Impact and perceived value of the revolutionary advent of artificial intelligence in research and publishing among researchers: a survey-based descriptive study

Purpose This study was conducted to understand the perceptions and awareness of artificial intelligence (AI) in the academic publishing landscape. Methods We conducted a global survey entitled “Role and impact of AI on the future of academic publishing” to understand the impact of the AI wave in the scholarly publishing domain. This English-language survey was open to all researchers, authors, editors, publishers, and other stakeholders in the scholarly community. Conducted between August and October 2021, the survey received responses from around 212 universities across 54 countries. Results Out of 365 respondents, about 93% belonged to the age groups of 18–34 and 35–54 years. While 50% of the respondents selected plagiarism detection as the most widely known AI-based application, image recognition (42%), data analytics (40%), and language enhancement (39%) were some other known applications of AI. The respondents also expressed the opinion that the academic publishing landscape will significantly benefit from AI. However, the major challenges restraining the large-scale adoption of AI, as expressed by 93% of the respondents, were limited knowledge and expertise, as well as difficulties in integrating AI-based solutions into existing IT infrastructure. Conclusion The survey responses reflected the necessity of AI in research and publishing. This study suggests possible ways to support a smooth transition. This can be best achieved by educating and creating awareness to ease possible fears and hesitation, and to actualize the promising benefits of AI

Biochemical characterization of sporulation-related histidine kinases in Clostridioides difficile

Histidine kinases are one of the two proteins that constitute a two-component signal transduction system. These systems are used by bacteria, fungi, and several plants to sense the conditions of their environment and alter their behavior to ensure survival. In bacteria, two-component systems control basic cellular processes like motility, virulence, cell division, sporulation etc. While histidine kinases are responsible for signal perception in the host, the other protein of this system, called response regulator, conducts the response output. These response outputs can be downstream gene regulation via DNA binding, RNA binding, enzymatic reactions etc. Although a significant number of histidine kinases have been identified for Clostridioides difficile till date, it is not yet clear how these histidine kinases affect the pathogenicity of this bacterium, especially sporulation, a process where bacterial cell goes into a dormant form until placed in a favorable environment. The precise prediction of progression mechanism of sporulation adopted by this bacterium could enable researchers to develop techniques to mitigate this pathogenic behavior. In general, these two-component systems (TCS) are absent in mammals and hence can be a good target for therapeutics for several bacterial and fungal infections. This thesis presents a detailed script of studies done towards unraveling the mechanism behind sporulation of Clostridioides difficile. This includes using γ-32P ATP functional assay to provide quantitative and qualitative evidence of functional activities of sporulation-related histidine kinases as well as initial binding screens to examine the impetus behind these phosphorelay systems. Histidine kinases covered in this study are HK_1587 from the hypervirulent R20291 strain and CD1492 and CD2492 from the historic CD630 strain of C. difficile

Thermoelectric properties of Cu3SbSe3 with intrinsically ultralow lattice thermal conductivity

We report the synthesis, characterization and evaluation of the thermoelectric properties of Cu3SbSe3 with a view to explore its utility as an useful thermoelectric material due to its intrinsically low thermal conductivity. Cu3SbSe3 was synthesized employing a solid state reaction process followed by spark plasma sintering, and the synthesized material was extensively characterized for its phase, composition and structure, which suggested formation of a single-phase. The measured electrical transport properties of Cu3SbSe3 indicated p-type conduction in this material. The electrical transport behavior agrees well with that predicted theoretically using first-principle density-functional theory calculations, employing generalized gradient approximation. The measured thermal conductivity was found to be 0.26 W m(-1) K-1 at 550 K, which is the lowest reported thus far for Cu3SbSe3 and is among the lowest for state-of-the-art thermoelectric materials. Despite its ultralow thermal conductivity coupled with a moderate Seebeck coefficient, the calculated value of its thermoelectric figure-of-merit was found to be exceptionally low (<0.1), which was primarily attributed to its low electrical conductivity. Nevertheless, it is argued that Cu3SbSe3, due its environmentally-friendly constituent elements, ultralow thermal conductivity and moderate thermopower, could be a potentially useful thermoelectric material as the power factor can be favorably tailored by tuning the carrier concentration using suitable metallic dopants

Intraperitoneal bupivacaine alone or with dexmedetomidine or tramadol for post-operative analgesia following laparoscopic cholecystectomy: A comparative evaluation

Background and Aims: Intraperitoneal instillation of local anaesthetics has been shown to minimise post-operative pain after laparoscopic surgeries. We compared the antinociceptive effects of intraperitoneal dexmedetomidine or tramadol combined with bupivacaine to intraperitoneal bupivacaine alone in patients undergoing laparoscopic cholecystectomy. Methods: A total of 120 patients were included in this prospective, double-blind, randomised study. Patients were randomly divided into three equal sized (n = 40) study groups. Patients received intraperitoneal bupivacaine 50 ml 0.25% +5 ml normal saline (NS) in Group B, bupivacaine 50 ml 0.25% + tramadol 1 mg/kg (diluted in 5 ml NS) in Group BT and bupivacaine 50 ml 0.25% + dexmedetomidine 1 μg/kg, (diluted in 5 ml NS) in Group BD before removal of trocar at the end of surgery. The quality of analgesia was assessed by visual analogue scale score (VAS). Time to the first request of analgesia, total dose of analgesic in the first 24 h and adverse effects were noted. Statistical analysis was performed using Microsoft (MS) Office Excel Software with the Student′s t-test and Chi-square test (level of significance P = 0.05). Results: VAS at different time intervals, overall VAS in 24 h was significantly lower (1.80 ± 0.36, 3.01 ± 0.48, 4.5 ± 0.92), time to first request of analgesia (min) was longest (128 ± 20, 118 ± 22, 55 ± 18) and total analgesic consumption (mg) was lowest (45 ± 15, 85 ± 35, 175 ± 75) in Group BD than Group BT and Group B. Conclusion: Intraperitoneal instillation of bupivacaine in combination with dexmedetomidine is superior to bupivacaine alone and may be better than bupivacaine with tramadol

Data science for Chemists: Integrating and evaluating the use of interactive digital python notebooks in a large enrollment undergraduate biochemistry course

Genomic sequencing and other big biological data is unquestionably of paramount value, however the success in recruiting highly skilled individuals with diverse backgrounds has been limited. A main reason for this deficiency could be due to the lack of educational resources and early exposure to the field. With the steady increase in big biological data over the past decade1, we not only need to increase the number of skilled researchers in the field but also empower the next generation of students with skills that can apply data analysis skills to a variety of career trajectories23,4. Here, we share a successful example of integrating python-based interactive digital notebooks in a large-enrollment undergraduate chemistry course with more than 400 participants across various degree programs. The goal of this manuscript is to detail the teaching pedagogy, supply the teaching materials, and evaluate the outcomes of integrating coding in a large-enrollment undergraduate chemistry course. The benefit of integrating coding exercises in large-enrollment undergraduate classes is to provide earlier exposure of data science to undergraduate students. Gaining skills in big data analysis will be an asset to any chemist, biologist, physician or scientist, regardless of career path or academic trajectory

Emerging extraction and diagnostic tools for detection of plant pathogens: Recent trends, challenges, and future scope

Plant pathogens are a serious threat to agriculture for long-term viability and cost loss of billions of dollars yearly. Many pathogens have been documented in the literature that infect a variety of crops. Nevertheless, new pathogens emerge and often result in disease outbreaks, leading to million-dollar losses. Currently, several diagnostic approaches with enhanced sensitivity and specificity for the identification of widespread and/or unknown plant pathogens are constantly being developed. Whereas the extensively used approaches for plant pathogen diagnostics are mostly serological and nucleic acid-based assays, many different nucleic acid-based approaches for amplifying target DNA/RNA have also emerged over time. However, these approaches lack precision, specificity, and rapidity, making them unsuitable for on-field analysis. As a result, there is a lot of interest arising in field-deployable point of care (POC) devices and artificial intelligence (AI)-assisted pathogens' detection accurately at an early stage within a minute. Similarly, development of a cell-lysis and purification-free DNA/RNA extraction process is also crucial for quick sample preparation for molecular diagnosis of plant pathogens at field level. In this review, we have discussed advanced tools that are trending not only to extract nucleic acids but also detect plant pathogens. We have also discussed critical challenges and future perspectives of disease diagnostic tools for plant pathogens' detection. In summary, advanced plant disease diagnostic tools can be helpful for routine monitoring of plant pathogens toward improving crop productivity and yield that can be used for improving the financial status of farmers.Web of Science2588185

Mental Health Issues in Madhya Pradesh: Insights from National Mental Health Survey of India 2016

Background: About 14% of the global mental health burden is contributed by India. However, there exists a disparity in mental health patterns, utilization, and prioritization among various Indian states. The state of Madhya Pradesh is a low performer among Indian states, ranking lower than the national average on the Human Development Index, Hunger Index, and Gross Domestic Product (GDP). The state also performes poorly on other health-related indicators. Objectives of Study: To estimate the prevalence and patterns of mental illnesses in the state of Madhya Pradesh, India. Material and Methods: This study used the multistage, stratified, random cluster sampling technique, with selection probability proportionate to size at each stage. A total of 3240 individuals 18 years and older were interviewed. The mixed-method study that was employed had both quantitative and qualitative components. The Mini International Neuropsychiatric Interview along with 10 other instruments were used. Results: The overall weighted prevalence for any mental illness was 13.9%, with 16.7% over the lifetime. The treatment gap for all of the mental health problems is very high (91%), along with high suicidal risk and substance use in the state. Conclusions: This study provides evidence of the huge burden of mental, behavioral, and substance use disorders as well as the treatment gap in Madhya Pradesh. This information is crucial for developing an effective prevention and control strategy. The high treatment gap in the state calls for coordinated efforts from all stakeholders, including policy makers, political leaders, health care professionals, and the society at large to give mental health care its due priority. These findings also highlight the need for multi-pronged interventions rooted in health policy directed at reducing the treatment gap in the short term and disease burden in the long run

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