for labeling triples. Our framework performs as well as five baselines on a publicly available knowledge graph and achieves over 90 accuracy on our ASGM-KG validated by domain experts. ASGM-KG demonstrates an advancement in knowledge aggregation and representation for complex, interdisciplinary environmental crises such as ASGM.

The ongoing pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates strategies to identify prophylactic and therapeutic drug candidates for rapid clinical deployment. Here, we describe a screening pipeline for the discovery of efficacious SARS-CoV-2 inhibitors. We screen a best-in-class drug repurposing library, ReFRAME, against two high-throughput, high-content imaging infection assays: one using HeLa cells expressing SARS-CoV-2 receptor ACE2 and the other using lung epithelial Calu-3 cells. From nearly 12,000 compounds, we identify 49 (in HeLa-ACE2) and 41 (in Calu-3) compounds capable of selectively inhibiting SARS-CoV-2 replication. Notably, most screen hits are cell-line specific, likely due to different virus entry mechanisms or host cell-specific sensitivities to modulators. Among these promising hits, the antivirals nelfinavir and the parent of prodrug MK-4482 possess desirable in vitro activity, pharmacokinetic and human safety profiles, and both reduce SARS-CoV-2 replication in an orthogonal human differentiated primary cell model. Furthermore, MK-4482 effectively blocks SARS-CoV-2 infection in a hamster model. Overall, we identify direct-acting antivirals as the most promising compounds for drug repurposing, additional compounds that may have value in combination therapies, and tool compounds for identification of viral host cell targets. Here, the authors perform repurposing screens of the ReFRAME drug library in two cell lines and identify inhibitors of SARS-CoV-2 infection. Antiviral activity of prodrug MK-4482 is confirmed in hamsters.

An intriguing DABCO-catalyzed and DBU-promoted one-pot synthesis of an important class of (2-hydroxyaryl)pyridine derivatives bearing a carboxylate or a nitrile group suitably placed at C3 position of the aza-ring has been achieved in acceptable chemical yields with a broad functional group tolerance. This sequential C–C/C–N bond making process proceeds through a regioselective allylic alkylation/aza-Michael reaction between MBH carbonates derived from an acrylate/acrylonitrile and N -sulfonyl ketimines as C,N-binucleophiles catalyzed by DABCO, followed by elimination of SO 2 under the influence of base and subsequent aromatization in an open atmosphere.

Immune checkpoint blockade therapy has shown promising results in patients with advanced hepatocellular carcinoma. We aimed to assess the efficacy and safety of pembrolizumab in this patient population. KEYNOTE-224 is a non-randomised, multicentre, open-label, phase 2 trial that is set in 47 medical centres and hospitals across ten countries. Eligible patients had pathologically confirmed hepatocellular carcinoma; had previously been treated with sorafenib and were either intolerant to this treatment or showed radiographic progression of their disease after treatment; an Eastern Cooperative Oncology Group performance status of 0–1; adequate organ function, and were Child-Pugh class A. Participants received 200 mg pembrolizumab intravenously every 3 weeks for about 2 years or until disease progression, unacceptable toxicity, patient withdrawal, or investigator decision. The primary endpoint was objective response, defined as the proportion of patients with complete or partial response in all patients who received at least one dose of pembrolizumab, which was radiologically confirmed by use of the Response Evaluation Criteria in Solid Tumors version 1.1 by central review. Safety was also assessed in all treated patients. This trial is ongoing but closed to enrolment and is registered with ClinicalTrials.gov number NCT02702414. Between June 7, 2016, and Feb 9, 2017, we screened 169 patients with advanced hepatocellular carcinoma, of whom 104 eligible patients were enrolled and treated. As of data cutoff on Feb 13, 2018, 17 (16%) patients were still receiving pembrolizumab. We recorded an objective response in 18 (17%; 95% CI 11–26) of 104 patients. The best overall responses were one (1%) complete and 17 (16%) partial responses; meanwhile, 46 (44%) patients had stable disease, 34 (33%) had progressive disease, and six (6%) patients who did not have a post-baseline assessment on the cutoff date were considered not to be assessable. Treatment-related adverse events occurred in 76 (73%) of 104 patients, which were serious in 16 (15%) patients. Grade 3 treatment-related events were reported in 25 (24%) of the 104 patients; the most common were increased aspartate aminotransferase concentration in seven (7%) patients, increased alanine aminotransferase concentration in four (4%) patients, and fatigue in four (4%) patients. One (1%) grade 4 treatment-related event of hyperbilirubinaemia occurred. One death associated with ulcerative oesophagitis was attributed to treatment. Immune-mediated hepatitis occurred in three (3%) patients, but there were no reported cases of viral flares. Pembrolizumab was effective and tolerable in patients with advanced hepatocellular carcinoma who had previously been treated with sorafenib. These results indicate that pembrolizumab might be a treatment option for these patients. This drug is undergoing further assessment in two phase 3, randomised trials as a second-line treatment in patients with hepatocellular carcinoma. Merck & Co, Inc.

The myo‐inositol‐1‐phosphate synthase (MIPS) catalyses the biosynthesis of myo‐inositol, an important sugar that regulates various physiological and biochemical processes in plants. Here, we provide evidence that host (SlMIPS1) and pathogen (Rs_MIPS) myo‐inositol‐1‐phosphate synthase (MIPS) genes are required for successful infection of Rhizoctonia solani, a devastating necrotrophic fungal pathogen, in tomato. Silencing of either SlMIPS1 or Rs_MIPS prevented disease, whereas an exogenous spray of myo‐inositol enhanced disease severity. SlMIPS1 was upregulated upon R. solani infection, and potentially promoted source‐to‐sink transition, induced SWEET gene expression, and facilitated sugar availability in the infected tissues. In addition, salicylic acid (SA)‐jasmonic acid homeostasis was altered and SA‐mediated defence was suppressed; therefore, disease was promoted. On the other hand, silencing of SlMIPS1 limited sugar availability and induced SA‐mediated defence to prevent R. solani infection. Virus‐induced gene silencing of NPR1, a key gene in SA signalling, rendered SlMIPS1‐silenced tomato lines susceptible to infection. These analyses suggest that induction of SA‐mediated defence imparts disease tolerance in SlMIPS1‐silenced tomato lines. In addition, we present evidence that SlMIPS1 and SA negatively regulate each other to modulate the defence response. SA treatment reduced SlMIPS1 expression and myo‐inositol content in tomato, whereas myo‐inositol treatment prevented SA‐mediated defence. We emphasize that downregulation of host/pathogen MIPS can be an important strategy for controlling diseases caused by R. solani in agriculturally important crops. Rhizoctonia solani infection upregulates myo‐inositol‐1‐phosphate synthase (MIPS) to suppress salicylic acid‐mediated defence and enhance sugar availability whereas silencing of MIPS enhances disease tolerance.

Inorganic nanoparticles (NPs) have played an important role as nano-drug delivery systems during cancer therapy in recent years. These NPs can carry cancer therapeutic agents. Due to this, they are considered a promising ancillary to traditional cancer therapies. Among inorganic NPs, Zinc Oxide (ZnO) NPs have been extensively utilized in cellular imaging, gene/drug delivery, anti-microbial, and anti-cancerous applications. In this study, a rapid and cost-effective method was used to synthesize Nat -ZnO NPs using the floral extract of the Nyctanthes arbor-tristis (Nat) plant. Nat -ZnO NPs were physicochemically characterized and tested further on in vitro cancer models. The average hydrodynamic diameter ( Z average ) and the net surface charge of Nat -ZnO NPs were 372.5 ± 70.38 d.nm and −7.03 ± 0.55 mV, respectively. Nat -ZnO NPs exhibited a crystalline nature. HR-TEM analysis showed the triangular shape of NPs. Furthermore, Nat -ZnO NPs were also found to be biocompatible and hemocompatible when tested on mouse fibroblast cells and RBCs. Later, the anti-cancer activity of Nat -ZnO NPs was tested on lung and cervical cancer cells. These NPs displayed potent anti-cancer activity and induced programmed cell death in cancer cells.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder characterised by widespread inflammation affecting multiple organ systems. Its varied clinical manifestations often complicate diagnosis, as it can closely mimic other conditions, particularly infectious diseases such as tuberculosis. This case report describes a woman in her early 20s initially suspected of having disseminated tuberculosis and treated accordingly due to overlapping symptoms, including fever, night sweats, lymphadenopathy and bilateral exudative pleural effusion. Subsequent evaluation, however, confirmed a diagnosis of SLE based on clinical criteria and positive autoantibody results. The patient also presented with anaemia of chronic disease and elevated inflammatory markers. This case highlights the diagnostic difficulty of differentiating SLE from tuberculosis, particularly in regions with high tuberculosis prevalence. Comprehensive physical examination, thorough evaluation and consideration of autoimmune disorders are essential in such cases to ensure accurate diagnosis, guide appropriate treatment and prevent severe complications.

Metal/Metal Oxide nanoparticles (M/MO NPs) exhibit potential biomedical applications due to their tunable physicochemical properties. Recently, the biogenic synthesis of M/MO NPs has gained massive attention due to their economical and eco-friendly nature. In the present study, Nyctanthes arbor-tristis ( Nat ) flower extract-derived Zinc Ferrite NPs ( Nat -ZnFe 2 O 4 NPs) were synthesized and physicochemically characterized by FTIR, XRD, FE-SEM, DLS, and other instruments to study their crystallinity, size, shape, net charge, presence of phytocompounds on NP’s surface and several other features. The average particle size of Nat -ZnFe 2 O 4 NPs was approx. 25.87 ± 5.67 nm. XRD results showed the crystalline nature of Nat -ZnFe 2 O 4 NPs. The net surface charge on NPs was -13.28 ± 7.18 mV. When tested on mouse fibroblasts and human RBCs, these NPs were biocompatible and hemocompatible. Later, these Nat -ZnFe 2 O 4 NPs exhibited potent anti-neoplastic activity against pancreatic, lung, and cervical cancer cells. In addition, NPs induced apoptosis in tested cancer cells through ROS generation. These in vitro studies confirmed that Nat -ZnFe 2 O 4 NPs could be used for cancer therapy. Moreover, further studies are recommended on ex vivo platforms for future clinical applications.