Formulations of synergistic microbial consortia for enhanced systemic resistance against Fusarium wilt in cumin.

The study aimed to understand the dynamic interplay between plants and their associated microbes to develop an efficient microbial consortium for managing Fusarium wilt of cumin. A total of 601 rhizospheric and endophytic bacteria and fungi were screened for antagonistic activity against Fusarium oxysporum f.sp. cumini (Foc). Subsequently, ten bacteria and ten fungi were selected for characterizing their growth promotion traits and ability to withstand abiotic stress. Furthermore, a pot experiment was conducted to evaluate the bioefficacy of promising biocontrol isolates-1F, 16B, 31B, and 223B in mono and consortium mode, focusing on disease severity, plant growth, and defense responses in cumin challenged with Foc. Promising isolates were identified as Trichoderma atrobruneum 15F, Pseudomonas sp. 2B, Bacillus amyloliquefaciens 9B, and Bacillus velezensis 32B. In planta, results revealed that cumin plants treated with consortia of 15F, 2B, 9B, and 32B showed highest percent disease control (76.35%) in pot experiment. Consortia of biocontrol agents significantly enhanced production of secondary metabolites and activation of antioxidant-defense enzymes compared to individual strain. Moreover, consortium treatments effectively reduced electrolyte leakage over the individual strain and positive control. The four-microbe consortium significantly enhanced chlorophyll (~ 2.74-fold), carotenoid content (~ 2.14-fold), plant height (~ 1.8-fold), dry weight (~ 1.96-fold), and seed yield (~ 19-fold) compared to positive control in pot experiment. Similarly, four microbe consortia showed highest percent disease control (72.2%) over the positive control in field trial. Moreover, plant growth, biomass, yield, and yield attributes of cumin were also significantly increased in field trial over the positive control as well as negative control.

Accumulation of resveratrol, ferulic acid and iron in seeds confer iron deficiency chlorosis tolerance to a novel genetic stock of peanut (Arachis hypogaea L.) grown in calcareous soils.

Peanut is mostly grown in calcareous soils with high pH which are deficient in available iron (Fe2+) for plant uptake causing iron deficiency chlorosis (IDC). The most pertinent solution is to identify efficient genotypes showing tolerance to limited Fe availability in the soil. A field screening of 40 advanced breeding lines of peanut using NRCG 7472 and ICGV 86031 as IDC susceptible and tolerant checks, respectively, was envisaged for four years. PBS 22040 and 29,192 exhibited maximum tolerance while PBS 12215 and 12,185 were most susceptible. PBS 22040 accumulated maximum seed resveratrol (5.8 ± 0.08 ppm), ferulic acid (378.6 ± 0.31 ppm) and Fe (45.59 ± 0.41 ppm) content. Enhanced chlorophyll retention (8.72-9.50 µg ml-1), carotenoid accumulation (1.96-2.08 µg ml-1), and antioxidant enzyme activity (APX: 35.9-103.9%; POX: 51- 145%) reduced the MDA accumulation (5.61-9.11 µM cm-1) in tolerant lines. The overexpression of Fe transporters IRT1, ZIP5, YSL3 was recorded to the tune of 2.3-9.54; 1.45-3.7; 2.20-2.32- folds respectively in PBS 22040 and 29,192, over NRCG 7472. PBS 22040 recorded the maximum pod yield (282 ± 4.6 g/row), hundred kernel weight (55 ± 0.7 g) and number of pods per three plants (54 ± 1.7). The study thus reports new insights into the roles of resveratrol, ferulic acid and differential antioxidant enzyme activities in imparting IDC tolerance. PBS 22040, being the best performing line, can be the potent source of IDC tolerance for introgression in high yielding but susceptible genotypes under similar edaphic conditions. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-023-01321-9.

Effects of Confounding Bias in Coronavirus Disease 2019 (COVID-19) and Influenza Vaccine Effectiveness Test-Negative Designs Due to Correlated Influenza and COVID-19 Vaccination Behaviors.

BACKGROUND: The test-negative design is commonly used to estimate influenza and coronavirus disease 2019 (COVID-19) vaccine effectiveness (VE). In these studies, correlated COVID-19 and influenza vaccine behaviors may introduce a confounding bias where controls are included with the other vaccine-preventable acute respiratory illness (ARI). We quantified the impact of this bias on VE estimates in studies where this bias is not addressed. METHODS: We simulated study populations under varying vaccination probabilities, COVID-19 VE, influenza VE, and proportions of controls included with the other vaccine-preventable ARI. Mean bias was calculated as the difference between estimated and true VE. Absolute mean bias in VE estimates was classified as low (<10%), moderate (10% to <20%), and high (≥20%). RESULTS: Where vaccination probabilities are positively correlated, COVID-19 and influenza VE test-negative studies with influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ARI controls, respectively, underestimate VE. For COVID-19 VE studies, mean bias was low for all scenarios where influenza represented ≤25% of controls. For influenza VE studies, mean bias was low for all scenarios where SARS-CoV-2 represented ≤10% of controls. Although bias was driven by the conditional probability of vaccination, low VE of the vaccine of interest and high VE of the confounding vaccine increase its magnitude. CONCLUSIONS: Where a low percentage of controls is included with the other vaccine-preventable ARI, bias in COVID-19 and influenza VE estimates is low. However, influenza VE estimates are likely more susceptible to bias. Researchers should consider potential bias and its implications in their respective study settings to make informed methodological decisions in test-negative VE studies.

MixEHR-Guided: A guided multi-modal topic modeling approach for large-scale automatic phenotyping using the electronic health record.

Electronic Health Records (EHRs) contain rich clinical data collected at the point of the care, and their increasing adoption offers exciting opportunities for clinical informatics, disease risk prediction, and personalized treatment recommendation. However, effective use of EHR data for research and clinical decision support is often hampered by a lack of reliable disease labels. To compile gold-standard labels, researchers often rely on clinical experts to develop rule-based phenotyping algorithms from billing codes and other surrogate features. This process is tedious and error-prone due to recall and observer biases in how codes and measures are selected, and some phenotypes are incompletely captured by a handful of surrogate features. To address this challenge, we present a novel automatic phenotyping model called MixEHR-Guided (MixEHR-G), a multimodal hierarchical Bayesian topic model that efficiently models the EHR generative process by identifying latent phenotype structure in the data. Unlike existing topic modeling algorithms wherein the inferred topics are not identifiable, MixEHR-G uses prior information from informative surrogate features to align topics with known phenotypes. We applied MixEHR-G to an openly-available EHR dataset of 38,597 intensive care patients (MIMIC-III) in Boston, USA and to administrative claims data for a population-based cohort (PopHR) of 1.3 million people in Quebec, Canada. Qualitatively, we demonstrate that MixEHR-G learns interpretable phenotypes and yields meaningful insights about phenotype similarities, comorbidities, and epidemiological associations. Quantitatively, MixEHR-G outperforms existing unsupervised phenotyping methods on a phenotype label annotation task, and it can accurately estimate relative phenotype prevalence functions without gold-standard phenotype information. Altogether, MixEHR-G is an important step towards building an interpretable and automated phenotyping system using EHR data.

An expedient ion chromatography based method for high-throughput analysis of phytic acid in groundnut kernels.

A study was made to expedite ion chromatography method using IonPac analytical column and self-regenerating anion suppressor for phytic acid determination in groundnut seeds and compared with a widely adopted spectrophotometric method based on enzymatic hydrolysis. The Ion Chromatography method equipped with AG11 guard and AS11 analytical columns in isocratic mode using 65 mM NaOH mobile phase at 1 mL min-1 flow rate showed a sharp peak for phytic acid with a retention time of 2.42 ± 0.2 min. The peak area was plotted v/s concentration showed linearity with an R2 value of 0.997, detection limit of 0.028 mg L-1 and recovery of 98% as against R2 value of 0.988 and detection limit of 0.065 mg L-1 in the spectrophotometric method. The study demonstrates that Ion Chromatography method was more accurate with a better detection limit than spectrophotometry. Also, this method provides robust handling with lesser reagent requirements due to combined eluent generation and self-regenerating suppression. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-022-05527-9.

Bayesian latent multi-state modeling for nonequidistant longitudinal electronic health records.

Large amounts of longitudinal health records are now available for dynamic monitoring of the underlying processes governing the observations. However, the health status progression across time is not typically observed directly: records are observed only when a subject interacts with the system, yielding irregular and often sparse observations. This suggests that the observed trajectories should be modeled via a latent continuous-time process potentially as a function of time-varying covariates. We develop a continuous-time hidden Markov model to analyze longitudinal data accounting for irregular visits and different types of observations. By employing a specific missing data likelihood formulation, we can construct an efficient computational algorithm. We focus on Bayesian inference for the model: this is facilitated by an expectation-maximization algorithm and Markov chain Monte Carlo methods. Simulation studies demonstrate that these approaches can be implemented efficiently for large data sets in a fully Bayesian setting. We apply this model to a real cohort where patients suffer from chronic obstructive pulmonary disease with the outcome being the number of drugs taken, using health care utilization indicators and patient characteristics as covariates.

Metabolic profiling for dissection of late leaf spot disease resistance mechanism in groundnut.

Late leaf spot (LLS) caused by fungi Passalora personata is generally more destructive and difficult to control than early leaf spot. The aim of this study was to decipher biochemical defense mechanism in groundnut genotypes against P. personata by identifying resistance specific biomarkers and metabolic pathways induced during host-pathogen interaction. Metabolomics of non-infected and infected leaves of moderately resistant (GPBD4 and ICGV86590), resistant (KDG128 and RHRG06083) and susceptible (GG20, JL24 and TMV2) genotypes was carried out at 5 days after infection (65 days after sowing). Non-targeted metabolite analysis using GC-MS revealed total 77 metabolites including carbohydrates, sugar alcohols, amino acids, fatty acids, polyamines, phenolics, terpenes and sterols. Variable importance in projection (VIP) measure of partial least squares-discriminant analysis (PLS-DA) showed that resistant and moderately resistant genotypes possessed higher intensities of ribonic acid, cinnamic acid, malic acid, squalene, xylulose, galactose, fructose, glucose, ß-amyrin and hydroquinone while susceptible genotypes had higher amount of gluconic acid 2-methoxime, ribo-hexose-3-ulose and gluconic acid. Heat map analysis showed that resistant genotypes had higher intensities of ß-amyrin, hydroquinone in non-infected and malic acid, squalene, putrescine and 2,3,4-trihydroxybutyric acid in infected leaves. Dendrogram analysis further separated resistant genotypes in the same cluster along with infected moderately resistant genotypes. The most significant pathways identified are: linoleic acid metabolism, flavone and flavonol biosynthesis, cutin, suberin and wax biosynthesis, pentose and glucuronate interconversions, starch and sucrose metabolism, stilbenoid biosynthesis and ascorbate and aldarate metabolism. Targeted metabolite analysis further confirmed that resistant genotypes possessed higher content of primary metabolites sucrose, glucose, fructose, malic acid and citric acid. Moreover, resistant genotypes possessed higher content of salicylic, coumaric, ferulic, cinnamic, gallic acid (phenolic acids) and kaempferol, quercetin and catechin (flavonols). Thus metabolites having higher accumulation in resistant genotypes can be used as biomarkers for screening of LSS resistant germplasm. These results unravel that higher amount of primary metabolites leads to stimulate the accumulation of more amounts of secondary metabolites such as phenolic acid, flavanols, stilbenes and terpenoids (squalene and ß-amyrin) biosynthesis which are ultimately involved in defense mechanism against LLS pathogen. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-00985-5.

A systematic review of aberration detection algorithms used in public health surveillance.

The algorithms used for detecting anomalies have evolved substantially over the last decade to take advantage of advances in informatics and to accommodate changes in surveillance data. We identified 145 studies since 2007 that evaluated statistical methods used to detect aberrations in public health surveillance data. For each study, we classified the analytic methods and reviewed the evaluation metrics. We also summarized the practical usage of the detection algorithms in public health surveillance systems worldwide. Traditional methods (e.g., control charts, linear regressions) were the focus of most evaluation studies and continue to be used commonly in practice. There was, however, an increase in the number of studies using forecasting methods and studies applying machine learning methods, hidden Markov models, and Bayesian framework to multivariate datasets. Evaluation studies demonstrated improved accuracy with more sophisticated methods, but these methods do not appear to be used widely in public health practice.

Implantless patellar fixation in medial patellofemoral ligament reconstruction.

PURPOSE: The medial patellofemoral ligament (MPFL) acts as primary restraint to lateral patellar dislocation and its rupture has been reported in almost all cases of acute patellar dislocation. Various surgical techniques have been described for MPFL reconstruction, using many femoral and patellar fixation techniques and different grafts. This article details our technique for MPFL reconstruction using semitendinosus graft which avoids the use of implant at patellar end. METHODS: Twenty patients (8 males and 12 females) with complaints regarding acute and chronic lateral patellar instability were evaluated and treated by MPFL reconstruction procedure. The mean age of patients was 21 years (range 17-34 years). MPFL reconstruction was performed using semitendinosus graft passing through two parallel, obliquely directed tunnels created in patella. Fixation of graft was done with an interference screw only at the femoral end. Mean follow-up period after intervention was 26.4 months (range 23-30 months). Results were evaluated using Kujala score. RESULTS: All patients gained adequate patellar stability and full arc of motion. No incidence of patella fracture was noted. There were no postoperative complications related to the procedure. There was no recurrence of instability in patella at final follow-up. CONCLUSION: Passing the graft through the tunnels in patella without use of any implant has given excellent functional outcome and moreover has the advantages of less implant-related complications and cost-effectiveness.

Effect of microwave pre-treatment on quality parameters in Indian mustard.

Demand for edible oil from crops like groundnut, mustard and soybean, is increasing and likely to increase further. In this regard, Indian mustard seeds were treated with microwaves (MW), to investigate the possibility of enhancing oil yield and nutritional content. MW pre-treatment was given to the seeds of two Indian mustard varieties i.e. PM21 (V1) and PDZ1 (V2) for 0, 2, 4 and 6 min (H0, H2, H4 and H6 min respectively). MW treatment with increasing exposure time showed a linear reduction in the glucosinolate and erucic acid content with concomitant increase in oil yield and moisture loss in both the varieties, as evident from correlation and principal component analysis. Antioxidant capacity has increased with the reduction in phytic acid content (1.82) in V2 at 6 min exposure time with respect to untreated control. Free radical scavenging activity was improved with increasing MW treatment in both the varieties. Therefore, from the obtained results, it is advisable to treat mustard seeds with MW before extraction of oil, because it gives a relatively good oil yield, with enhanced nutritional factors. Moreover, microwaving was effective in reducing glucosinolates and erucic acid also.

A population-based analysis of predictors of influenza vaccination uptake in pregnant women: The effect of gestational and calendar time.

Pregnant women are vaccinated against influenza less frequently than other high-risk groups. To design effective vaccination strategies, we must understand how decisions regarding vaccination may vary by trimester and over vaccination campaigns. We used a Cox model indexed by calendar time to estimate the effect of gestational trimester and other factors on vaccination uptake in a large cohort of pregnant women in Catalonia (Spain) during 2008-09 to 2012-13 influenza vaccination campaigns. We analyzed 247,316 pregnancies. Vaccination coverage was 3.7%, 5.2%, 4.8%, 5.6% and 4.6% from 2008-09 to 2012-13 seasonal vaccination campaigns and 8.3% for the 2009 pandemic vaccination campaign. Pregnant women previously vaccinated had higher uptake than women not previously vaccinated and the hazard ratios (HRs) comparing these 2 groups decreased from 10, the first day of seasonal campaigns, to 1.3 the last day. During the pandemic campaign, HRs decreased over the course of the campaign from 8.6 to 1.9. Women in second and third trimester had higher uptake than women in first trimester, with HR=2.8 and 2.3, respectively, at the start of seasonal campaigns. Influenza vaccination coverage among this cohort of pregnant women was alarmingly low. Our analysis reveals that gestational and calendar time have distinct and interacting effects on vaccination uptake; women in their second trimester and third trimester and previously vaccinated were more prone to be vaccinated, but this effect wanes as the influenza season progresses.

Life Cycle Analysis of Bitumen Transportation to Refineries by Rail and Pipeline.

Crude oil is currently transported primarily by pipelines and rail from extraction sites to refineries around the world. This research evaluates energy use and greenhouse gas (GHG) emissions for three scenarios (synthetic crude oil and dilbit with and without diluent return) in which 750 000 bpd of Alberta's bitumen is transported 3000 km to determine which method has a lower environmental impact. Each scenario has a pipeline and rail pathway, and the dilbit without diluent return scenario has an additional heated bitumen pathway, which does not require diluent. An Excel based bottom-up model is developed using engineering first-principles to calculate mass and energy balances for each process. Results show that pipeline transportation produced between 61% and 77% fewer GHG emissions than by rail. The GHG emissions decreased by 15% and 73% for rail and pipelines as the capacity increased from 100 000 to 800 000 bpd. A Monte Carlo simulation was performed to determine the uncertainty in the emissions and found that the uncertainty was larger for pipelines (up to ±73%) and smaller for rail (up to ±28%). The uncertainty ranges do not overlap, thus confirming that pipelines have lower GHG emissions, which is important information for policy makers conducting pipeline reviews.

Towards probabilistic decision support in public health practice: predicting recent transmission of tuberculosis from patient attributes.

OBJECTIVE: Investigating the contacts of a newly diagnosed tuberculosis (TB) case to prevent TB transmission is a core public health activity. In the context of limited resources, it is often necessary to prioritize investigation when multiple cases are reported. Public health personnel currently prioritize contact investigation intuitively based on past experience. Decision-support software using patient attributes to predict the probability of a TB case being involved in recent transmission could aid in this prioritization, but a prediction model is needed to drive such software. METHODS: We developed a logistic regression model using the clinical and demographic information of TB cases reported to Montreal Public Health between 1997 and 2007. The reference standard for transmission was DNA fingerprint analysis. We measured the predictive performance, in terms of sensitivity, specificity, negative predictive value, positive predictive value, the Receiver Operating Characteristic (ROC) curve and the Area Under the ROC (AUC). RESULTS: Among 1552 TB cases enrolled in the study, 314 (20.2%) were involved in recent transmission. The AUC of the model was 0.65 (95% confidence interval: 0.61-0.68), which is significantly better than random prediction. The maximized values of sensitivity and specificity on the ROC were 0.53 and 0.67, respectively. CONCLUSIONS: The characteristics of a TB patient reported to public health can be used to predict whether the newly diagnosed case is associated with recent transmission as opposed to reactivation of latent infection.

Weather warnings predict fall-related injuries among older adults.

BACKGROUND: weather predictions are a useful tool for informing public health planning and prevention strategies for non-injury health outcomes, but the association between winter weather warnings and fall-related injuries has not been assessed previously. OBJECTIVE: to examine the association between fall-related injuries among older adults and government-issued winter weather warnings. METHODS: using a dynamic cohort of individuals ≥65 years of age who lived in Montreal between 1998 and 2006, we identified all fall-related injuries from administrative data using a validated set of diagnostic and procedure codes. We compared rates of injuries on days with freezing rain or snowstorm warnings to rates observed on days without warnings. We also compared the incidence of injuries on winter days to non-winter days. All analyses were performed overall and stratified by age and sex. RESULTS: freezing rain alerts were associated with an increase in fall-related injuries (incidence rate ratio [IRR] = 1.20, 95% confidence interval [CI]: 1.08-1.32), particularly among males (IRR = 1.31, 95% CI: 1.10-1.56), and lower rates of injuries were associated with snowstorm alerts (IRR = 0.89, 95% CI: 0.80-0.99). The rate of fall-related injuries did not differ seasonally (IRR = 1.00, 95% CI: 0.97-1.03). CONCLUSIONS: official weather warnings are predictive of increases in fall-related injuries among older adults. Public health agencies should consider using these warnings to trigger initiation of injury prevention strategies in advance of inclement weather.

Method for fabrication and verification of conjugated nanoparticle-antibody tuning elements for multiplexed electrochemical biosensors.

There is a critical need for more accurate, highly sensitive and specific assay for disease diagnosis and management. A novel, multiplexed, single sensor using rapid and label free electrochemical impedance spectroscopy tuning method has been developed. The key challenges while monitoring multiple targets is frequency overlap. Here we describe the methods to circumvent the overlap, tune by use of nanoparticle (NP) and discuss the various fabrication and characterization methods to develop this technique. First sensors were fabricated using printed circuit board (PCB) technology and nickel and gold layers were electrodeposited onto the PCB sensors. An off-chip conjugation of gold NP's to molecular recognition elements (with verification technique) is described as well. A standard covalent immobilization of the molecular recognition elements is also discussed with quality control techniques. Finally use and verification of sensitivity and specificity is also presented. By use of gold NP's of various sizes, we have demonstrated the possibility and shown little loss of sensitivity and specificity in the molecular recognition of inflammatory markers as "model" targets for our tuning system. By selection of other sized NP's or NP's of various materials, the tuning effect can be further exploited. The novel platform technology developed could be utilized in critical care, clinical management and at home health and disease management.

Comparative evaluation of dentinal tubule penetration and push-out bond strength of new injectable hydraulic calcium disilicate based root canal sealer: A single blinded in vitro study.

Objective: To evaluate and compare dentinal tubule penetration and push-out bond strength of BIO-C ION+, AH Plus and NanoSeal-S using Confocal Laser Scanning Microscopy (CLSM) and Universal Testing Machine (UTM). Materials & method: Sixty human mandibular premolars were prepared using ProTaper Gold till F3. Samples were then divided into 3 groups: Group I (n = 20) BIO-C ION + sealer, Group II (n = 20) AH Plus and Group III (n = 20) NanoSeal-S sealer. Groups were then sub-divided into two sub groups: In Subgroup A (n = 10) samples were obturated using single-cone with 0.1 % Rhodamine B dye and in Subgroup B (n = 10) samples were obturated using single cone. The samples were then transversely sectioned into coronal, middle and apical segments, samples in subgroup A & B were then submitted to CLSM analysis and UTM respectively. Results: The Bond Strength data showed following means (MPa): Group I Subgroup B: (BIO-C ION+) coronal (1.64), middle (1.25), apical (0.93); Group II Subgroup B: (AH Plus) coronal (2.20), middle (1.85) apical (1.38) and Group III Subgroup B: (NanoSeal-S) coronal (1.26), middle (0.94), apical (0.58). The dentinal tubule penetration data showed following means: (µm) Group I Subgroup A (BIO-C ION+) coronal (1184.69), middle (997.03), apical (637.26); Group II Subgroup-A AH Plus (864.14) and NanoSeal-S (495.64). Statistical analysis (two-way ANOVA, Tukey's Post Hoc Test) showed significant difference among sealers (p < 0.001) and root canal thirds (p < 0.001). Conclusion: The results of the study concluded that BIO-C ION + sealer showed maximum dentinal tubule penetration and AH Plus demonstrated maximum push-out bond strength.

Harnessing nature's defenders: unveiling the potential of microbial consortia for plant defense induction against Alternaria blight in cumin.

Present study was aimed to develop an efficient microbial consortium for combating Alternaria blight disease in cumin. The research involved isolating biocontrol agents against Alternaria burnsii, characterizing their biocontrol and growth promotion traits, and assessing compatibility. A pot experiment was conducted during rabi season of 2022-2023 to evaluate the bioefficacy of four biocontrol agents (1F, 16B, 31B, and 223B) individually and in consortium, focusing on disease severity, plant growth promotion, and defense responses in cumin challenged with A. burnsii. Microbial isolates 1F, 16B, 31B, and 223B significantly inhibited A. burnsii growth in dual plate assays (~ 86%), displaying promising biocontrol and plant growth promotion activities. They were identified as Trichoderma afroharzianum 1F, Aneurinibacillus aneurinilyticus 16B, Pseudomonas lalkuanensis 31B, and Bacillus licheniformis 223B, respectively. The excellent compatibility was observed among all selected biocontrol agents. Cumin plants treated with consortia of 1F + 16B + 31B + 223B showed least percent disease index (32.47%) and highest percent disease control (64.87%). Consortia of biocontrol agents significantly enhanced production of secondary metabolites (total phenol, flavonoids, antioxidant, and tannin) and activation of antioxidant-defense enzymes (POX, PPOX, CAT, SOD, PAL, and TAL) compared to individual biocontrol treatment and infected control. Moreover, consortium treatments effectively reduced electrolyte leakage over the individual biocontrol agent and infected control treatment. The four-microbe consortium significantly enhanced chlorophyll (154%), carotenoid content (88%), plant height (78.77%), dry weight (72.81%), and seed yield (104%) compared to infected control. Based on these findings, this environmentally friendly four-microbe consortium may be recommended for managing Alternaria blight in cumin.

Is Restoration of Sagittal Spinopelvic Parameters Necessary in Spinal Tuberculosis of Lumbar and Lumbosacral Spine? Conservative versus Operative Management.

BACKGROUND: The relationship of spinopelvic parameters with spondylolisthesis is widely explored. However, there is scarce evidence on correlation of tuberculosis of lumbar spine with respect to spinopelvic harmony. The current study aims to find the association between functional outcomes and spinopelvic parameters in lumbar spine tuberculosis treatment. METHODS: A total of 47 patients with active tuberculosis confined to lumbar spine were prospectively analyzed and divided into 2 groups according to mode of intervention. Group A included 26 operatively managed patients and group B had 21 conservatively managed cases. Functional parameters comprising Oswestry Disability Index (ODI) and Visual Analog Scale (VAS) along with spinopelvic radiologic parameters (pelvic incidence [PI], pelvic tilt [PT], sacral slope [SS], lumbar lordosis [LL], PI-LL, sagittal vertical axis) in both groups were analyzed at 0 and 6 months of follow-up. RESULTS: Both the groups showed significant improvement from initial presentation to final follow-up in ODI (Group A: 85.4 ± 12.1-12.3 ± 3.2, P = 0.02; Group B: 82.5 ± 10.06-36.8 ± 11.9, P = 0.04) and VAS (Group A: 8.1 ± 1.2-1.4 ± 0.9, P = 0.02; Group B: 8.5 ± 0.09-3.5 ± 1.1, P = 0.02). Statistically significant (P < 0.05) difference was observed in both functional outcome parameters between the 2 groups at 2-month and 6-month follow-up, compared with nonsignificant difference (P > 0.05) at presentation. Better improvements of spinopelvic parameters of PT, SS, LL, PI-LL were observed in Group A and in both groups the difference of these parameters correlated with differences of functional outcome parameters, though PI showed no correlation. CONCLUSIONS: The spinopelvic parameters played significant role in functional outcome. There is better functional outcome when LL is adequately restored. Surgical correction offered betterment of spinopelvic parameters like PT, SS, an sagittal vertical axis, which in turn leads to improvement in functional outcome.

Healing Assessment of Spinal Tuberculosis: A Systematic Review.

OBJECTIVE: Deciding the healing end point in spinal tuberculosis (STB) remains a controversial topic. The current systematic review aims to address the controversy existing in the literature to find a comprehensive method to assess healing in STB. METHODS: A thorough literature search was carried out for studies with the assessment of healing parameters in STB. Data extraction was carried out manually, which included study characteristics and healing criteria evaluated in each study. RESULTS: Qualitative analysis of 8 included studies showed that healing parameters were described in 3 domains: clinical, hematologic, and radiologic response of the patient to antitubercular chemotherapy. Each domain included various individual parameters, with clinical and radiologic assessment criteria being used in most of the studies. Improvement in terms of pain, constitutional symptoms, weight gain, neurology; variation in erythrocyte sedimentation rate and C-reactive protein; and changes in radiography, magnetic resonance imaging, and positron emission tomography/computed tomography were found to be promising predictors in the assessment of healing. CONCLUSIONS: Radiologic response parameters emerged as the maximally used criteria to assess healing in STB. However, in the absence of any statistical analysis and an observed lag in radiologic response, the cumulative effect of all the parameters in 3 domains (clinical, hematologic, and radiologic) can be used to declare a spinal tubercular lesion nonhealing, healing, or healed.