Group Testing Research Articles

Diagnostic accuracy of the point-of-care standard G6PD test™ (SD Biosensor) for glucose-6-phosphate dehydrogenase deficiency: a systematic review and meta-analysis

BackgroundGlucose-6-Phosphate Dehydrogenase deficiency (G6PDd) is a common genetic enzymopathy that can induce haemolysis triggered by various factors, including some anti-malarial drugs. Although many Point-of-Care (PoC) tests, such as Standard G6PD™ are available to detect G6PDd, its pooled diagnostic test accuracy (DTA) remains unknown.MethodsTo estimate the DTA of StandG6PD-BS at various thresholds of G6PDd, a systematic review with a DTA meta-analysis were conducted, searching EMBASE, MEDLINE, and SciELO databases up to April 4, 2024.The included studies were those that measured G6PD activity using StandG6PD-BS (reference test) and spectrophotometry (gold standard) in patients suspected of having G6PDd. The risk of bias (RoB) of the studies was assessed using the QUADAS-2 tool and the certainty of evidence (CoE) with the GRADE approach. For the estimation of within-study DTA, a random-effect bivariate meta-analysis was performed to determine the pooled sensitivity and specificity for 30%, 70%, and 80% enzyme levels’ thresholds, and a graphical analysis of the heterogeneity using crosshair and Confidence Regions on receiver operating characteristic (ROC) space plots.ResultsAfter screening 2496 reports, four studies were included with 7864 participants covering all thresholds. Two studies had high RoB in QUADAS-2 domains 2 and 3, and the others had low RoB, with low, moderate, and high heterogeneity at the 30%, 70%, and 80% thresholds, respectively. The pooled sensitivity was 99.1%, 95.7%, and 90% for 30%, 70%, and 80% thresholds, respectively. The pooled specificity was 97.4%; 92.9%; and 89.0% for 30%, 70%, and 80% thresholds, respectively.ConclusionStandG6PD-BS is a PoC test with high sensitivity and specificity to detect G6PDd at different thresholds.

Pooling sputum samples for the Xpert MTB/RIF Ultra assay: a sensitive and effective screening strategy

The sensitivity of Xpert MTB/RIF (Xpert) pooled testing is limited for diagnosing patients with paucibacillary tuberculosis (TB). We assessed whether pooled testing with Xpert MTB/RIF Ultra (Ultra) can be a sensitive and effective approach for mass TB screening. Conserved, frozen sputum samples, previously confirmed as positive or negative for Mycobacterium tuberculosis by individual Xpert assays, were mixed in pools of 4, 8, and 16 and then tested using Ultra. Each pool contained a single positive sample with varying mycobacterial loads. We then simulated TB screening at prevalence ranges of 0.2-1.0% and calculated the cartridges required per case detected at different pool sizes. The overall sensitivity of Ultra pooled testing was high (88.9%, 75.9-96.3). Sensitivity was greater in pools in which the positive sample had a high mycobacterial load compared to those with scant bacilli. As prevalence increased, the optimal pool size and benefits of pooled testing declined, but a pool size of 8 resulted in at least 80% cartridge savings with the highest simulated prevalence. Sputum pooling using Ultra could be a sensitive and effective strategy for TB screening. However, broad TB screening in communities with limited resources will require new, lower-cost, high-throughput screening tools, perhaps based on non-sputum specimens.

Impacts of testing and immunity acquired through vaccination and infection on covid-19 cases in Massachusetts elementary and secondary students

BackgroundDuring the 2021–22 academic year, Massachusetts supported several in-school testing programs to facilitate in-person learning. Additionally, COVID-19 vaccines became available to all school-aged children and many were infected with SARS-CoV-2. There are limited studies evaluating the impacts of these testing programs on SARS-CoV-2 cases in elementary and secondary school settings. The aim of this state-wide, retrospective cohort study was to assess the impact of testing programs and immunity on SARS-CoV-2 case rates in elementary and secondary students.MethodsCommunity-level vaccination and cumulative incidence rates were combined with data about participation in and results of in-school testing programs (test-to-stay, pooled surveillance testing). School-level impacts of surveillance testing programs on SARS-CoV-2 cases in students were estimated using generalized estimating equations within a target trial emulation approach stratified by school type (elementary/middle/high). Impacts of immunity and vaccination were estimated using random effects linear regression.ResultsHere we show that among N = 652,353 students at 2141 schools participating in in-school testing programs, surveillance testing is associated with a small but measurable decrease in in-school positivity rates. During delta, pooled testing positivity rates are higher in communities with higher cumulative incidence of infection. During omicron, when immunity from prior infection became more prevalent, the effect reversed, such that communities with lower burden of infection during the earlier phases of the pandemic had higher infection rates.ConclusionsTesting programs are an effective strategy for supporting in-person learning. Fluctuating levels of immunity acquired via natural infection or vaccination are a major determinant of SARS-CoV-2 cases in schools.

Rooftop pools - a problem from an acoustic point of view: how to identify and solve it

There is no standard with specific methods for acoustic testing of rooftop swimming pools in Brazil. On the other hand, although the compatible requirement for impact noise from rooftop leisure environments is not the type of noise generated by swimming pools, it is a current requirement in the Brazilian performance standard. To study the subject, evaluate possible solutions and improve the state of the art, this article brings measurement results for impact noise in the same situation without and with the application of an acoustic solution. The study also presents sound pressure level and vibration measurements in an environment below a swimming pool after the application of the acoustic solution. Vibrations were measured as well in the pool structure and in the slab below, making it possible to identify the vibrational behavior of the pool. Measurements of impact noise took place in a situation where the pool is three floors above the last residential unit to verify the influence of technical slabs. With the measured values in the three situations, it was possible to identify the frequency range for which acoustic solutions should be designed for this type of source and to monitor the effectiveness of different solutions.

An optimized method for AUV trajectory model in benthonic hydrothermal area based on improved slime mold algorithm

The optimization of the desired autonomous underwater vehicle (AUV) trajectory modeling and AUV trajectory tracking control in the benthonic hydrothermal area were studied. In the conventional trajectory tracking model construction methods, the time points were roughly combined with the position points of the planned path, making it difficult to produce a smooth trajectory. Although the spline interpolation method was an ideal option for smooth curves, a great number of points were needed for a complex desired trajectory mode. In response to the demanding requirements of AUV trajectory tracking control in the benthonic hydrothermal area, an under-actuated test platform was first established, and the cubic spline interpolation was adopted to process the preset path points for a smooth desired trajectory. An improved slime mold algorithm (SMA) was put forward to optimize the interpolating points used in the trajectory modeling. The Levy flight technology and the compactness technique to speed up the search process and increase the search accuracy. The simulation experiments were conducted in comparison with the artificial fish swarm algorithm (AFSA), the particle swarm optimization (PSO), and the compact cuckoo search (CCS). The results showed that the improved SMA shortened the search process, effectively avoided the local extreme values, and generated a high-precision desired trajectory model in a shorter time. The pool test also verified the feasibility and effectiveness of the proposed method. The method proposed in this study can satisfy the modeling of benthonic hydrothermal trajectory with a fewer number of nodes, faster search progress and search accuracy.

Needle-Plug/Piston-Based Modular Mesoscopic Design Paradigm Coupled With Microfluidic Device for Point-of-Care Pooled Testing.

Emerging diagnostic scenarios, such as population surveillance by pooled testing and on-site rapid diagnosis, highlight the importance of advanced microfluidic systems for in vitro diagnostics. However, the widespread adoption of microfluidic technology faces challenges due to the lack of standardized design paradigms, posing difficulties in managing macro-micro fluidic interfaces, reagent storage, and complex macrofluidic operations. This paper introduces a novel modular-based mesoscopic design paradigm, featuring a core "needle-plug/piston" structure with versatile variants for complex fluidic operations. These structures can be easily coupled with various microfluidic platforms to achieve truly self-contained microsystems. Incorporated into a "3D extensible" design architecture, the mesoscopic design meets the demands of function integration, macrofluid manipulations, and flexible throughputs for point-of-care nucleic acid testing. Using this approach, an ultra-sensitive nucleic acid detection system is developed with a limit of detection of ten copies of SARS-CoV-2 per mL. This system efficiently conducts large-scale pooled testing from 50 pharyngeal swabs in a tube with an uncompromised sensitivity, enabling a truly "sample-in-answer-out" microsystem with exceptional performance.

Optimizing Disease Surveillance Through Pooled Testing with Application to Infectious Diseases

AbstractPooled (or group) testing has been widely used for the surveillance of infectious diseases of low prevalence. The potential benefits of pooled testing include savings in testing time and costs, reducing false positive tests, and estimating models or making predictions from limited observed data information (e.g., only initial pooled responses). However, realizing these benefits often critically depends on the pool size used. Statistical methods introduced in the literature for optimal pool size determination have been developed mainly to accommodate simpler pooling protocols or perfect diagnostic assays. In this article, we study these issues with the goal of presenting a general optimization technique. We evaluate the efficiency of the estimators of disease prevalence (i.e., the proportion of diseased individuals in a population) while accounting for testing costs. Then, we determine the optimal pool size by minimizing the measures of optimality, such as screening efficiency and estimation efficiency. Our findings are illustrated using data from an ongoing screening application at the Louisiana Department of Health. We show that when a pooling application is properly designed, substantial advantages can be realized. We provide an package and a software application to facilitate the implementation of our optimization techniques. Supplementary materials accompanying this paper appear online.

Firearm injury hospitalizations and handgun purchaser licensing laws: longitudinal evaluation of state-level purchaser licensure requirements on firearm violence, 2000–2016

BackgroundHandgun purchaser licensing (HPL) laws mandate individuals to obtain a license from law enforcement before buying a firearm. Research indicates these laws effectively reduce various forms of fatal firearm violence, including homicides, suicides, and mass shootings. Our study sought to assess the impact of HPL laws on non-fatal firearm violence.MethodsUtilizing the augmented synthetic control method (ASCM), we estimated the average treatment effect on the treated (ATT) resulting from a full repeal of an HPL law in Missouri (2007), a partial repeal in Michigan (2012), and an adoption on HPL law in Maryland (2013) on firearm injury hospitalizations. We utilized RAND's healthcare cost and utilization project-based dataset from 2000 to 2016 for our outcome variable. We conducted in-time placebo testing and leave-one-out donor pool testing as sensitivity analyses.ResultsMaryland’s adoption was associated with a statistically significant 32.3% reduction in firearm-related injury hospitalization (FIH) rates (ATT = − 0.497, standard error (SE) = 0.123); Missouri’s repeal was associated with a statistically significant 35.7% increase in FIH rates (ASCM = 0.456, SE = 0.155); and Michigan’s partial repeal showed no statistically significant associations with FIH rates (ATT = − 0.074, SE = 0.129). Sensitivity analyses confirm the robustness of the estimated HPL effects.DiscussionHPL laws appear to be protective against hospitalizations for nonfatal firearm injuries. These findings align with prior research indicating that HPL laws are effective in reducing fatal firearm violence. States without such licensing systems ought to consider these robust policies as a means to address firearm violence.

Surveillance of SARS-CoV-2 prevalence from repeated pooled testing: application to Swiss routine data.

Surveillance of SARS-CoV-2 through reported positive RT-PCR tests is biased due to non-random testing. Prevalence estimation in population-based samples corrects for this bias. Within this context, the pooled testing design offers many advantages, but several challenges remain with regards to the analysis of such data. We developed a Bayesian model aimed at estimating the prevalence of infection from repeated pooled testing data while (i) correcting for test sensitivity; (ii) propagating the uncertainty in test sensitivity; and (iii) including correlation over time and space. We validated the model in simulated scenarios, showing that the model is reliable when the sample size is at least 500, the pool size below 20, and the true prevalence below 5%. We applied the model to 1.49 million pooled tests collected in Switzerland in 2021-2022 in schools, care centres, and workplaces. We identified similar dynamics in all three settings, with prevalence peaking at 4-5% during winter 2022. We also identified differences across regions. Prevalence estimates in schools were correlated with reported cases, hospitalizations, and deaths (coefficient 0.84 to 0.90). We conclude that in many practical situations, the pooled test design is a reliable and affordable alternative for the surveillance of SARS-CoV-2 and other viruses.

Maximizing efficiency in sedimentary ancient DNA analysis: a novel extract pooling approach

In the last few decades, the field of ancient DNA has taken a new direction towards using sedimentary ancient DNA (sedaDNA) for studying human and mammalian population dynamics as well as past ecosystems. However, the screening of numerous sediment samples from archaeological sites remains a time-consuming and costly endeavor, particularly when targeting hominin DNA. Here, we present a novel high-throughput method that facilitates the fast and efficient analysis of sediment samples by applying a pooled testing approach. This method combines multiple extracts, enabling early parallelization of laboratory procedures and effective aDNA screening. Pooled samples with detectable aDNA signals undergo detailed analysis, while empty pools are discarded. We have successfully applied our method to multiple sediment samples from Middle and Upper Paleolithic sites in Europe, Asia, and Africa. Notably, our results reveal that an aDNA signal remains discernible even when pooled with four negative samples. We also demonstrate that the DNA yield of double-stranded libraries increases significantly when reducing the extract input, potentially mitigating the effects of inhibition. By embracing this innovative approach, researchers can analyze large numbers of sediment samples for aDNA preservation, achieving significant cost reductions of up to 70% and reducing hands-on laboratory time to one-fifth.

Study on the Turning Characteristics and Influencing Factors of the Unmanned Sailboat

Unmanned sailboats can convert wind energy with sails to provide power for navigation, which can independently plan routes and collect data without human intervention. They have received increasing attention in recent years due to their low power consumption and strong self-sustainability. Due to the greater difficulty of manipulation, the unmanned sailboats have a weaker maneuverability than the propeller-driven vessels in the complex and variable marine environment. Typically, the turning motion is evaluated to characterize the maneuverability of a vessel, which has rarely been investigated in the existing research on unmanned sailboats. Therefore, this study builds a motion simulation platform for unmanned sailboats based on the 3 m class Petrel Sail to investigate the turning characteristics. The index of the approximate turning circle is introduced based on the turning motion trajectory, which is used to obtain the effect of rudder angle, wind angle, wind speed, and current speed on the turning performance of the sailboat in ideal hydrostatic conditions and under flow disturbance, respectively. Finally, a harbor pool test is conducted with an unmanned sailboat to verify the analysis results, and the errors in maximum transverse distance and maximum advance distance are in the reasonable range, proving the correctness of the theoretical results. The current study also provides theoretical guidance for subsequent research on sailboat manipulation and maneuverability.

A cost-sensitive decision model for efficient pooled testing in mass surveillance of infectious diseases like COVID-19

The COVID-19 pandemic has imposed significant challenges on global health, emphasizing the persistent threat of large-scale infectious diseases in the future. This study addresses the need to enhance pooled testing efficiency for large populations. The common approach in pooled testing involves consolidating multiple test samples into a single tube to efficiently detect positivity at a lower cost. However, what is the optimal number of samples to be grouped together in order to minimize costs? i.e. allocating ten individuals per group may not be the most cost-effective strategy. In response, this paper introduces the hierarchical quotient space, an extension of fuzzy equivalence relations, as a method to optimize group allocations. In this study, we propose a cost-sensitive multi-granularity intelligent decision model to further minimize testing costs. This model considers both testing and collection costs, aiming to achieve the lowest total cost through optimal grouping at a single layer. Building upon this foundation, two multi-granularity models are proposed, exploring hierarchical group optimization. The experimental simulations were conducted using MATLAB R2022a on a desktop with Intel i5-10500 CPU and 8G RAM, considering scenarios with a fixed number of individuals and fixed positive probability. The main findings from our simulations demonstrate that the proposed models significantly enhance the efficiency and reduce the overall costs associated with pooled testing. For example, testing costs were reduced by nearly half when the optimal grouping strategy was applied, compared to the traditional method of grouping ten individuals. Additionally, the multi-granularity approach further optimized the hierarchical groupings, leading to substantial cost savings and improved testing efficiency.

Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries

BackgroundIn 2022, fewer than half of persons with tuberculosis (TB) had access to molecular diagnostic tests for TB due to their high costs. Studies have found that the use of artificial intelligence (AI) software for chest X-ray (CXR) interpretation and sputum specimen pooling can each reduce the cost of testing. We modeled the combination of both strategies to estimate potential savings in consumables that could be used to expand access to molecular diagnostics.MethodsWe obtained Xpert testing and positivity data segmented into deciles by AI probability scores for TB from the community- and healthcare facility-based active case finding conducted in Bangladesh, Nigeria, Viet Nam, and Zambia. AI scores in the model were based on CAD4TB version 7 (Zambia) and qXR (all other countries). We modeled four ordinal screening and testing approaches involving AI-aided CXR interpretation to indicate individual and pooled testing. Setting a false negative rate of 5%, for each approach we calculated additional and cumulative savings over the baseline of universal Xpert testing, as well as the theoretical expansion in diagnostic coverage.ResultsIn each country, the optimal screening and testing approach was to use AI to rule out testing in deciles with low AI scores and to guide pooled vs individual testing in persons with moderate and high AI scores, respectively. This approach yielded cumulative savings in Xpert tests over baseline ranging from 50.8% in Zambia to 57.5% in Nigeria and 61.5% in Bangladesh and Viet Nam. Using these savings, diagnostic coverage theoretically could be expanded by 34% to 160% across the different approaches and countries.ConclusionsUsing AI software data generated during CXR interpretation to inform a differentiated pooled testing strategy may optimize TB diagnostic test use, and could extend molecular tests to more people who need them. The optimal AI thresholds and pooled testing strategy varied across countries, which suggests that bespoke screening and testing approaches may be needed for differing populations and settings.

Comparison of RT-PCR cycle threshold values between individual and pooled SARS-CoV-2 infected nasopharyngeal swab specimens.

The molecular reverse transcription-polymerase chain reaction (RT-PCR) testing of respiratory tract swabs has become mandatory to confirm the diagnosis of coronavirus disease 2019 (COVID-19). However, RT-PCR tests are expensive, require standardized equipment, and relatively long testing times, and the sample pooling method has been introduced to solve this issue. The aim of this study was to compare the cycle threshold (Ct) values of the individual sample and pooled sample methods to assess how accurate the pooling method was. Repeat RT-PCR examinations were initially performed to confirm the Ct values for each sample before running the pooled test procedure. Sample extraction and amplification were performed in both assays to detect ORF1ab, N, and E genes with a cut-off point value of Ct <38. Overall, there was no difference in Ct values between individual sample and pooled sample groups at all concentrations (p=0.259) and for all pooled sizes. Only pooled size of five could detect the Ct value in the pooled samples for all concentration samples, including low-concentration sample (Ct values 36 to 38). This study highlighted that pooled RT-PCR testing strategy did not reduce the quality of individually measured RT-PCR Ct values. A pool size of five could provide a practical technique to expand the screening capacity of RT-PCR.

Risk of Cancer in Patients with Congenital Heart Disease: A Systematic Review and Meta-Analysis.

There has been remarkable progress in both diagnosis and treatment of patients with congenital heart disease (CHD), with an increasing number of survivors. Whether patients with CHD are more likely to develop cancer is still a controversial issue. This study aimed to quantitatively estimate the association between patients with CHD and the risk of developing cancer through meta-analysis. Web of Science, PubMed, and Embase databases were searched from inception to September 2023 to identify potentially relevant case-control studies and cohort studies that reported risk estimates and confidence intervals (CIs). RevMan software was used to analyze the pooled effect size and test for heterogeneity. The random effect and fixed effect models were applied to the study period. Egger's test was performed to examine publication bias. We analyzed six studies, consisting of 2 case-control studies and 4 cohort studies comprising 276,124 participants. The overall pooled hazard risk for cancer in patients with CHD was 1.71 (95% CI: 1.28-2.28; p &lt; 0.01), with significant heterogeneity (I2 = 97%, p &lt; 0.01). The quantitative analysis of studies indicates that patients with CHD have an increased risk of developing cancer, even after adjusting for chromosomal disorders. Our study highlights the importance of controlling modifiable factors in cancer prevention and emphasizes the need for health education for patients with CHD in primary care. Given the limited number of studies included in this analysis, further research is needed to accurately quantify the cancer risk of exposed versus unexposed CHD.

Bayesian group testing regression models for spatial data

Spatial patterns are common in infectious disease epidemiology. Disease mapping is essential to infectious disease surveillance. Under a group testing protocol, biomaterial from multiple individuals is physically combined into a pooled specimen, which is then tested for infection. If the pool tests negative, all contributing individuals are generally assumed to be uninfected. If the pool tests positive, the individuals are usually retested to determine who is infected. When the prevalence of infection is low, group testing provides significant cost savings over traditional individual testing by reducing the number of tests required. However, the lack of statistical methods capable of producing maps from group testing data has limited the use of group testing in disease mapping. We develop a Bayesian methodology that can simultaneously map disease prevalence using group testing data and identify risk factors for infection. We illustrate its real-world utility using two datasets from vector-borne disease surveillance.

CFD simulation of thermal stratification and mixing in a Nordic BWR pressure suppression pool

Boiling Water Reactor (BWR) employs the Pressure Suppression Pool (PSP) as a heat sink to prevent overpressure of the reactor vessel and containment. Steam can be injected into the PSP through spargers in normal and accident conditions and through blowdown pipes in case of a loss of coolant accident (LOCA). There is a safety limit on the maximum PSP temperature at which such steam injection might cause dynamic loads on the containment structures. The performance of the pool can be affected if thermal stratification is developed when temperature of the hot layer grows rapidly while cold layer remains inactive. Simulation of pool behavior during realistic accident scenarios requires validated models that can sufficiently address the interaction between phenomena, safety systems and operational procedures. Direct modeling of steam injection into a water pool in long-term transients is computationally expensive due to the need to resolve simultaneously the smallest space and time scales of individual steam bubbles and the scales of the whole PSP. To enable PSP analysis for practical purposes, Effective Heat source and Effective Momentum source (EHS/EMS) models have been proposed that avoid the need to resolve steam-water interface. This paper aims to implement mechanistic approaches previously developed by authors for the simulation of transient thermal stratification and mixing phenomena induced by steam injection through spargers in a Nordic BWR PSP. The latest version of the EHS/EMS models using the ‘Unit cell’ approach has been validated against integral effect pool tests and applied to plant simulations. Several scenarios with boundary conditions corresponding to postulated accident sequences were simulated to investigate the possibility of stratification development and the effects of activation of different systems (e.g., blowdown pipes, high momentum nozzle) on the pool behavior.

Beyond Standard Urine Culture: Advanced Molecular Testing for Urinary Tract Infections

In this review article, it is emphasized that adopting advanced molecular diagnostics is essential for modern UTI management, offering a more comprehensive, accurate, and rapid approach compared to traditional methods. Standard urine culture’s limitations include low sensitivity and failure to culture certain microorganisms, leading to undiagnosed cases and increased morbidity. Advanced molecular techniques, like multiplex-PCR and pooled antibiotic susceptibility testing have been shown to reduce empiric treatments and negative outcomes significantly. And advanced molecular methods like metagenomics (mNGS) offer comprehensive pathogen detection without prior knowledge of target organisms, improving diagnostic yield. These methods also detect antibiotic resistance genes, aiding in precise treatment strategies and improving patient outcomes. Adopting advanced molecular diagnostics is essential for modern UTI management, offering a more comprehensive, accurate, and rapid approach compared to traditional methods. These technologies are vital in improving patient care and combating antibiotic-resistant infections.

High capacity clinical SARS-CoV-2 molecular testing using combinatorial pooling

BackgroundThe SARS-CoV-2 pandemic led to unprecedented testing demands, causing major testing delays globally. One strategy used for increasing testing capacity was pooled-testing, using a two-stage technique first introduced during WWII. However, such traditional pooled testing was used in practice only when positivity rates were below 2%.MethodsHere we report the development, validation and clinical application of P-BEST - a single-stage pooled-testing strategy that was approved for clinical use in Israel.ResultsP-BEST is clinically validated using 3636 side-by-side tests and is able to correctly detect all positive samples and accurately estimate their Ct value. Following regulatory approval by the Israeli Ministry of Health, P-BEST was used in 2021 to clinically test 837,138 samples using 270,095 PCR tests - a 3.1fold reduction in the number of tests. This period includes the Alpha and Delta waves, when positivity rates exceeded 10%, rendering traditional pooling non-practical. We also describe a tablet-based solution that allows performing manual single-stage pooling in settings where liquid dispensing robots are not available.ConclusionsOur data provides a proof-of-concept for large-scale clinical implementation of single-stage pooled-testing for continuous surveillance of multiple pathogens with reduced test costs, and as an important tool for increasing testing efficiency during pandemic outbreaks.

Antibacterial Potential of Protein Solution Separated from Bovine Serum by SDS Treatment

This study explores the separation of antibacterial proteins from bovine serum using a simple and novel method developed. The salt out protein precipitate was prepared from the acid extract of the bovine serum using 30% ammonium sulphate solution. One volume of the precipitate is treated with two volumes of each concentration of SDS solution (1 – 10%) separately in refrigerator temperature. After a week of treatment, two layers are formed. The lower layer is frozen SDS where the upper one is unfrozen protein solution. The upper layer formed by each percentage of SDS was carefully collected and its protein content is also measured. The maximum protein content (90%) has been recovered in the liquid layer formed by 3 % SDS. The λ-max of pooled test protein solution is 276 nm. The Minimum Inhibitory Concentration (MIC) of this protein was checked against seven human pathogenic bacteria and it is ranged from 4 to 1μg. In contrast, there is no heamolysis even at the higher concentration (33 μg) of the test solution. A single mild and faint band with approximate Molecular Weight of 45 kDa is observed in SDS-PAGE. This method of antibacterial protein preparation from cattle serum could lead a new insight in pharmaceutical industries for the development of protein based natural antibiotics.