Search

Abstract Filamentous Fungal Human Pathogens (FFHPs) such as Aspergillus fumigatus, are growing resistant to currently available antifungal drugs. One possible target, the Nucleoside diphosphate kinase (Ndk) is significant for nucleotide biosynthesis and crucial for fungal metabolism. Violacein, a natural food colorant, was examined for its antifungal effects against Aspergillus fumigatus via computational approach against the Ndk protein. Known and predicted interactions of Ndk with proteins was performed using the STRING application. Molecular docking was performed using Schrodinger Maestro software (V.14.1) under enhanced precision docking, with OPLS4 forcefield. MDS was performed for 500ns under OPLS4 forcefield and the TIP3P solvent system. The geometry optimization for DFT was performed using the Becke 3-parameter exchange functional (B3LYP) method. The Molecular Docking Studies revealed significant interactions with good binding energy between Violacein and Ndk. Subsequent MD Simulations confirmed the stability of Violacein-Ndk complex, compared to the reference ligand-complex, indicating a stable interaction between the protein and violacein. The energy band gap of violacein was found to be 0.072567 eV suggesting its softness with lower kinetic stability and higher chemical reactivity. The results suggest Violacein could potentially disrupt nucleotide metabolism by targeting Ndk, thus demonstrating antifungal activity. However, further experimental validation is required to confirm these computational findings and explore the practical use of Violacein in antifungal treatments.

Abstract Tissue nanotransfection (TNT) topically delivers Etv2, Foxc2, and Fli1 (EFF) plasmids increasing vasculogenic fibroblasts (VF) and promoting vascularization in ischemic murine skin. Human dermal fibroblasts respond to EFF nanoelectroporation with elevated expression of endothelial genes in vitro, which is linked to increased ten-eleven translocase 1/2/3 (TET) expression. Single cell RNA sequencing dependent validation of VF induction reveals a TET-dependent transcript signature. TNTEFF also induces TET expression in vivo, and fibroblast-specific EFF overexpression leads to VF-transition, with TET-activation correlating with higher 5-hydroxymethylcytosine (5-hmC) levels in VF. VF emergence requires TET-dependent demethylation of endothelial genes in vivo, enhancing VF abundance and restoring perfusion in diabetic ischemic limbs. TNTEFF improves perfusion and wound closure in diabetic mice, while increasing VF in cultured human skin explants. Suppressed in diabetes, TET1/2/3 play a critical role in TNT-mediated VF formation which supports de novo blood vessel development to rescue diabetic ischemic tissue.

Abstract Background Swellings of the neck are a common presentation encountered by surgeons in outpatient settings, often prompting early medical attention due to their visibility and potential cosmetic concerns. Neck masses can range from reactive lymphadenitis to malignant lesions. Aim of the study This observational study aimed to investigate the clinical profile and etiopathology of neck masses within the Indian population. Methods Over a six-month period, patients presenting with neck swellings at the Department of ENT in a multi-speciality government hospital, Delhi, were included. 100 patients were included in the study. Detailed demographic data and presenting symptoms were recorded, along with local examination findings and cytological analysis using fine needle aspiration cytology (FNAC). Results The study population predominantly consisted of individuals aged 21 to 30 (30%) and 11 to 20 (22%), with females comprising 68% of the total, male to female ratio being 0.6:1. The most common etiologies observed were infective or inflammatory (42%), followed by thyroid-related conditions (35%). Tubercular lymphadenitis was the most common among infective etiology, accounting for 36% of these cases. Notable variations were observed across age groups, with younger demographics showing higher prevalence of benign and inflammatory conditions, while older individuals presented with diverse etiologies including thyroid nodules and salivary gland tumors. Conclusion The age distribution data of patients presenting with neck masses provides valuable insights into the epidemiology and etiology of such conditions across different age groups. FNAC remains a valuable and cost-effective diagnostic tool for evaluating superficial and deep-seated lesions in the head and neck region. It offers reliable categorization of lesions due to its high sensitivity and specificity.

Abstract Prototype-based methods in deep learning offer interpretable explanations for decisions by comparing inputs to typical representatives in the data. This study explores the adaptation of SESM, a self-attention-based prototype method successful in electrocardiogram (ECG) tasks, for electroencephalogram (EEG) signals. The architecture is evaluated on sleep stage classification, exploring its efficacy in predicting stages with single-channel EEG. The model achieves comparable test accuracy compared to EEGNet, a state-of-the-art black-box architecture for EEG classification. The generated prototypical components are exaimed qualitatively and using the area over the perterbation curve (AOPC) indicate some alignment with expected bio-markers for different sleep stages such as alpha spindles and slow waves in non-REM sleep, but the results are severely limited by the model’s ability to only extract and present information in the time-domain. Ablation studies are used to explore the impact of kernel size, number of heads, and diversity threshold on model performance and explainability. This study represents the first application of a self-attention based prototype method to EEG data and provides a step forward in explainable AI for EEG data analysis.

Abstract Ventricular arrhythmias after myocardial infarction (MI) originate from discrete areas within the MI border zone (BZ), identified during functional electrophysiology tests. Accurate sampling of arrhythmogenic sites for ex-vivo study remains challenging, yet is critical to identify their tissue, cellular and molecular signature. In this study, we developed, validated, and applied a targeted sampling methodology based on individualized 3D prints of the human-sized pig heart. To this end, 3D anatomical models of the left ventricle were created from magnetic resonance imaging and fused with biplane fluoroscopy. Regions of interest for sampling were annotated on the anatomical models, from which we created a unique 3D printed cast with custom slits identifying the annotated regions for sampling. The methodology was validated by retrieving ablation lesions created at predefined locations on the anatomical model. We applied the methodology to sample arrhythmia-vulnerable regions after MI during adrenergic stimulation. A pipeline of imaging was developed to create a 3D high-resolution map of each sample, highlighting the complex interplay of cellular organization, and altered innervation in the BZ.

Abstract The theory of ion-acoustic solitons in nonrelativistic fully degenerate plasmas and nonrelativistic and ultra-relativistic degenerate plasmas at low temperatures is known. We consider a multi-component relativistic degenerate electron-positron-ion plasma at finite temperatures. Specifically, we focus on the intermediate region where the particle’s thermal energy $$(k_BT)$$ ( k B T ) and the rest mass energy $$(mc^2)$$ ( m c 2 ) do not differ significantly, i.e., $$k_BT\sim mc^2$$ k B T ∼ m c 2 . However, the Fermi energy $$(k_BT_F)$$ ( k B T F ) is larger than the thermal energy and the normalized chemical energy ( $$\xi =\mu /k_BT$$ ξ = μ / k B T ) is positive and finite. Two different parameter regimes with $$\beta \equiv k_BT/mc^21$$ β > 1 , relevant for astrophysical plasmas, are defined, and the existence of small amplitude ion-acoustic solitons in these regimes are studied, including the critical cases where the known KdV (Korteweg–de Vries) theory fails. We show that while the solitons with both the positive (compressive) and negative (rarefactive) potentials coexist in the case of $$\beta 1)$$ ( β > 1 ) . Furthermore, while the rarefactive solitons within the parameter domains of $$\beta$$ β and $$\xi$$ ξ can evolve with increasing amplitude and hence increasing energy, the energy of compressive solitons reaches a steady state.

Abstract Psoriasis, being a chronic, inflammatory, lifelong skin disorder, has become a major threat to the human population. The precise and effective diagnosis of psoriasis continues to be difficult for clinicians due to its varied nature. In northern India, the prevalence of psoriasis among adult population ranges from 0.44 to 2.8%. Chronic plaque psoriasis accounts for over 90% of cases. This study utilized a dataset of 325 raw images collected from a reputable local hospital using a digital camera under uniform lighting conditions. These images were processed to generate 496 image patches (both diseased and normal), which were then normalized and resized for model training. An automated psoriasis image recognition framework was developed using four state-of-the-art deep transfer learning models: VGG16, VGG19, MobileNetV1, and ResNet-50. The convolutional layers adopted various edge, shape, and color filters to generate the feature map for psoriasis detection. Each pre-trained model was adapted with two dense layers, one dropout layer, and one output layer to classify input images. Among these models, MobileNetV1 achieved the best performance, with 94.84% sensitivity, 89.37% specificity, and 97.24% overall accuracy. Hyper-parameter tuning was performed using grid search to optimize learning rates, batch sizes, and dropout rates. The AdaGrad (Adaptive gradient)) optimizer was chosen for its adaptive learning rate capabilities, facilitating quicker convergence in model performance. Consequently, the methodology’s performance improved to 94.25% sensitivity, 96.42% specificity, and 99.13% overall accuracy. The model’s performance was also compared with non-machine learning-based diagnostic methods, yielding a Dice coefficient of 0.98. However, the model’s effectiveness is dependent upon high-quality input images, as poor image conditions may affect accuracy, and it may not generalize well across diverse demographics or psoriasis variations, highlighting the need for varied training datasets for robustness.

Abstract Widely prescribed for Attention-Deficit/Hyperactivity Disorder (ADHD), stimulants (e.g., methylphenidate) have been studied for their chronic effects on the brain in prospective designs controlling dosage and adherence. While controlled approaches are essential, they do not approximate real-world stimulant exposure contexts where medication interruptions, dosage non-compliance, and polypharmacy are common. Brain changes in real-world conditions are largely unexplored. To fill this gap, we capitalized on the observational design of the Adolescent Brain Cognitive Development (ABCD) study to examine effects of stimulants on large-scale bilateral cortical networks’ resting-state functional connectivity (rs-FC) with 6 striatal regions (left and right caudate, putamen, and nucleus accumbens) across two years in children with ADHD. Bayesian hierarchical regressions revealed associations between stimulant exposure and change in rs-FC of multiple striatal-cortical networks, affiliated with executive and visuo-motor control, which were not driven by general psychotropic medication. Of these connections, three were selective to stimulants versus stimulant naive: reduced rs-FC between caudate and frontoparietal network, and between putamen and frontoparietal and visual networks. Comparison with typically developing children in the ABCD sample revealed stronger rs-FC reduction in stimulant-exposed children for putamen and frontoparietal and visual networks, suggesting a normalizing effect of stimulants. 14% of stimulant-exposed children demonstrated reliable reduction in ADHD symptoms, and were distinguished by stronger rs-FC reduction between right putamen and visual network. Thus, stimulant exposure for a two-year period under real-world conditions modulated striatal-cortical functional networks broadly, had a normalizing effect on a subset of networks, and was associated with potential therapeutic effects involving visual attentional control.

Abstract The PIM kinase family, consisting of PIM1, PIM2, and PIM3, is a group of serine/threonine protein kinases crucial for cellular growth, immunoregulation, and oncogenesis. PIM1 kinase is often overexpressed in solid and hematopoietic malignancies, promoting cell survival, proliferation, migration, and senescence by activating key genes. In vitro and in vivo studies have established the oncogenic potential of PIM1 kinases. These kinases have been implicated in tumor progression, metastasis, and resistance to chemotherapy, underscoring their potential as a therapeutic target for cancer therapy. This review delves into the intricate molecular mechanisms through which PIM1 interacts with specific substrates in different tumor tissues, leading to diverse outcomes in various human cancers. Over the past decade, the inhibition of PIM1 in cancers has garnered significant attention as a potential standalone treatment. Various in vitro, in vivo, and early clinical trial data have provided support for this approach to varying extents. Novel compounds that inhibit PIM1 kinase have shown effectiveness and a favorable toxicity profile in preclinical studies. Several of these substances are now being studied in clinical trials due to their promising outcomes. This article provides a thorough examination of the PIM1 kinase pathways and the recent advancements in producing PIM1 kinase inhibitors for the treatment of cancer.

Adenovirus (Ad), a common virus, can cause a variety of symptoms such as respiratory issues, fever, and occasionally neurological problems. Transverse Myelitis (TM) is defined as a neurological disorder marked by inflammation of a section of the spinal cord which further damages the myelin sheath surrounding the nerve fibers. This can result in a variety of symptoms, including general weakness, sensory changes, pain and difficulties with bowel and bladder control. Ad causing TM is a topic of great significance in the field of medicine as it involves a rare yet serious condition. Hereby the case report of a 64-year-old female who presented to the Emergency Room with fever and bilateral lower limb weakness and was diagnosed with TM, with the Cerebrospinal Fluid (CSF) report Polymerase Chain Reaction (PCR) showing Ad. The patient was treated with plasmapheresis, antivirals, steroids and physiotherapy. The present case emphasises that timely diagnosis and identification of the underlying cause of TM are essential to prevent respiratory paralysis and other complications. It is also important to exclude other autoimmune conditions, as well as, bacterial and fungal infections, in every patient.

We present a case of a patient with Bernard–Soulier syndrome (BSS) who had his impacted third mandibular molar surgically extracted. An uncommon congenital bleeding condition called BSS is inherited in an autosomal recessive fashion. The syndrome, which has an incidence of fewer than 1 in 1,000,000, is characterized by delayed bleeding time, thrombocytopenia, and abnormally large platelets. Even simple surgical procedures become difficult in these patients due to their increased propensity for bleeding. There are no established standards for the management of perioperative bleeding linked to BSS because the condition is uncommon. The regular management of these bleeding episodes involves the delivery of platelets matched to the patient’s human leukocyte antigen, which carries certain challenges. We explain the treatment plan used for a patient with BSS whose impacted third molar was successfully extracted surgically.

Abstract Characterization of a productive oil/gas well blowout through seismological methods is relatively uncommon. In this paper, we conduct an in-depth seismic evaluation of one of the world’s most significant onshore oil well blowout incidents, which occurred in 2020 at the Baghjan oil field in Assam, northeast India. We show that the blowout and related on-site activities generated distinct signals that can be distinguished by their spectral characteristics, temporal variation in geometric spreading, and sharp attenuation of daytime noise in comparison to the nighttime. A micro-earthquake potentially triggered by the blowout was also detected. Furthermore, we show how seismic data can be used to reasonably estimate blowout gas exit velocity and flame height. Our results demonstrate that a detailed characterization and spatiotemporal variation of blowout activity can be successfully captured through seismic monitoring, opening new opportunities for hazard mitigation and cost-effective disaster management for such catastrophic events.

Abstract An extraordinary resolution down to 50 microns is demonstrated for the first time for bulk ultrasonics, using novel micro-fabricated metamaterial lenses. The development and performance of the silicon-based Fabry–Perot type metalenses with an array of 10 micrometre square holes are discussed. Challenges in wave reception are addressed by a custom-developed micro-focal laser with a sub-micron spot size and an innovative experimental set-up together with physics based signal processing. The results provide a pathway for material diagnostics at greater depths with high resolution using micro-metalens-enhanced ultrasound as an alternative to expensive and radiation prone electromagnetic techniques.

Abstract A single-center, prospective, observational pilot study was performed to evaluate wound healing endpoint and recurrence by measuring transepidermal water loss (TEWL) post-closure at the site of wound repair. Patients with clinically-defined chronic wounds (such as pressure ulcers, diabetic ulcers, and trauma wounds) who visited the Plastic Surgery outpatient department or were in-patients at the All India Institute of Medical Sciences, Rishikesh, India, and were referred for chronic wound management, were enrolled. Non-invasive point-of-care TEWL measurements were obtained, from closed wound-site and contralateral healthy skin site, starting from confirmation of closure (post-closure, V0) continuing every 2 weeks for a maximum of five visits or until the wound recurred. Statistical analyses of the data involved logistic regression and likelihood ratio chi-square tests to assess differences in TEWL at visit 0 (V0) between the closed wound site and reference skin, with the TEWL score as the sole predictor of recurrence. Of the 72 subjects that completed the study, 44 (61%) showed no recurrence and 28 (39%) had wounds that recurred over a period of 12 weeks. A significant association was found between the V0 (post-closure) TEWL score and the odds of wound recurrence, both in univariate analysis (OR [95%CI] = 1.26[1.14,1.42] (p

Abstract In the era of renewed space exploration, comprehending the effects of the space environment on human health, particularly for deep space missions, is crucial. While extensive research exists on the impacts of spaceflight, there is a gap regarding female reproductive risks. We hypothesize that space stressors could have enduring effects on female health, potentially increasing risks for future pregnancies upon return to Earth, particularly related to small-for-gestational-age (SGA) fetuses. To address this, we identify a shared microRNA (miRNA) signature between SGA and the space environment, conserved across humans and mice. These miRNAs target genes and pathways relevant to diseases and development. Employing a machine learning approach, we identify potential FDA-approved drugs to mitigate these risks, including estrogen and progesterone receptor antagonists, vitamin D receptor antagonists, and DNA polymerase inhibitors. This study underscores potential pregnancy-related health risks for female astronauts and proposes pharmaceutical interventions to counteract the impact of space travel on female health.

Abstract Emergent phases often appear when the electronic kinetic energy is comparable to the Coulomb interactions. One approach to seek material systems as hosts of such emergent phases is to realize localization of electronic wavefunctions due to the geometric frustration inherent in the crystal structure, resulting in flat electronic bands. Recently, such efforts have found a wide range of exotic phases in the two-dimensional kagome lattice, including magnetic order, time-reversal symmetry breaking charge order, nematicity, and superconductivity. However, the interlayer coupling of the kagome layers disrupts the destructive interference needed to completely quench the kinetic energy. Here we demonstrate that an interwoven kagome network—a pyrochlore lattice—can host a three dimensional (3D) localization of electron wavefunctions. Meanwhile, the nonsymmorphic symmetry of the pyrochlore lattice guarantees all band crossings at the Brillouin zone X point to be 3D gapless Dirac points, which was predicted theoretically but never yet observed experimentally. Through a combination of angle-resolved photoemission spectroscopy, fundamental lattice model and density functional theory calculations, we investigate the novel electronic structure of a Laves phase superconductor with a pyrochlore sublattice, CeRu2. We observe evidence of flat bands originating from the Ce 4f orbitals as well as flat bands from the 3D destructive interference of the Ru 4d orbitals. We further observe the nonsymmorphic symmetry-protected 3D gapless Dirac cone at the X point. Our work establishes the pyrochlore structure as a promising lattice platform to realize and tune novel emergent phases intertwining topology and many-body interactions.

Abstract The nodal-line semiconductor Mn3Si2Te6 is generating enormous excitment due to the recent discovery of a field-driven insulator-to-metal transition and associated colossal magnetoresistance as well as evidence for a new type of quantum state involving chiral orbital currents. Strikingly, these qualities persist even in the absence of traditional Jahn-Teller distortions and double-exchange mechanisms, raising questions about exactly how and why magnetoresistance occurs along with conjecture as to the likely signatures of loop currents. Here, we measured the infrared response of Mn3Si2Te6 across the magnetic ordering and field-induced insulator-to-metal transitions in order to explore colossal magnetoresistance in the absence of Jahn-Teller and double-exchange interactions. Rather than a traditional metal with screened phonons, the field-driven insulator-to-metal transition leads to a weakly metallic state with localized carriers. Our spectral data are fit by a percolation model, providing evidence for electronic inhomogeneity and phase separation. Modeling also reveals a frequency-dependent threshold field for carriers contributing to colossal magnetoresistance which we discuss in terms of polaron formation, chiral orbital currents, and short-range spin fluctuations. These findings enhance the understanding of insulator-to-metal transitions in new settings and open the door to the design of unconventional colossal magnetoresistant materials.

Abstract Due to the advancement in biomedical technologies, to diagnose problems in people, a number of psychological signals are extracted from patients. We should be able to ensure that psychological signals are not altered by adversaries and it should be possible to relate a patient to his/her corresponding psychological signal. As far as our awareness extends, none of the existing methods possess the capability to both identify and verify the authenticity of the ECG signals. Consequently, this paper introduces an innovative dual-layer data-embedding approach for electrocardiogram (ECG) signals, aiming to achieve both signal identification and authenticity verification. Since file name-based signal identification is vulnerable to modifications, we propose a robust watermarking method which will embed patient-related details such as patient identification number, into the medically less-significant portion of the ECG signals. The proposed robust watermarking algorithm adds data into ECG signals such that the patient information hidden in an ECG signal can resist the filtering attack (such as high-pass filtering) and noise addition. This is achieved via the use of error buffers in the embedding algorithm. Further, modification-sensitive fragile watermarks are added to ECG signals. By extracting and checking the fragile watermark bits, we can determine whether an ECG signal is modified or not. To ensure the security of the proposed mechanism, two secret keys are used. Our evaluation demonstrates the usefulness of the proposed system.

Abstract Control over the catalytic activity of artificial catalytic systems in aqueous media is of high interest for biomimetic artificial catalysts. The activity of catalytic systems can be controlled via introducing stimuli-responsive feature in the structure of the catalytic systems. However, temperature, pH or light have been predominantly used as stimulus. Aqueous catalytic system whose activity can be turned ‘ON/OFF’ employing mechanical force has not been demonstrated. Here we show how catalytic activity of an aqueous catalytic system can be switched ‘ON/OFF’ via the application/ceasing ultrasound stimulus. We demonstrate that the accessibility of imidazole, a catalyst moiety, can be modulated via the presence/absence of the ultrasound stimulus, resulting temporal control over the rate of ester hydrolysis reactions in aqueous buffer solution. This generic approach enables using a large range of organocatalysts for the preparation of molecules and/or materials in aqueous media for their application to material science, and in biomedical field.

Introduction: Up to 40% of patients with suspected prostate cancer (PCa) have a negative prebiopsy magnetic resonance imaging (nMRI), and up to 15% of them may have clinically significant PCa (csPCa). The ability to predict the presence of csPCa despite nMRI may help avoid unnecessary biopsies. We aimed to determine the negative predictive value (NPV) of mpMRI, the influence of MRI reporting patterns in clinical practice, and the factors that might predict csPCa among men with an nMRI. Methodology: In an IRB-approved, ambispective study, men who underwent prostate biopsy from 2016 to 2023 and had a prebiopsy MRI, were included to determine the presence of csPCa. The reporting patterns of institutional and noninstitutional MRI were evaluated. Age, digital rectal examination (DRE) findings, prostate specific antigen (PSA), PSA density (PSAD), and MRI reports were evaluated for their ability to predict csPCa in men with nMRI. Results: 1660 patients who underwent prostate biopsy were assessed for eligibility, and 685 patients were enrolled in the study. The median age, PSA and PSAD were 60 years, 11.63 ng/ml and 0.23 ng/ml/cm3, respectively. 62 (9%) men had an nMRI, among which csPCa, non-csPCa, and negative biopsy were found in 34%, 5%, and 61% of men, respectively. 61% had an institutional MRI, while 39% had a noninstitutional MRI. The sensitivity and NPV of any MRI for csPCa were 93% and 66%, respectively, which improved to 96% and 81% for institutional MRI. Univariate and multivariate analyses showed abnormal DRE and PSAD ≥0.25 ng/ml/cc as predictive factors for csPCa in men with an nMRI. Conclusion: 34% of men with negative MRIs were found to harbor csPCa on prostate biopsy. The NPV of institutional MRI was higher than for noninstitutional MRI. Men with an abnormal DRE or PSAD ≥0.25 ng/ml/cc had a higher incidence of csPCa despite an nMRI.

Background: Diabetes mellitus, a multifaceted metabolic disorder with diverse etiologies, has remained a significant global health concern, imposing a substantial burden on healthcare systems. Objectives: This review aims to explore contemporary advancements in diabetes research, shedding light on recent breakthroughs and their potential impact. Methods: A thorough examination of current literature was conducted to identify critical areas in diabetes research. Precision medicine, innovative therapies, biomarker discovery, and technology integration, including artificial intelligence (AI), in diabetes care were investigated to provide a comprehensive overview. Results: The review highlights the emergence of precision medicine as a promising avenue in diabetes research, emphasizing tailored therapeutic approaches based on individual patient characteristics. Innovative therapies, such as gene therapies and advanced pharmacological interventions, present novel strategies for effective diabetes management. Biomarker discovery is a key focus, which helps identify reliable indicators for early diagnosis and personalized treatment strategies. Incorporating technology, including continuous glucose monitoring and insulin delivery systems, reflects a paradigm shift in diabetes care. Conclusion: This review underscores the dynamic landscape of diabetes research, emphasizing the crucial role of precision medicine, innovative therapies, biomarker discovery, and technology integration in shaping future directions. The evolving role of AI in diabetes care signifies a transformative potential for personalized, data-driven interventions. By providing insights into contemporary advancements, this review contributes to the ongoing efforts to develop more effective prevention and management strategies for diabetes, addressing the pressing global health challenge posed by this complex metabolic disorder.

Introduction: Prostate cancer is one of the most prevalent malignancies affecting men globally, with a significant impact on health-related quality of life (HRQOL). With the recent therapeutic advancements and improvements in survival, there is a need to understand the determinants of HRQOL in metastatic prostate cancer patients to optimize treatment strategies for quality of life as the number of survivors increases. The aim of this study was to identify clinical variables that affect HRQOL and its domains in patients with metastatic prostate cancer. Methods: We conducted a cross-sectional questionnaire-based study in patients diagnosed with metastatic prostate cancer at a tertiary cancer center in India. Baseline clinical features, treatment details, and completed Functional Assessment of Cancer Therapy—Prostate (FACT-P), composed of FACT-general (FACT-G) and prostate cancer-specific concerns subscale (PCS) and FACT-P Trial Outcome Index (FACT-P TOI) questionnaires, were collected. The mean total, as well as individual domain scores, were calculated. Additionally, these were stratified by the current treatment being received by patients. Linear regression was used to identify independent factors affecting HRQOL in these patients. Results: Of the 106 enrolled patients, 84 completed the FACT-P questionnaire and were included in the analysis. The median age was 66 years, and at the time of assessment, 3 patients (3.6%) were receiving androgen deprivation therapy only, 53 patients (63.1%) were on ADT + androgen receptor-targeted agents (ARTAs), and 18 patients (21.4%) patients received ADT + chemotherapy. The mean (±standard deviation) of the FACT-P TOI score was 70.33 (±15.16); the PCS subscale was the most affected, followed by functional well-being. Patients on chemotherapy scored significantly higher on PCS, but the composite scores were not significantly different. Univariable regression identified obesity (body mass index > 25 kg/m2) and duration of first-line treatment as significant predictors of better HRQOL; however, obesity was the only independent predictor in multivariable analysis (β = 8.2; 95% confidence interval, 1.2 to 15.0; p = 0.022). Obesity also independently predicted a better FACT-P and its physical well-being domain score and PCS. Conclusion: Prostate cancer patients experience impaired QoL, especially in the prostate cancer-specific and functional well-being domains. Lower BMI is an independent predictor of poor QoL, and this requires efforts to assess the impact of strategies to manage the nutritional status of patients with metastatic disease on QoL outcomes.

The authors have investigated the axisymmetric and three-dimensional, steady, incompressible, and bioconvective flow of Ag-TiO2/water hybrid nanofluid between two infinite and parallel rotating disks. Practical uses of flows between two rotating disks include brake systems in vehicles, engines, disks in computers, atomizers, rotating air cleaners, gas turbines, and evaporators. This study was conducted within a Darcy-Forchheimer porous medium and considered the impact of a magnetic field, heat source, and thermal radiation. The governing mathematical equations are transformed into coupled and nonlinear ordinary differential equations through similarity transformations. Subsequently, these equations are numerically solved using MATLAB's built-in function "bvp4c". A multilayer perceptron based artificial neural network (ANN) model has been formulated to predict the Nusselt number (heat transfer rate) on both the lower and upper surfaces of the disk. The model utilizes the Levenberg-Marquardt training algorithm, renowned for its exceptional learning capability, as the training method for the ANN. Moreover, the authors generated a dataset consisting of 84 data points for each case using numerical methods to construct the proposed Multilayer Perceptron Artificial Neural Network. The computed mean squared error values for the developed ANN model, targeting Nusselt number predictions, were found to be 2×10−6, 5×10−6, 9×10−6, and 3×10−6. Additionally, the regression (R2) values, serving as an additional performance parameter, were determined as 0.999317, 0.997672, 0.999963, and 0.999840, respectively. A comprehensive assessment of these outcomes, strongly affirms that the ANN model has been crafted with a high degree of accuracy for predicting Nusselt numbers.

Objectives: Dengue emerged as a significant health threat in endemic regions in recent years. However, inconsistent diagnostic accuracy in sequential dengue infections necessitate improved testing methods to ensure effective management of dengue cases. Here, we evaluated a portable, rapid, and sensitive molecular assay—reverse transcriptase recombinase polymerase amplification assay (RT-RAA)—utilizing a mobile suitcase laboratory to detect infections in suspected dengue cases in Bangladesh. Methods: A total of 364 suspected patients with dengue were enrolled in the study. Dengue cases were confirmed by a positive result from any of the four tests: non-structural protein 1 (NS1) rapid diagnostic test (RDT), immunoglobulin (Ig) M RDT, quantitative reverse transcriptive-polymerase chain reaction (RT-PCR), and RT-RAA assay. IgG RDT was performed to differentiate between primary and secondary dengue infections. Results: Of 364 suspected cases, 320 were confirmed dengue cases, with 55.94% classified as primary and 44.06% as secondary infections. Laboratory results showed comparable positivity rates between RT-RAA (78.8%) and NS1 RDT (77.1%) in primary dengue, followed by quantitative RT-PCR (57.5%) and IgM RDT (12.8%). RT-RAA demonstrated superior positivity rates in secondary dengue (76.6%), surpassing RT-PCR (60.3%), NS1 RDT (27%), and IgM RDT (24.8%). Combining RT-RAA with NS1 RDT detected infections in 89.95% primary and 81.56% secondary dengue. Conclusions: The findings suggest that complementing RT-RAA with NS1 RDT could significantly improve dengue detection rate, particularly, for secondary infections.

Within the basis light-front quantization (BLFQ) framework, we evaluate the gluon chiral-odd generalized parton distributions (GPDs) inside the proton at zero skewness. We employ the light-front wave functions of the proton obtained from a light-front quantized Hamiltonian with quantum chromodynamics input using BLFQ. Our investigation encompasses both the valence Fock sector with three constituent quarks and an additional sector containing three quarks and a dynamical gluon. We analyze the gluon GPDs in the momentum space as well as in the transverse position space. We further present the gluon's generalized form factors derived from the Mellin moments of its chiral-odd GPDs. Using the proton transverse spin sum rule, we also present the x-dependence of the angular momentum carried by the polarized gluon and determine the relative contributions of quarks and the gluon to the transversity asymmetry.

The present study explores the unsteady flow of a nanoliquid past a stretching cylinder with the consequence of heat source/sink and chemical reaction. Additionally, the effect of nanoparticle aggregation, convective boundary conditions, and magnetic field on the liquid flow is taken into consideration. Utilizing similarity variables, the modeled equations are transformed into dimensionless ordinary differential equations (ODEs). Further, the obtained ODEs are numerically solved by using the Keller box method. Moreover, the physics-informed neural network (PINN) is applied to analyze the flow, heat, and mass transport features. Graphical illustrations are used to display the influence of various parameters on the velocity, concentration, and temperature profiles for aggregation and without aggregation cases. As the value of the magnetic parameter increases, the temperature and concentration profile upsurge, but the reverse trend can be seen in the velocity profile. The concentration and temperature profiles rise as the unsteadiness parameter increases, but the velocity profile declines. The concentration, velocity, and temperature profiles are strengthened by an improvement in the curvature parameter value. The intensification in the values of the chemical reaction parameter declines the concentration.

High scalability and quick deployability of solar photovoltaic (PV) make it an ideal candidate for rapid decarbonization of electricity. The typical SPV generation profile and power grids designed for conventional power plants (PP) are the major obstacles to maximizing SPV utilization. While energy storage systems (ESS) are often deemed critical, scalable ESS are site-limited, highly dependent on rare-earth elements, and either have higher embodied energy and emissions or low round-trip efficiencies. This manuscript demonstrates that by strategically interconnecting SPV power plants longitudinally, PV can meet base load demands and extend availability beyond peak-solar hours, thereby reducing the need for ESS and replacing existing carbon-intensive electricity infrastructure. It is demonstrated by modelling two 12 GW longitudinally separated transmission lines interconnecting SPVPPs situated 40° (case-1) and 90° (case-2) apart can provide PV electricity beyond solar hours for 4.69 and 7.33 equivalent hours (daily average), respectively. For cases 1 and 2, the lithium battery-ESS route can result in 4.76 and 3.35 times more carbon emissions and cost 4.23 and 2.98 times more than the transmission route, respectively, for providing the same energy over the transmission line's 40-year lifespan. Technologies such as multi-terminal ultra-high-voltage-DC grids, hybrid superconductive cables, new semiconductor materials for PV and energy systems, etc. are explored for the globally interconnected solar grid. Findings suggest 90 TWp of PV capacity can supply a significant portion of world's energy demand by 2050. This study outlines a comprehensive approach to build a sustainable and interconnected global solar energy infrastructure that aligns with climate objectives.

Insects are an integral part of an agroecosystem. Some of them are pestiferous, while some are beneficial like- natural enemies and pollinators. Therefore, it is very important to identify and manage them timely. With the rapid development of convolutional neural networks, automatic detection techniques for identifying insects using digital images have shown impressive performances in agriculture. In this study, we propose a deep learning approach using YOLOv5-based single-stage object detection model for the identification of agriculturally important insects of crucifers and some of their damage symptoms. A total of 2,730 images were captured from different fields and polyhouses using different smartphones and an SLR camera. The specimens were taxonomically identified by experts and the images were curated, annotated, resized, augmented, split, and trained, validated and tested through five variants of YOLOv5 viz. nano (n), small (s), medium (m), large (l), and extra-large (x). After all the experiments, YOLOv5l was found to be the best-performing model, acquiring an average accuracy, precision, recall, and F1-Score of 99.5%, 92.0%, 83.0%, and 0.873, respectively in the test images. The inference time and computational complexity of YOLOv5l are also significantly lower than those of YOLOv5x. Therefore, to strike a balance between complexity and performance, YOLOv5l has emerged as the most viable option to integrate with AI-based insect identification applications. Our findings reveals that deep learning is reliable for quick detection of insects under complex backgrounds. Further, we demonstrate that use of damage symptoms produced by insects will also be explored for pest detection. Integration of present model with mobile application will help the farmers and stake holders in detection of insects and suggesting effective management.

Summary: Genomic plasticity helps adapt to extreme environmental conditions. We tested the hypothesis that exposure to space environment (ESE) impacts the epigenome inducing genomic plasticity. Murine skin samples from the Rodent Research Reference Mission-1 were procured from the International Space Station (ISS) National Laboratory. Targeted RNA sequencing to test differential gene expression between the skin of ESE versus ground controls revealed upregulation of VEGF-mediated angiogenesis pathways secondary to promoter hypomethylation in responders. Methylome sequencing identified ESE-sensitive hypomethylated genes including developmental angiogenic genes Araf, Vegfb, and Vegfr1. Based on differentially expressed genes, the angiogenesis biofunction was enriched in responders. The induction of genomic plasticity in response to ESE, as reported herein, may be viewed as a mark of biological resilience that is evident in a minority of organisms, responders but not in non-responders, exposed to the same stressor. Inducible genomic plasticity may be implicated in natural resilience to ESE.

Particulate matter (PM) is an extremely overlooked air pollutant with drastic effects on the biome, owing to the industrial and agricultural advancements, significantly exacerbating global environmental contamination levels. The altered atmosphere in urban settings due to PM pollution profoundly influences plants' morphological, physiochemical state and allied responses. PM exposure leads to drastic decrease in plant-height, phytomass, leaf number, leaf length and productivity. PM change the epicuticular wax patterns, penetrates plant tissue through stomata, and denatures the chloroplast pigmentation. It changes leaves' light absorption and reflection patterns, weakening the total radiation that reaches the chlorophyll antenna and ultimately reducing the photosynthetic rate and electron transport chain. Consequently, this alters plants morphology like wax deposits, thick epidermis, and long trichomes near stomata. Moreover, PM stress also adversely effects gluconeogenesis, amino acid biosynthesis, TCA cycle, and photorespiration-associated gene expression. Several transcription factors, such as MYB, C3H, and G2-homologues, are activated as a collective stress response. Additionally, ascorbic acid, proline and soluble sugars accumulate and several antioxidants are produced to scavenge the PM-induced reactive oxygen species (ROS). This review aims to document plants' various responses to PM pollution in their respective eco-geographic settings and investigate ways used by plants to mitigate PM pollution. We also enumerate the consequences of PM pollution on plants and the corresponding phenomic and genetic mechanisms through which plants adapt.

This study explored the thermal tolerance and routine metabolic rate of ten small indigenous fish species from Northeast India: Amblypharyngodon mola, Esomus danrica, Puntius sophore, Gudusia chapra, Heteropneustes fossilis, Botia dario, Lepidocephalichthys guntea, Mystus cavasius, Aplocheilus panchax, and Glossogobius giuris. Fish were acclimated to 20°C, 25°C, and 30°C for two weeks prior to experiments and assessed for critical thermal maxima (CTmax), critical thermal minima (CTmin), lethal thermal maxima (LTmax), oxygen consumption rates, and respiratory quotients using standardized methods. The results revealed significant interspecific variations: CTmax ranged from 36.4°C to 41.7°C, CTmin from 8.7°C to 15.2°C, and LTmax from 41.5°C to 44.9°C. Oxygen consumption rates varied between 0.26 and 1.07 mg O₂/g/h, with respiratory quotients ranging from 0.76 to 1.01. Heteropneustes fossilis (CTmax: 41.7°C at 30°C acclimation) exhibited the highest thermal tolerance, while Amblypharyngodon mola had the lowest (CTmax: 38.2°C at 30°C acclimation). Differences in thermal tolerance between species were statistically significant (p

Purpose: this study aims to present an innovative approach (Diffusion of Innovation Theory) to investigate the adoption of ChatGPT by business and management students. The theory emphasizes integrating the variables Viz. relative advantage, compatibility, complexity, trialability, observability, attitude, and intention to adopt ChatGPT in the context of management education. Method: ology: a non-probability purposive sample of 383 students enrolled in management of Indian public and private institutions was taken to conduct survey to administer questionnaires. Partial Least Square-Structural Equation Modelling was employed to analyze the data using Smart PLS software. Findings: the findings suggest that students' attitude toward the integration of ChatGPT for educational purposes and knowledge acquisition are overwhelmingly positive. Moreover, relative benefit, compatibility, complexity, trialability, and observability indicate a favorable disposition toward the intention to use ChatGPT among business and management students’ community. Implications: the study asserts significant implications for multiple sectors, including global society, businesses, and academia. The application of the Diffusion of Innovation Theory to the examination of management students' attitude towards ChatGPT provides valuable practical and theoretical insights. Originality: the originality of the study lies in the innovative approach it takes in investigating the utilization of ChatGPT in management education. Hence, the application of the Diffusion of Innovation theory and the inclusion of context-specific characteristics contribute to the uniqueness of the study.

This article introduces a novel method for designing a fast chaotic oscillator using a CCTA (Current Conveyor Transconductance Amplifier) based on Chua's circuit. The proposed method uses innovative configurations and advanced simulation techniques to overcome challenges in high-speed operation, nonlinear dynamics, and Analog Building Block (ABB) selection. The design begins with nonlinear negative resistance, essential for Chua's diode characteristics, including two negative resistances, NR1 and NR2. The circuit integrates one CCTA block, two grounded capacitors, two fixed resistors, one inductor, and one potentiometer. It is simulated using PSPICE with IC (Integrated Circuit) macro-models and 180nm CMOS (Complementary Metal Oxide Semiconductor) technology. Various chaotic waveforms and attractors are produced, validating the theoretical and mathematical predictions. By varying the resistance values (1450Ω, 1650Ω, 1800Ω, 1950Ω), the circuit exhibits different chaotic behaviors, such as large limit cycles, double-scroll attractors, Rossler-type attractors, and I-periodic attractors. FFT (Fast Fourier Transform) analysis confirms the highest dominant operating frequency of 37.5MHz. A Monte Carlo simulation with 100 runs shows maximum voltage variations in the chaotic waveforms of 5.21 % and 4.61 % across the capacitors, demonstrating robustness and reliability. This design offers significant advancements in implementing high-frequency chaotic oscillators, with potential applications in various fields requiring chaotic signal generation. • A novel design of Chua's diode and Chua's chaotic oscillator using only one CCTA block is presented in this paper. • The proposed chaotic oscillator achieves the highest operating frequency of 37.5MHz. • The proposed circuit is simulated using commercially available ICs (MAX435 and AD844) and CMOS 180nm technology in PSPICE to confirm its workability.

Shot noise measures out-of-equilibrium current fluctuations and is a powerful tool to probe the nature of current-carrying excitations in quantum systems. Recent shot-noise measurements in the heavy-fermion strange metal YbRh_{2}Si_{2} exhibit a strong suppression of the Fano factor (F)—the ratio of the current noise to the average current in the dc limit. This system is representative of metals in which electron correlations are extremely strong. Here we carry out the first theoretical study on the shot noise of diffusive metals in the regime of strong correlations. A Boltzmann-Langevin equation formulation is constructed in a quasiparticle description in the presence of strong correlations. We find that F=sqrt[3]/4 in such a correlation regime. Thus, we establish the aforementioned Fano factor as universal to Fermi liquids, and we show that the Fano factor suppression observed in experiments on YbRh_{2}Si_{2} necessitates a loss of the quasiparticles. Our work opens the door to systematic theoretical studies of shot noise as a means of characterizing strongly correlated metallic phases and materials.

PURPOSESquamous cell carcinoma of the head and neck (SCCHN) is the sixth most common cancer, with approximately 225,419 new cases with over 125,000 deaths annually in India. This trial compared the efficacy and safety of biosimilar cetuximab versus innovator cetuximab (IC) in combination with platinum-based chemotherapy in patients with recurrent locoregional or metastatic SCCHN.METHODSThis phase III trial is a multicenter, randomized, double-blind and parallel group study performed in Indian patients with recurrent locoregional or metastatic SCCHN. Patients were randomly assigned in 2:1 ratio to receive biosimilar cetuximab and IC in combination with cisplatin and fluorouracil via intravenous infusions. The primary end points were disease control rate (DCR) and overall response rate (ORR) as per response evaluation criteria in solid tumors version 1.1. The secondary end points included pharmacokinetics (PK), immunogenicity, safety, and tolerability.RESULTSOf 180 patients enrolled, 120 patients received biosimilar cetuximab and 60 patients received IC treatment. No significant statistical difference was observed in the primary outcomes between two groups. Treatment difference in DCR and ORR response was found to be –5.21 (90% CI, –8.94 to –1.48) and –4.79 (90% CI, –19.42 to 9.84), respectively, indicating noninferiority to reference product. The incidence of treatment-emergent adverse events (AEs; biosimilar cetuximab: 89.2% v IC: 91.7%; P = .8364) and serious AEs (biosimilar cetuximab: 23.3% v IC: 13.3%; P = .0603) and PK parameters were comparable between treatment groups. The immunogenicity findings showed higher incidence of anticetuximab antibodies in the biosimilar cetuximab group compared with the IC group at the end of Study.CONCLUSIONThe findings of this study demonstrated noninferiority along with comparable PK, safety, and immunogenicity of biosimilar cetuximab and IC in patients with recurrent or metastatic SCCHN.

ABSTRACT Avian leukosis is a significant viral disease affecting chicken populations globally, including Bangladesh, resulting in high mortality and morbidity rates and causing substantial economic losses in the commercial poultry industry. This study aimed to detect avian leukosis virus (ALV) during recent outbreaks in Bangladesh, utilising a molecular‐based approach. A total of 14 liver samples were collected from the suspected layer flocks in Bangladesh. The diagnosis of ALV infection in chickens was confirmed through necropsy, histopathological examinations, reverse transcription‐polymerase chain reaction (RT‐PCR), and sequence analysis. Gross observations revealed severe liver enlargement with scattered white nodules on the surface in the infected chickens. Histopathological observations showed the infiltration of huge mononuclear inflammatory cells in the periportal area of liver and microvesicular fatty degeneration and necrosis of some hepatocytes. RT‐PCR results identified three samples positive for the env gene of ALV. Sequence analysis of the env genes demonstrated high homology among the identified strains (97%–98%) and with reference strains (92%–96%) at the nucleotide level. The phylogenetic tree revealed close relatedness of the three identified strains to reference strains from India, USA, and China. Mutational analysis indicated several mutations throughout the envelope glycoprotein of the identified strains. Protein structure analysis showed minor changes in the hydrophobic region of the envelope protein of the identified strains. In conclusion, this study, the first detailed investigation in Bangladesh, contributes to understanding ALV epidemiology, highlights genetic diversity, and emphasises the necessity for further investigations and the implementation of effective control measures in the affected regions.

Abstract Background The emergence and dissemination of multidrug resistant (MDR) bacteria pose a severe threat to public health by limiting clinical treatment and prophylactic options. Objectives This study investigates the prevalence of Escherichia coli in broilers, their phenotypic antimicrobial resistance (AMR) profiles and the presence of virulence‐associated genes (VAGs) and antimicrobial resistance genes (ARGs) using polymerase chain reaction (PCR). Materials and methods A total of 216 pooled cloacal samples were collected from 1080 broilers across six districts of Bangladesh. Each pooled sample comprised randomly selected cloacal swabs from five birds per farm. E. coli isolates were identified using standard bacteriological approach, followed by biochemical assays and PCR. Antimicrobial susceptibility was assessed using the Kirby–Bauer disc diffusion method, and the presence of ARGs and VAGs was determined via PCR. Five selected isolates were partially sequenced for five VAGs using Sanger sequencing. Results A total of 177 E. coli isolates (81.94%, 95% confidence interval: 76.24%–86.53%) were identified. The isolates showed the highest resistance to ampicillin (93.79%), followed by tetracycline (91.53%), erythromycin (89.27%) and ciprofloxacin (87%). Conversely, ceftriaxone (80.79%) showed highest susceptibility, followed by gentamicin (37.29%) and neomycin (31.07%). All isolates were MDR, with a multiple antibiotic resistance indexes were

Orchestrated action of peptidoglycan (PG) synthetases and hydrolases is vital for bacterial growth and viability. Although the function of several PG synthetases and hydrolases is well understood, the function, regulation, and mechanism of action of PG hydrolases characterised as lysostaphin-like endopeptidases have remained elusive. Many of these M23 family members can hydrolyse glycyl-glycine peptide bonds and show lytic activity against Staphylococcus aureus whose PG contains a pentaglycine bridge, but their exact substrate specificity and hydrolysed bonds are still vaguely determined. In this work, we have employed NMR spectroscopy to study both the substrate specificity and the bond cleavage of the bactericide lysostaphin and the S. aureus PG hydrolase LytM. Yet, we provide substrate-level evidence for the functional role of these enzymes. Indeed, our results show that the substrate specificities of these structurally highly homologous enzymes are similar, but unlike observed earlier both LytM and lysostaphin prefer the D-Ala-Gly cross-linked part of mature peptidoglycan. However, we show that while lysostaphin is genuinely a glycyl-glycine hydrolase, LytM can also act as a D-alanyl-glycine endopeptidase.

Isolated cysticercosis of the sternocleidomastoid is a rare entity caused by the ingestion of eggs of Taenia solium. The case reported here is of a 24-year-old male who presented to the hospital with complaints of a firm, non-tender, isolated, progressively increasing swelling of the right side of his neck for 3 months. Diagnosis of cysticercosis was made on high-resolution ultrasound and the patient was managed medically with complete resolution. The relevant findings of the case are discussed herein.

A 23 yr old primigravida reported for a 1st-trimester antenatal scan at 12 weeks of gestation. Sonography revealed findings consistent with Cystic Hygroma with Hydrops fetalis. The case merits discussion to reflect upon the findings of these rare co-existing grave medical conditions in the fetus and emphasize the relevance of timely antenatal diagnosis of Cystic Hygroma with concomitant hydrops, the condition known to have a very high rate of fetal mortality. The relevant review of literature and findings of the case are discussed thence.

Purpose: Scrub typhus is a potentially life-threatening febrile illness associated with serious complications viz. pneumonia, acute respiratory distress syndrome, hepatic failure, acute kidney injury, encephalitis, and shock often culminating in mortality. We aimed to identify the predictors of mortality in scrub typhus. Methods: This prospective observational study was conducted in a tertiary referral hospital of the north Indian state of Uttarakhand on in-patients of scrub typhus hospitalized over 1 year Results: Of the 109 cases studied (54.1% males), 44% were aged

Abstract Accurately predicting agricultural commodity prices is crucial for India's economy. Traditional parametric models struggle with stringent assumptions, while machine learning (ML) approaches, though data-driven, lack automatic feature extraction. Deep learning (DL) models, with advanced feature extraction and predictive abilities, offer a promising solution. However, their application to agricultural price data ignored the exogenous factors. Hence, the study explored advanced versions of the well-known univariate models, NBEATSX and TransformerX. The research employed price data for essential crops like Tomato, Onion, and Potato (TOP) from major Indian markets and complemented it with corresponding weather data (precipitation and temperature). To provide a comprehensive analysis, the study also evaluated traditional statistical methods (ARIMAX and MLR) and a suite of ML algorithms (ANN, SVR, RFR, and XGBoost). The performance of these models was rigorously evaluated using error metrics like RMSE, MAE, sMAPE, MASE and QL. The findings were significant indicating DL models, particularly when augmented with exogenous variables, consistently outshone other methods with NBEATSX and TransformerX showing an average RMSE of 110.33 and 135.33, MAE of 60.08 and 74.92, sMAPE of 22.14 and 24.00, MASE of 1.02 and 1.32 and QL of 30.04 and 34.07, respectively. They exhibited lower error metrics, as compare to the statistical and ML models underscoring their effectiveness and potential in agricultural crop price forecasting. This study not only bridged a crucial research gap but also highlighted the robust potential of DL models in enhancing the accuracy of agricultural commodity price predictions in India.

Abstract We explore long-lived particle (LLP) searches using non-pointing photons at the LHC as a probe for sterile-to-sterile and active-to-sterile transition magnetic dipole moments of sterile neutrinos. We consider heavy sterile neutrinos with masses ranging from a few GeV to several hundreds of GeV. We discuss transition magnetic dipole moments using the Standard Model effective field theory and low-energy effective field theory extended by sterile neutrinos (N R SMEFT and N R LEFT) and also provide a simplified UV-complete model example. LLP searches at the LHC using non-pointing photons will probe sterile-to-sterile dipole moments two orders of magnitude below the current best constraints from LEP, while an unprecedented sensitivity to sterile neutrino mass of about 700 GeV is expected for active-to-sterile dipole moments. For the UV model example with one-loop transition magnetic moments, the searches for charged lepton flavour violating processes in synergy with LLP searches at the LHC can probe new physics at several TeV mass scales and provide valuable insights into the lepton flavour structure of new physics couplings.

Abstract Background Plastic is widely utilized in packaging, frameworks, and as coverings material. Its overconsumption and slow degradation, pose threats to ecosystems due to its toxic effects. While polyhydroxyalkanoates (PHA) offer a sustainable alternative to petroleum-based plastics, their production costs present significant obstacles to global adoption. On the other side, a multitude of household and industrial activities generate substantial volumes of wastewater containing both organic and inorganic contaminants. This not only poses a threat to ecosystems but also presents opportunities to get benefits from the circular economy. Main body of abstract Production of bioplastics may be improved by using the nutrients and minerals in wastewater as a feedstock for microbial fermentation. Strategies like feast-famine culture, mixed-consortia culture, and integrated processes have been developed for PHA production from highly polluted wastewater with high organic loads. Various process parameters like organic loading rate, organic content (volatile fatty acids), dissolved oxygen, operating pH, and temperature also have critical roles in PHA accumulation in microbial biomass. Research advances are also going on in downstream and recovery of PHA utilizing a combination of physical and chemical (halogenated solvents, surfactants, green solvents) methods. This review highlights recent developments in upcycling wastewater resources into PHA, encompassing various production strategies, downstream processing methodologies, and techno-economic analyses. Short conclusion Organic carbon and nitrogen present in wastewater offer a promising, cost-effective source for producing bioplastic. Previous attempts have focused on enhancing productivity through optimizing culture systems and growth conditions. However, despite technological progress, significant challenges persist, such as low productivity, intricate downstream processing, scalability issues, and the properties of resulting PHA. Graphical abstract

Background: In carpal tunnel syndrome (CTS), conservative management did not show satisfactory results, and some patients required revision surgery due to persistent or recurrent symptoms. Ultrasound (USG)-guided median nerve (MN) hydrodissection with a 5% dextrose injection is an advanced approach for treating symptoms of CTS. We prospectively investigated the patients to demonstrate the safety and effectiveness of this approach. Aims and Objectives: This study aims to evaluate the effect of USG-guided nerve hydrodissection using single injection of 5% dextrose on pain, MN conduction parameters, and functional status in patients with CTS of mild–to-moderate grade. The study also predicts about the safety of the procedure. Materials and Methods: A study was performed in the pain clinic of the tertiary care teaching institute of India for one year. The study included 15 patients diagnosed with mild-to-moderate CTS. The diagnosis was done on the basis of history, physical examination, and a nerve conduction velocity (NCV) study. Patients were given analgesics and NSAIDS and enrolled in the procedure. Parameters used for statistical analysis were Visual Analog Scale (VAS) scores, NCV study data (sensory conduction velocity [SNCV] and distal motor latency [DML]), and Boston carpal tunnel questionnaire (BCTQ) scores. Pre-injection parameters were compared with parameters 3 months after the injection to show the usefulness of this procedure. Results: A statistically significant reduction in VAS score was found in 74% of the cases (P

Background and Aims: Depression is a common and debilitant mental health disorder that is very common among young adults of the age group of 18-25 years. There is evidence that autonomic nervous system dysfunction associated with depression may play an important role in cardiovascular disease among patients with depression. HRV that is used to assess ANS function is found to be altered in depression. Since the HRV findings associated with depression remain inconsistent, this study is aimed to find HRV changes associated with depression so that the use of HRV as a diagnostic tool for depression can be validated. Methods: A total of 42 newly diagnosed patients of depression of the age group (18-26) years and 89 non-depressed volunteers matched for age, BMI and sex proportions were included in the study. Heart rate variability was recorded using five-minute stationary RR interval of Lead II by 4-channel Power Lab System (AD Instrument Ltd). HRV findings are summarized into Time-Domain parameters, Frequency-Domain parameters and Non-Linear parameters. Result: All HRV parameters are significantly reduced and the LF/HF ratio is significantly raised (P < 0.05) in the group of depressive patients when compared to the group of healthy controls. The reduction of HRV parameters (SDRR, RMSSD, Total Power, SD1 and SD2) in the group of patients with depression is found to be highly significant (P < 0.0001). Conclusion: The findings of our study suggest that depression may be associated with alterations in ANS activities, which contribute to an increased risk of cardiovascular disease. Thus, HRV can serve as a potential bio-marker for depression.

BACKGROUND: Primary immunodeficiency diseases (PIDDs) are clinically and immunologically diverse and require a wide array of clinical and laboratory modalities to make specific diagnosis. Serum immunoglobulin levels and T cell, B cell and NK (Natural killer) cell immunophenotyping are routine laboratory investigations advised to diagnose the PIDD cases in Bangladesh. Along with T-B-NK markers, use of Naïve (CD45RA+) and memory (CD45RO+) T cell, switched memory B cell (CD27+IgD-) markers, detection of intracellular BTK (Bruton’s tyrosine kinase), LRBA (Lipopolysaccharide-responsive beige-like anchor), DOCK8 (Dedicator of cytokinesis 8) protein expression and DHR123 (Dihydro-rhodamine 123) assay of neutrophil can increase the PIDD cases detection in Bangladesh. METHODS: The study was conducted in the Department of Microbiology and Immunology, Bangabandhu Sheikh Mujib Medical University (BSMMU) during the time period of March, 2021 to February, 2022. Seventy clinically suspected PIDD cases were enrolled in this study on the basis of clinical findings and peripheral venous blood was collected from all patients to perform immunophenotyping. Routine T-B-NK cell, naïve and memory T cell with switched memory B cell markers were detected by flow-cytometry. Serum immunoglobulins (IgG, IgM, IgA & IgE) were estimated by Nephelometry and by Chemiluminescence. Intracellular BTK, LRBA and DOCK8 protein expression was detected by flow-cytometry in suspected X-linked agammaglobulinemia (XLA), LRBA and DOCK8 deficiency patients respectively. DHR123 assay was performed in suspected Chronic granulomatous disease (CGD) patients. RESULTS: Among the 70 clinically suspected PIDD cases, 9 (12.9%) were diagnosed as patients of PIDDs on the basis of laboratory evidence. Five (55.55%) cases were diagnosed as predominantly antibody deficiencies (PADs), 3 (33.33%) were patients of combined immunodeficiency (CID) and 1 (11.11%) was CGD patient. Among the diagnosed PIDD cases, 2 (22.22%) were diagnosed by T-B-NK cell immunophenotyping with serum immunoglobulin levels and 7 (77.77%) cases were diagnosed by additional CD45RA+, CD45RO+, CD27+IgD- markers, BTK protein expression detection and DHR123 assay. LRBA and DOCK8 deficiency cases could not found in this study. CONCLUSION: The use of additional markers (CD45RA+, CD45RO+, CD27+IgD-) with BTK, LRBA, DOCK8 intracellular protein expression evaluation and DHR123 assay by flow-cytometry can increase rate of specific diagnosis of the PIDD cases in Bangladeshi paediatric population.

Acute kidney injury (AKI) is a common and severe complication in severe burns. Preexisting chronic kidney disease (CKD) can make the management more challenging. We present the management strategy adopted in such a case, highlighting the adaptations in fluid resuscitation, dialysis, and septicemia prevention. The case involved the 2nd and 3rd degree burns covering 53% body surface, in a patient with preexisting CKD and hypertension. Despite initial fluid resuscitation, the patient developed AKI. Sustained low-efficiency dialysis (SLED) was started, along with nutritional support using buttermilk diet. Aggressive antibiotic prophylaxis was initiated based on wound swabs culture and sensitivity. Wound debridement was deferred and daily dressing with silver nitrate gel and moisture-retaining film was used. Debridement and grafting were performed on postburn days 43 and 65. The patient was discharged after 80 days, with healed wounds. Our approach included meticulous fluid and nutrition supplementation coupled with SLED and appropriate wound management coupled with aggressive antimicrobial prophylaxis to prevent septicemia.