We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
Online ordering will be unavailable from 17:00 GMT on Friday, April 25 until 17:00 GMT on Sunday, April 27 due to maintenance. We apologise for the inconvenience.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
The therapeutic effects of soya consumption on adipokine concentrations have yielded inconsistent results in previous meta-analyses. This umbrella meta-analysis aims to investigate the impact of soya and its isoflavones on serum adiponectin and leptin levels in adults. We searched the Cochrane Central, Web of Science, PubMed and Scopus databases until October 10, 2024. The articles were restricted to those written in English. We included meta-analysis studies that evaluated the effects of soya and its isoflavones on levels of adiponectin and leptin and reported effect sizes (ES) and corresponding CI. Two independent reviewers screened all articles based on eligibility criteria and extracted the required data from the included meta-analyses. The meta-analysis was performed using a random-effects model in STATA software. Six meta-analyses of randomised controlled trials meeting the inclusion criteria were included in the current umbrella meta-analysis. The findings indicated that soya and its isoflavones did not have a significant effect on adiponectin (ES = 0·10; 95 % CI: −0·22, 0·41; P = 0·55; I2 = 51·8 %) and leptin (ES = −0·37; 95 % CI: −1·35, 0·61; P = 0·46; I2 = 71·2 %) concentrations. Subgroup analysis based on participants’ mean age, total sample size and duration was conducted. Results showed that the effect is not statistically significant in any of the subgroups. In conclusion, soya and its isoflavones could not improve the adipokines mentioned above. However, further high-quality research in different countries is required to substantiate these findings.
Indaziflam was evaluated in Connecticut and Tennessee, USA, for weed control and safety of container-grown ornamental plants. Indaziflam was applied at 49, 98, or 196 g ha-1 to container-grown ornamental plants on an outdoor gravel pad and preemergence or early postemergence to weeds in greenhouse. Ornamental plants were treated twice annually in 2020 and 2021 in Connecticut, and in 2019 and 2020 in Tennessee, with approximately six weeks between applications. Chinese pyramid juniper, common juniper, eastern hemlock, eastern white pine, and Norway spruce in Connecticut, USA, and 'Andorra Compacta’ creeping juniper and 'Black Dragon’ Japanese cedar, ‘Blue Rug’ creeping juniper, and ‘Blue Pfitzer’ Chinese pyramid juniper in Tennessee, USA, were not injured with indaziflam regardless of rate applied. Preemergence application of indaziflam reduced densities of creeping woodsorrel, hairy bittercress, giant foxtail, and large crabgrass 72 to 100%, depending upon the indaziflam rate applied, by 28 d after treatment (DAT). When applied early postemergence, indaziflam provided 97 to 99% control of creeping woodsorrel (1- to 2-leaf), fringed willowherb (4- to 6-leaf), hairy bittercress (cotyledon to 1-leaf), and mouse-ear chickweed (2- to 4-leaf) by 28 DAT. Compared with the nontreated control, the total fresh shoot biomass reduction was 86 to 100% and 78 to 100% following preemergence or postemergence applications. Indaziflam offers a new site-of-action with excellent safety and weed control in the tested ornamental plants.
The whitefly, Bemisia tabaci is a cryptic species complex in which one member, Middle East-Asia Minor 1 (MEAM1) has invaded globally. After invading large countries like Australia, China, and the USA, MEAM1 spread rapidly across each country. In contrast, our analysis of MEAM1 in India showed a very different pattern. Despite the detection of MEAM1 being contemporaneous with invasions in Australia, the USA, and China, MEAM1 has not spread widely and instead remains restricted to the southern regions. An assessment of Indian MEAM1 genetic diversity showed a level of diversity equivalent to that found in its presumed home range and significantly higher than that expected across the invaded range. The high level of diversity and restricted distribution raises the prospect that its home range extends into India. Similarly, while the levels of diversity in Australia and the USA conformed to that expected for the invaded range, China did not. It suggests that China may also be part of its home range. We also observed that diversity across the invaded range was primarily accounted for by a single haplotype, Hap1, which accounted for 79.8% of all records. It was only the invasion of Hap1 that enabled outbreaks to occur and MEAM1’s discovery.
Weak-line T Tauri stars (WTTS) exhibit X-ray flares, likely resulting from magnetic reconnection that heats the stellar plasma to very high temperatures. These flares are difficult to identify through targeted observations. Here, we report the serendipitous detection of the brightest X-ray flaring state of the WTTS KM Ori in the eROSITA DR1 survey. Observations from SRG/eROSITA, Chandra X-ray Observatory, and XMM-Newton are analysed to assess the X-ray properties of KM Ori, thereby establishing its flaring state at the eROSITA epoch. The long-term (1999–2020) X-ray light curve generated for the Chandra observations confirmed that eROSITA captured the source at its highest X-ray flaring state recorded to date. Multi-instrument observations support the X-ray flaring state of the source, with time-averaged X-ray luminosity ($L_\mathrm{0.2-5\ keV}$) reaching $\sim 1.9\times10^{32}\mathrm{{erg\ s^{-1}}}$ at the eROSITA epoch, marking it the brightest and possibly the longest flare observed so far. Such intense X-ray flares have been detected only in a few WTTS. The X-ray spectral analysis unveils the presence of multiple thermal plasma components at all epochs. The notably high luminosity ($L_\mathrm{0.5-8\ keV}\sim10^{32}\ \mathrm{erg\ s}^{-1}$), energy ($E_\mathrm{ 0.5-8\ keV}\sim10^{37}$ erg), and the elevated emission measures of the thermal components in the eROSITA epoch indicate a superflare/megaflare state of KM Ori. Additionally, the H$\alpha$ line equivalent width of $\sim$$-5$ Å from our optical spectral analysis, combined with the lack of infrared excess in the spectral energy distribution, were used to re-confirm the WTTS (thin disc/disc-less) classification of the source. The long-duration flare of KM Ori observed by eROSITA indicates the possibility of a slow-rise top-flat flare. The detection demonstrates the potential of eROSITA to uncover such rare, transient events, thereby providing new insights into the X-ray activity of WTTS.
This study aimed to explore the genetic variability present in tamarind fruits. A survey and collection of twenty-nine tamarind accessions from the Bastar region of Chhattisgarh was conducted, focusing on morphological traits, biochemical properties, and mineral content. The analysis revealed significant variation in fruit characteristics, including pod weight (91.1–528.3 g), pod length (4.11–15.39 cm), pulp weight (32.88–275.68 g), number of seeds (26–237), seed weight (23.14–214.08 g), pulp percentage (26.43–52.18%), vitamin C content (54.5–92 mg/100 g), phenolic content (51.53–296.4 mg GAE/g fw), flavonoid content (75.91–280.88 mg QE/ 100 g fw), acidity (5.3–12.60%), reducing sugars (24.67–68.29%), total sugars (24.89–78.87%), calcium (0.15–1.28%), and iron content (26.6–125.7 ppm) across different accessions. Based on the overall evaluation, five accessions B21, B26, B15, B25, and B7 with the best combination of desirable fruit traits, were identified as the most promising. Additionally, five sweet accessions with acidity levels below 6% were identified (B26, B21, B15, B12, B11). Principal component analysis (PCA) was applied, identifying five principal components that accounted for 86.73% of the total variability. Correlation analysis showed a significant positive relationship between pod weight and pulp weight (r = 0.93), shell weight (r = 0.70), number of seeds (r = 0.89), and seed weight (r = 0.89). The biplot of PC1 and PC2 illustrated the distribution of accessions across all four quadrants, with B27, B8, B26, B29, B14, B18, and B13 displaying distinct differences from one another.
This work studies upper-limb impairment resulting from stroke or traumatic brain injury and presents a simple technological solution for a subset of patients: a soft, active stretching aid for at-home use. To better understand the issues associated with existing associated rehabilitation devices, customer discovery conversations were conducted with 153 people in the healthcare ecosystem (60 patients, 30 caregivers, and 63 medical providers). These patients fell into two populations: spastic (stiff, clenched hands) and flaccid (limp hands). Focusing on the first category, a set of design constraints was developed based on the information collected from the customer discovery. With these constraints in mind, a powered wrist-hand stretching orthosis (exoskeleton) was designed and prototyped as a preclinical study (T0 basic science research) to aid in recovery. The orthosis was tested on two patients for proof-of-concept, one survivor of stroke and one of traumatic brain injury. The prototype was able to consistently open both patients’ hands. A mathematical model was developed to characterize joint stiffness based on experimental testing. Donning and doffing times for the prototype averaged 76 and 12.5 s, respectively, for each subject unassisted. This compared favorably to times shown in the literature. This device benefits from simple construction and low-cost materials and is envisioned to become a therapy device accessible to patients in the home. This work lays the foundation for phase 1 clinical trials and further device development.
Face milling is performed on aluminum alloy A96061-T6 at diverse cutting parameters proposed by the design of experiments. Surface roughness is predicted by examining the effects of cutting parameters (CP), vibrations (Vib), and sound characteristics (SC). Sound characteristics based on surface roughness estimation determine the rarity of the work. In this study, a unique ANN-TLBO hybrid model (Artificial Neural Networks: Teaching Learning Based Algorithm) is created to predict the surface roughness from CP, Vib, and SC. To ascertain their correctness and efficacy in evaluating surface roughness, the performance of these models is evaluated. First off, the CP hybrid model demonstrated an amazing accuracy of 95.1%, demonstrating its capacity to offer trustworthy forecasts of surface roughness values. The Vib hybrid model, in addition, demonstrated a respectable accuracy of 85.4%. Although it was not as accurate as the CP model, it nevertheless showed promise in forecasting surface roughness. The SC-based hybrid model outperformed the other two models in terms of accuracy with a remarkable accuracy of 96.2%, making it the most trustworthy and efficient technique for assessing surface roughness in this investigation. An analysis of error percentages revealed the exceptional performance of SC-based Model-3, exhibiting an average error percentage of 3.77%. This outperformed Vib Model-2 (14.52%) and CP-based Model-1 (4.75%). The SC model is the best option, and given its outstanding accuracy, it may end up becoming the go-to technique for industrial applications needing accurate surface roughness measurement. The SC model’s exceptional performance highlights the importance of optimization strategies in improving the prediction capacities of ANN-based models, leading to significant advancements in the field of surface roughness assessment and related fields. An IoT platform is developed to link the model’s output with other systems. The system created eliminates the need for manual, physical surface roughness measurement and allows for the display of surface roughness data on the cloud and other platforms.
Blast waves have been produced in solid target by irradiation with short-pulse high-intensity lasers. The mechanism of production relies on energy deposition from the hot electrons produced by laser–matter interaction, producing a steep temperature gradient inside the target. Hot electrons also produce preheating of the material ahead of the blast wave and expansion of the target rear side, which results in a complex blast wave propagation dynamic. Several diagnostics have been used to characterize the hot electron source, the induced preheating and the velocity of the blast wave. Results are compared to numerical simulations. These show how blast wave pressure is initially very large (more than 100 Mbar), but it decreases very rapidly during propagation.
Multiple herbicide classes–resistant (MHCR) kochia poses a serious concern for producers in the Central Great Plains, including western Kansas. Greenhouse and field experiments were conducted at Kansas State University Research and Extension Centers near Hays and Garden City, KS, to evaluate pyridate-based postemergence herbicide mixtures for controlling MHCR kochia. One previously confirmed MHCR population (resistant to atrazine, glyphosate, dicamba, and fluroxypyr) and a susceptible (SUS) kochia population were tested in a greenhouse study. The kochia population at Hays field site was resistant to atrazine, dicamba, and glyphosate, whereas the kochia population at the Garden City site was resistant to atrazine and glyphosate. Colby’s analysis revealed synergistic interactions when pyridate was mixed with atrazine, dicamba, dichlorprop-p, fluroxypyr, glyphosate, or halauxifen/fluroxypyr and resulted in ≥94% control and shoot dry-biomass reduction of MHCR kochia in a greenhouse study. Similarly, synergistic interactions were observed for MHCR kochia control in fallow field studies at both sites when pyridate was mixed with glyphosate or atrazine. Kochia control was increased from 26% to 90% with the application of glyphosate + pyridate and from 28% to 95% with atrazine + pyridate at both sites as compared to separate applications of glyphosate or atrazine. This is the first report for such a strong synergistic effect for both glyphosate and atrazine mixtures with pyridate on a weed resistant to both. All other pyridate-based herbicide mixtures showed an additive interaction and resulted in better control of MHCR kochia (87% to 100%) as compared to their individual applications (23% to 92%) across both sites except 2,4-D. These results suggest that pyridate can play a crucial role in various postemergence herbicide mixtures for effective control of MHCR kochia.
Volunteer corn (Zea mays L.) is a competitive weed in corn-based cropping systems. Scientific literature does not exist about the water use of volunteer corn grown in different crops and irrigation systems. The objectives of this study were to characterize the growth and evapotranspiration (ETa) of volunteer corn in corn, soybean [Glycine max (L). Merr.], and sorghum [Sorghum bicolor (L.) Moench] under center-pivot irrigation (CPI) and subsurface drip irrigation (SDI) systems. Field experiments were conducted in south-central Nebraska in 2021 and 2022. Soil moisture sensors were installed at depths of 0 to 0.30, 0.30 to 0.60, and 0.60 to 0.90 m to track soil water balance and quantify seasonal total ETa. Corn was the most competitive, as volunteer corn had the lowest biomass, leaf area, and plant height compared with the fallow. Soybean was the least competitive with volunteer corn, as the plant height, biomass, and leaf area of volunteer corn in soybean were similar to fallow at 15, 30, 45, and 60 d after transplanting (DATr). Averaged across crop treatments, irrigation type did not affect volunteer corn growth at 15 to 45 DATr. Soil water depletion and ETa were similar across crop treatments with and without volunteer corn, as water was not a limiting factor in this study. The ETa of volunteer corn was the highest in soybean (623 mm), followed by sorghum (622 mm), and corn (617 mm) under CPI. The SDI had higher irrigation efficiency, because without affecting crop yield, it had 3%, 6%, and 8% lower ETa in soybean (605 mm), sorghum (585 mm), and corn (571 mm), respectively. Although soil water use did not differ with volunteer corn infestation, a soybean yield loss of 27% was observed, which suggests that volunteer corn may not compete for moisture under fully irrigated conditions; however, it can impact the crop yield potential due to competition for factors other than soil moisture.
Cannabinoid Hyperemesis Syndrome (CHS) is distinguished by a pathognomonic cyclic pattern of hyperemesis characterized by recurring episodes of severe vomiting every few weeks to months, as well as obsessive thoughts and compulsive behavior, such as a proclivity to take frequent hot baths or showers. It is largely accepted as the most commonly used illicit drug in the United States, with estimates ranging from 42% to 46% lifetime consumption. Despite greater awareness of CHS, practitioners continue to lack comprehension, resulting in an unfortunate delay in patient identification and treatment.
Objectives
The aim of this article is to bring attention to CHS in order to enable clinicians, and more specifically, addiction medicine specialists and psychiatrists, to diagnose it as quickly as possible and thus avoid unnecessary additional invasive examinations and investigations. This will save the patient’s time, prevent financial burdens and mental health stresses, and increase their overall quality of life.
Methods
A thorough screening and data extraction of the relevant articles was conducted using PubMed, Cochrane, and Embase. Databases were used to search for articles on CHS published between January 2021 and September 2023, yielding relevant articles. Keywords used were “hyperemesis”, “cyclical vomiting,” “cannabis” and “cannabinoid”.
Results
We present a case of 20-year-old teens who came to emergency with severe dehydration and vomiting of more than 40 episodes at home. He had multiple admissions for abdominal pain, nausea, and vomiting in the past and was evaluated and diagnosed with gastritis, PUD, and H. pylori infection. A more detailed medical history revealed a frequent use of cannabis over the past few years and symptoms manifestation and worsening is associated with the use of cannabis. After the complete cessation of cannabis, there have been no new symptomatic episodes reported in the patient and the patient is stable clinically.
Conclusions
Cannabinoid Hyperemesis Syndrome (CHS) is a serious health hazard that requires immediate discovery and treatment. Despite the widespread use of cannabis, CHS is often misdiagnosed, resulting in unnecessary medical treatments and complications for patients. Given their special knowledge of linking chronic cannabis use to this syndrome, this case report and literature review highlight the critical role of addiction medicine experts and psychiatrists in quickly detecting and treating CHS. Early detection and treatment, particularly complete cannabis abstinence, are critical in alleviating symptoms, minimizing recurrent hospitalizations, and ultimately improving patients’ overall quality of life.
Yoga has been demonstrated to have a range of beneficial effects on individuals with substance use disorders, including opioid use disorders. We initiated a randomized clinical trial to find out the efficacy of add-on yoga among patients with opioid dependence stabilized on treatment to find out whether it led to improvement in sleep and quality of life. However, the rate of enrolment into the study was quite low.
Objectives
In this interim analysis, we present the preliminary data on the reasons for non-enrolment in the yoga trial.
Methods
The single-centre trial involved 1:1 randomization of patients with opioid dependence stabilized on medications (naltrexone or buprenorphine) for a period of at least 4 weeks into two groups (add-on yoga or wait-list control). The yoga included asanas and panchakosha meditation, taught for a period of 7 days and to be practiced by the participants for a period of 12 weeks. We recorded the reasons for non-participation among those who did not participate and asked them questions about their views on yoga.
Results
Of the 310 patients recruited between August 2022 and July 2023 (99.7% male, mean age 34 years, 56.5% married), 255 (82.3%) could not be enrolled in the trial. The most common reasons for non-enrolment were not having time for training (n = 206, 80.8%), not having time for doing yoga (n = 180, 70.6%), not having a smartphone for continued training or contact (n = 31, 12.2%), distance from the center (n = 17, 5.5%) do not feel the need for yoga (n = 16, 5.2%), injury or disability (n = 9, 3.5%), old age or medical condition (n = 7, 2.7%), already doing gym exercises (n = 7, 2.7%), nature of job (n = 5, 2.0%), do not have knowledge of yoga (n = 5, 2.0%), and do not think yoga would be useful (n = 4, 1.6%). Among those who could not be enrolled, 35.1% reported doing yoga sometime in the past, and 21.6% reported that at least one of the family members did yoga. When asked whether they would be interested if yoga was available online, 16 (5.2%) responded ‘yes’ and 45 (14.5%) responded ‘maybe’.
Conclusions
Expressed time constraints may be an important factor deterring patients with opioid dependence from engaging in yoga as an add-on yoga. There are other reasons as well that may deter patients from such an intervention. The findings should be seen in the light of the limitation of a single medically oriented center, and patients already stabilized on treatment.
Depression is a widespread problem that affects individuals of all ages. This study looks at the use of omega-3 polyunsaturated fatty acids (PUFAs) as an additional therapy for depression in people of different ages. Depression has an impact on everyone, from youth to the elderly, causing therapeutic concerns such as treatment resistance and recurrence. Omega-3 PUFAs, which may be found in fish and flaxseed, are important because of their impact on neurochemistry, inflammation, and neuroprotection. While pharmacotherapy, including antidepressants, has proven beneficial for many, the likelihood of remission and recurrence remains substantial. In recent years, there has been a growing interest in the potential role of omega-3 polyunsaturated fatty acids (n-3 PUFAs) in mitigating depressive symptoms. The primary constituents of n-3 PUFAs are eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Understanding the potential of omega-3 PUFAs across the lifespan can help address the multifaceted challenges posed by depression and improve mental health outcomes for diverse age groups.
Objectives
This review aims to assess the role of omega-3 fatty acids in depression treatment across different age groups: children and adolescents, adults (18–60), and the elderly (60+). It investigates the effectiveness and potential differences in omega-3 supplementation among these age cohorts.
Methods
A comprehensive literature search was conducted from 2003 to 2023 using PubMed, Google Scholar, and EMBASE, using specific keywords. Studies with inadequate age group information or Omega-3 intervention were excluded.
Results
In children and adolescents, several studies indicate a positive association between omega-3 supplementation and improved depressive symptoms. In adults, results are mixed, with some studies showing benefits while others do not. In the elderly, omega-3 PUFAs appear to have a more consistent positive effect on depression. In contrast, a consistent positive association was observed in the geriatric population, suggesting that Omega-3 PUFAs may hold particular promise in the treatment of depression among older adults. However, variations in methodology, dosage, and study populations contribute to these mixed findings.
Conclusions
Omega-3 PUFAs show promise as an adjunct therapy for depression across different age groups. Further research with standardized methodologies and larger sample sizes is needed to clarify their role and establish optimal dosage guidelines. Omega-3 PUFAs should be considered as a potential complement to conventional depression treatments, emphasizing the need for personalized approaches in depression management.
Addiction medicine is becoming more of an issue as addiction-related problems continue to plague people all over the globe, resulting in serious health consequences. Addiction has become increasingly prevalent in recent years, as have addiction-related disorders. For efficient care and improved patient outcomes, this growing pandemic requires early and precise identification. In the field of addiction medicine, artificial intelligence (AI) looks to be a feasible tool. This systematic review examines the current state of research on the use of AI in addiction medicine, including a variety of AI techniques, their efficiency compared to conventional diagnostic methods, and their potential influence on addiction therapy. While AI has great potential for transforming addiction treatment, further research is needed to assess its use fully.
Objectives
The objective of this review is to assess the current state of research on the use of artificial intelligence in addiction medicine, focusing on its diagnostic efficacy and potential for revolutionizing addiction therapy.
Methods
To evaluate the effectiveness of AI in addiction medicine, we conducted an extensive search of the PubMed database. Our search encompassed articles published in the English language from January 2013 to March 2023. Inclusion criteria encompassed studies reporting the utilization of AI for addiction diagnosis in human patients.
Results
The initial PubMed search produced 100 papers, of which 15 were included after meticulous analysis and screening. These studies assessed diverse types of data, including patient records and behavioral patterns, employing various AI techniques, such as machine learning and deep learning. The findings indicate that AI can accurately and swiftly identify addiction-related issues, boasting high sensitivity and specificity rates. Additionally, AI demonstrates potential in identifying specific addiction subtypes and forecasting patient outcomes. Nevertheless, these studies also underscore certain limitations of AI, such as the requirement for extensive data and susceptibility to overfitting.
Conclusions
Artificial intelligence holds the potential to revolutionize addiction medicine by enabling faster and more precise diagnostics, pinpointing specific addiction subtypes, and predicting patient outcomes. However, further research is imperative to validate AI’s efficacy across diverse patient populations and address challenges related to data accessibility, communication, and integration into clinical practice.
The neuropsychiatric morbidities associated with post-COVID status are important public health issues. The range and severity of morbidity varies with the type of clinical setting and time of assessment. There are limited studies on the long-term persistence of the post-COVID neuropsychiatric symptoms (PCNS). Hence, this study aims to determine the proportion of persistent PCNS after approximately 2 years of COVID and to find any risk factors for persistent PCNS.
Methods
This study was a cross-sectional study of randomly selected 2,281 individuals aged 18–60 years, currently living in the community, who were RT-PCR positive for COVID-19 from the National Institute of Mental Health and Neurosciences (NIMHANS) laboratory (at least 4 weeks before intake) from a period of 1 June 2020 to 31 March 2022. Among them, 927 individuals who met the study criteria were screened for PCNS through telephone interviews using a validated PCNS screening tool comprising sociodemographic details, life events inventory and 20 questions to assess for PCNS. 196 individuals who came positive for PCNS were further evaluated by in-person or web-based interviews with Structured Clinical Interviews for DSM–5-Research Version and World Health Organization-Post-COVID Case Report Form for persistent PCNS. Descriptive statistics, Chi2 test, Mann–Whitney U Test, and Binary logistic regression analysis were used for data analysis. The Institutional Ethics Committee approved this study.
Results
The median age of study participants was 34 years, and 51.3% were female. 68 out of 196 participants (34.7%) had persistent PCNS approximately 2 years (23.84 months) after COVID-19 infection. Chronic fatigue (10.2%), depression (6.1%), cognitive symptoms (4%), hyposmia (3.6%), hypogeusia (3.6%), anxiety (2.5%), panic disorder (2.5%) and insomnia (2%) are the main persistent symptoms. The median age of the participants with persisted PCNS (40 years) is higher compared with the median age of the participants without persisted PCNS (34 years) [Mann–Whitney U = 5,225.0, P = 0.021]. Even though significant associations were found between the development of PCNS after 4 weeks of COVID and female gender, symptomatic COVID-19, severity of COVID-19 (oxygen supplementation), hospital admission, total number of times of COVID-19, and presence of life events, this association were not found with persistence of PCNS at 2 years.
Conclusion
This study revealed that one-third of the individuals with PCNS had persistent symptoms after 2 years. Chronic fatigue is the most common persistent PCNS. Middle-aged and above age groups were found to be a risk factor for persistent PCNS.
Twelve lacustrine sediment samples from a relict lake in the Kalla Glacier valley were co-dated using AMS radiocarbon (14C) and infrared stimulated luminescence (IRSL) dating methods. In general, the radiocarbon ages of bulk organic matter were older by a minimum of 1500 years compared to (age depth) modeled luminescence ages after fading corrections. This is observed for the first time in the lake sediments of High Himalayan Crystalline zone. A combination of lipid n-alkane data, Raman spectra and geochemical proxies suggested that this was due to ancient organic carbon (OCancient) that is a mixture of pre-aged (OCpre-aged) and petrogenic (OCpetro) organic carbon within older glacial moraine debris that served as sediment source to the lake. Raman spectra suggest the presence of moderate to highly graphitized OCpetro in all the profile samples. The OCpetro contributed 0.064 ± 0.032% to the sediment and the lake stored 2.5 ± 0.7 Gg OCpetro at variable rates during the last 16 kyr, with the mean burial flux 160 kg OCpetro yr−1. This study implies (1) employing another independent dating method in addition to radiocarbon method using bulk sediment organic matter, if the carbon content is low, to observe any discrepancy, and (2) a need to investigate on the fate of OCpetro as many such small lakes become relict in this region.
India is going through a rapid socio-economic transition resulting in considerable changes in dietary patterns and nutrition levels among different sections of the population. Despite several policy initiatives to combat malnutrition (Ministry of Women and Child Development, n.d.) over the past more than four decades, the level of malnutrition in India remains abysmally high. Malnutrition was the top cause of death and disability in India in 2017, followed by dietary risks, including poor diet choices, according to the 2017 Global Burden of Disease study (Institute for Health Metrics and Evaluation [IHME], 2018). The groups at the greatest risk of malnutrition are children, adolescents, and women. According to the 2020 Global Nutrition Report, every second child under five years of age in India is malnourished in some form or the other, with a prevalence of wasting being 21 per cent and stunting being 38 per cent – both figures notably greater than the than the average for Asia, where the wasting level is over 9 per cent and stunting level 23 per cent (Development Initiatives, 2020). Additionally, 36 per cent of children under five years of age are underweight, while 2 per cent are overweight (International Institute for Population Sciences [IIPS] and ICF International, 2017). A poor nutritional status, particularly in early life, can have lifelong consequences on physical and psychological well-being and can also impair long-term employment opportunities (Black et al., 2013).
The proportion of under-nutrition among women of reproductive ages declined from 36 per cent in 2005–06 to 23 per cent in 2015–16; at the same time, the proportion of over-nourished (overweight or obese) women increased from 13 per cent to 21 per cent. Maternal under-nutrition contributes to foetal growth restriction, which increases the risk of neonatal deaths and, for survivors, stunting by two years of age (Black et al., 2013), thus passing on the burden of under-nutrition to the next generation.
School-age children and adolescents, too, are affected by under-nutrition and over-nutrition, but they failed to gain attention until the recent past; women and child health, particularly the health of children below the age of five years, had been the focus of researchers and policymakers all these years. According to a study on worldwide trends, more children and adolescents aged 5–19 years are moderately or severely underweight than obese (NCD Risk Factor Collaboration [NCD-RisC], 2017).
Low phosphorus use efficiency (PUE) is one of the abiotic factors that hamper yield and production potential in chickpea (Cicer arietinum L.). Higher yield coupled with improved PUE can make this crop more adaptive and competitive to wide cropland area, especially on marginal soils having low-level phosphorus (P). To identify chickpea germplasm lines that assimilate phosphorus more efficiently under P-deficient soils, 288 diverse genotypes of chickpea belonging to reference set were evaluated for yield component traits and PUE under field conditions for two consecutive years at two phosphorus levels (low P – no phosphorus application and high P – phosphorus application at 40 kg/ha). Based on 2-year evaluation of data under high and low P soil conditions, we identified strong correlations for traits like number of primary and secondary branches, number of pods, biological yield and seed yield indicating that these traits can be used as proxy traits for PUE. ICC 6571 was the best performing genotype under low P conditions while ICC 6579 yielded maximum under high P regime. We report 16 genotypes namely ICC 1052, ICC 1083, ICC 1098, ICC 1161, ICC 2072, ICC 4418, ICC 4567, ICC 4991, ICC 5504, ICC 5639, ICC 7413, ICC 8350, ICC 9590, ICC 9702, ICC 11584 and ICC 13357 as phosphorus use efficient genotypes based on their better performance for yield and yield-contributing traits under low P compared to high P conditions. These genotypes can be exploited in future as potential donors for development of phosphorus use efficient chickpea cultivars.
We report the results of our analysis of six gravity-mode pulsating hot subdwarf stars observed in the short cadence mode by Transiting Exoplanet Survey Satellite. We detected at least 10 pulsation periods in each star, searched for multiplets, and used an asymptotic period spacing to identify modes. We used a grid of evolutionary and pulsation models calculated with the MESA and GYRE, along with spectroscopic parameters and modal degree identification, to derive the physical properties of the stars. We checked the relation between the helium content and pulsations and found that no pulsator exists among the extremely helium-rich hot subdwarfs, while the number of detected pulsators in other helium groups increases as the helium content decreases. We found p- and g-mode hot subdwarfs pulsators in all Galactic populations.