Cardiogenic Shock Challenges and Priorities: A Clinician Survey.

BACKGROUND: Cardiogenic shock (CS) is common and survival outcomes have not substantially improved. Australia's geography presents unique challenges in the management of CS. The challenges and research priorities for clinicians pertaining to CS identification and management have yet to be described. METHOD: We used an exploratory sequential mixed methods design. Semi-structured interviews were conducted with 10 clinicians (medical and nursing) to identify themes for quantitative evaluation. A total of 143 clinicians undertook quantitative evaluation through online survey. The interviews and surveys addressed current understanding of CS, status of cardiogenic systems and future research priorities. RESULTS: There were 143 respondents: 16 (11%) emergency, cardiology 22 (16%), 37 (26%) intensive care, 54 (38%) nursing. In total, 107 (75%) believe CS is under-recognised. Thirteen (13; 9%) of respondents indicated their hospital had existing CS teams, all from metropolitan hospitals, and 40% thought additional access to mechanical circulatory support devices was required. Five (5; 11%) non-tertiary hospital respondents had not experienced a delay in transfer of a patient in CS. All respondents felt additional research, particularly into the management of CS, was required. CONCLUSIONS: Clinicians report that CS is under-recognised and further research into CS management is required. Access to specialised CS services is still an issue and CS protocolised pathways may be of value.

Assessment of Safe Drinking Water Handling Practices in Households of Northern India: A Cross-Sectional Study.

Background Waterborne diseases are the most common form of infectious disease, spreading from contaminated water, especially in a developed country. These diseases are a major concern for the environment and public health. The living conditions in developing countries like India affect the water-handling practices, which make the population vulnerable to waterborne diseases. The inability to access safe drinking water also adds to this. Water safety for a community relies on water collection, treatment, storage, and handling in the household setting. Therefore, the burden of waterborne disease can be reduced by treating point-of-use drinking water, including improving handling and transport. Objectives The aim was to assess the safe drinking water handling practices in households. The objectives were to assess the safe drinking water-handling practices, namely, treatment, storage, lid status of the storage vessel, and water drawing technique, and to estimate the sources of safe drinking water. Methods This cross-sectional study was conducted in the Etawah district on a total of 312 eldest female family members actively working in the kitchen. Descriptive analysis and Chi-Square test were applied to the collected data and a p-value <0.05 at 95% confidence interval (CI) was taken as statistically significant. Results Overall, 135 (85.9%) households in urban areas relied on public supply. However, in rural areas mostly 130 (83%) households depended on private supply. In water-handling practices, 276 (88.4%) used some method to purify drinking water, a total of 209 (67%) households kept the lid of the storage container covered, and 249 (79.8%) households drew water either by pouring or scooping with a long handle. Conclusion The study concluded that both private and public sources were used for drinking water. Regarding water-handling practices, most households drank purified water, kept their containers covered, and drew water either by scooping or pouring from storage containers. Those who drank purified water mostly belonged to nuclear families and had private sources of drinking water.

Chitosan and neem gum-based polyelectrolyte complex for design of allantoin loaded biocomposite film: In-vitro, ex-vivo, and in-vivo characterization.

Presently, the preference for chitosan (CS) and gum polysaccharides in biomedical applications including drug delivery and wound healing has been extensively documented. Despite this, the demerits of CS and gum polysaccharides such as poor mechanical properties, degradation rate, swelling, etc., limit their applications for designing biocomposite films for drug delivery. Therefore, the anticipated work aims to design a CS and neem gum polysaccharides (NGP) polyelectrolyte complex-based allantoin (AT)-loaded (CS/NGP-AT) biocomposite film for improved wound healing. In brief, CS, NGP, and CS/NGP-AT-based biocomposite films were prepared using the solvent-casting method, and in-vitro, ex-vivo, and in-vivo characterizations were performed to assess the performance of these biocomposite films compared to their counterparts. In this, diffractogram and thermogram analysis assured the conversion of crystalline AT into an amorphous form. The optimized CS/NGP/AT-3 formulation exhibited controlled water absorption, appropriate water uptake capacity, good water retention ability, excellent water vapor transmission rate, controlled degradation rate, enhanced mechanical properties, cell and blood biocompatibility, etc. Furthermore, it offered improved antimicrobial, anti-inflammatory, and antioxidant potential. The optimized film provided a modified release (88.3 ± 0.3 %) of AT from the film for up to 48 h. Wound healing experiments on rats and their histopathology studies confirmed a significantly higher rate of wound recovery within 14 days compared to the control and CS/NGP film, attributable to the combined effects of CS, NGP, and AT. In conclusion, the fabricated CS/NGP-based biocomposite film presents promising prospects as an excellent candidate for wound healing applications.

A Design-Conversed Strategy Establishes the Performance Safe Space for Doxorubicin Nanosimilars.

Nanomedicines exhibit multifaceted performances, yet their biopharmaceutics remain poorly understood and present several challenges in the translation from preclinical to clinical research. To address this issue and promote the production of high-quality nanomedicines, a systematic screening of the design space and in vivo performance is necessary. Establishing formulation performance specifications early on enables an informed selection of candidates and promotes the development of nanosimilars. The deconvolution of the pharmacokinetics enables the identification of key characteristics that influence their performances and disposition. Using an in vitro-in vivo rank-order relationship for doxorubicin nanoformulations, we defined in vitro release specifications for Doxil/Caelyx-like follow-on products. Additionally, our model predictions were used to establish the bioequivalence of Lipodox, a nanosimilar of Doxil/Caelyx. Furthermore, a virtual safe space was established, providing crucial insights into expected disposition kinetics and informing formulation development. By addressing bottlenecks in biopharmaceutics and formulation screening, our research advances the translation of nanomedicine from bench to bedside.

An introduction to digital determinants of health.

In recent years, technology has been increasingly incorporated within healthcare for the provision of safe and efficient delivery of services. Although this can be attributed to the benefits that can be harnessed, digital technology has the potential to exacerbate and reinforce preexisting health disparities. Previous work has highlighted how sociodemographic, economic, and political factors affect individuals' interactions with digital health systems and are termed social determinants of health [SDOH]. But, there is a paucity of literature addressing how the intrinsic design, implementation, and use of technology interact with SDOH to influence health outcomes. Such interactions are termed digital determinants of health [DDOH]. This paper will, for the first time, propose a definition of DDOH and provide a conceptual model characterizing its influence on healthcare outcomes. Specifically, DDOH is implicit in the design of artificial intelligence systems, mobile phone applications, telemedicine, digital health literacy [DHL], and other forms of digital technology. A better appreciation of DDOH by the various stakeholders at the individual and societal levels can be channeled towards policies that are more digitally inclusive. In tandem with ongoing work to minimize the digital divide caused by existing SDOH, further work is necessary to recognize digital determinants as an important and distinct entity.

Corporate Social Responsibility Framework: An Innovative Solution to Social Determinants of Health in the USA.

PURPOSE: Expand firms' corporate social responsibility (CSR) framework to systematically address social determinants of health (SDOH) in their communities and improve firms' performance (FP). GAP: The U.S. healthcare system has struggled to improve population health outcomes while enhancing delivery performance. An oft-overlooked contributor to this deficit is SDOH inequities, accounting for 25-60% of deaths in the USA annually. Ironically, most healthcare firms do not view investment in SDOH, a neglected phenomenon, to develop sustainable healthy communities as their direct responsibility due to the "wrong pocket problem." Although extant literature theorizes the CSR construct, there is a paucity of research on SDOH integration with the CSR framework. DESIGN: We integrate a quantitative and qualitative study with supplementary literature on CSR and SDOH using the grounded theory method by researching fourteen health plan firms across the USA. FINDINGS: Research reveals early efforts undertaken by top-performing healthcare insurers to address SDOH and provides evidence that such measures can be integrated profitably under CSR as a competitive advantage. ORIGINALITY: Contributes to CSR theory and practice by providing an empirical model and expanding its framework to address SDOH systematically. Key implications are as follows: (1) healthcare firms to link with unconventional partners, such as housing authorities, food banks, employment agencies, and schools; (2) the entire healthcare supply chain to collaborate with social enterprises and regulators to develop sustainable communities; (3) policymakers must incentivize firms to align social equity and corporate goals; and (4) long-term view on CSR, SDOH, and healthy living (HL) will in-turn eliminate social inequities while enhancing FP.

Using pulsatility responses to breath-hold maneuvers to predict readmission rates in continuous-flow left ventricular assist device patients.

BACKGROUND: Dynamic respiratory maneuvers induce heterogenous changes to flow-pulsatility in continuous-flow left ventricular assist device patients. We evaluated the association of these pulsatility responses with patient hemodynamics and outcomes. METHODS: Responses obtained from HVAD (Medtronic) outpatients during successive weekly clinics were categorized into three ordinal groups according to the percentage reduction in flow-waveform pulsatility (peak-trough flow) upon inspiratory-breath-hold, (%∆P): (1) minimal change (%∆P ≤ 50), (2) reduced pulsatility (%∆P > 50 but <100), (3) flatline (%∆P = 100). Same-day echocardiography and right-heart-catheterization were performed. Readmissions were compared between patients with ≥1 flatline response (F-group) and those without (NF-group). RESULTS: Overall, 712 responses were obtained from 55 patients (82% male, age 56.4 ± 11.5). When compared to minimal change, reduced pulsatility and flatline responses were associated with lower central venous pressure (14.2 vs. 11.4 vs. 9.0 mm Hg, p = 0.08) and pulmonary capillary wedge pressure (19.8 vs. 14.3 vs. 13.0 mm Hg, p = 0.03), lower rates of ≥moderate mitral regurgitation (48% vs. 13% vs. 10%, p = 0.01), lower rates of ≥moderate right ventricular impairment (62% vs. 25% vs. 27%, p = 0.03), and increased rates of aortic valve opening (32% vs. 50% vs. 75%, p = 0.03). The F-group (n = 28) experienced numerically lower all-cause readmissions (1.51 vs. 2.79 events-per-patient-year [EPPY], hazard-ratio [HR] = 0.67, p = 0.12), reduced heart failure readmissions (0.07 vs. 0.57 EPPY, HR = 0.15, p = 0.008), and superior readmission-free survival (HR = 0.47, log-rank p = 0.04). Syncopal readmissions occurred exclusively in the F-group (0.20 vs. 0 EPPY, p = 0.01). CONCLUSION: Responses to inspiratory-breath-hold predicted hemodynamics and readmission risk. The impact of inspiratory-breath-hold on pulsatility can non-invasively guide hemodynamic management decisions, patient optimization, and readmission risk stratification.

Longitudinal analysis left ventricular chamber responses under durable LVAD support.

BACKGROUND: Left ventricular assist device (LVAD) support offers remodeling potential in some patients. Our goal was to use noninvasively derived pressure-volume (PV) loops to understand the effect of demographic and device variables on serial changes in cardiac function under pump support. METHODS: Thirty-two consecutive Medtronic HeartWare Ventricular Assist Device (HVAD) patients (mean 55.9 ± 12.3 years, 81.3% male) were prospectively recruited. Single-cycle ventricular pressure and volume were estimated using a validated algorithm. PV loops (n = 77) and corresponding cardiac chamber dynamics were derived at predefined postimplant timepoints (1, 3, 6 months). Changes in PV loop parameters sustained across the 6-month period were characterized using mixed-effects modeling. The influence of demographic and device variables on the observed changes was assessed. RESULTS: Across a 6-month period, the mean ventricular function parameters remained stable. Significant predictors of monthly improvement of stroke work include: lower pump speeds (2400 rpm vs 2500-2800 rpm) [0.0.051 mm Hg/liter/month (p = 0.001)], high pulsatility index (>1.0 vs <1.0) [0.052 mm Hg/liter/month (p = 0.012)], and ischemic cardiomyopathy indication for LVAD implantation (vs nonischemic) [0.0387 mm Hg/liter/month (p = 0.007)]. Various other cardiac chamber function parameters including cardiac power, peak systolic pressure, and LV elastance also showed improvements in these cohorts. CONCLUSIONS: Factors associated with improvement in ventricular energetics and hemodynamics under LVAD support can be determined with noninvasive PV loops. Understanding the basis of increasing ventricular load to optimize myocardial remodeling may prove valuable in selecting eligible recovery candidates.

Enhancing blood flow prediction in multi-exposure laser speckle contrast imaging through ensemble learning with K-mean clustering.

Purpose.Accurately visualizing and measuring blood flow is of utmost importance in maintaining optimal health and preventing the onset of various chronic diseases. One promising imaging technique that aids in visualizing perfusion in biological tissues is Multi-exposure Laser Speckle Contrast Imaging (MELSCI). MELSCI technique allows real-time quantitative measurements using multiple exposure times to obtain precise and reliable blood flow data. Additionally, the application of machine learning (ML) techniques can further enhance the accuracy of blood flow prediction in this imaging modality.Method.Our study focused on developing and evaluating Ensemble Learning ML techniques along with clustering algorithms for predicting blood flow rates in MELSCI. The effectiveness of these techniques was assessed using performance parameters, including accuracy, F1-score, precision, recall, specificity, and classification error rate.Result.Notably, the study revealed that Ensemble Learning with clustering emerged as the most accurate technique, achieving an impressive accuracy rate of 98.5%. Furthermore, it demonstrated a high recall of more than 91%, F1-score, the precision of more than 90%, higher specificity of 99%, and least classification error of 1.5%, highlighting its suitability and sustainability for flow prediction in MELSCI.Conclusion.The study's findings imply that Ensemble Learning can significantly contribute to enhancing the accuracy of blood flow prediction in MELSCI. This advancement holds substantial promise for healthcare professionals and researchers, as it facilitates improved understanding and assessment of perfusion within biological tissues, which will contribute to the maintenance of good health and prevention of chronic diseases.

Estimation of Access to Safe Drinking Water to Households in Etawah District: A Cross-Sectional Study.

CONTEXT: Unsafe drinking water causes diarrheal disease and environmental enteropathy. The quality of water is determined by its physical, chemical, and biological characteristics. Water sources have a significant impact on household members' health, particularly children. To combat this, India is committed to providing household tap connections to ensure the delivery of safe drinking water with the "Jal Jeevan Mission." AIMS: This study aims to estimate the access to safe drinking water and the physical and chemical qualities of water (qualitatively) in the urban and rural areas of Etawah district, India. SETTINGS AND DESIGN: A cross-sectional study was conducted in Etawah district from January 2020 to December 2021. The study subjects were the eldest female of the family. A total of 312 females were included. The data collected were analyzed using IBM SPSS Statistics for Windows, version 25 (released 2017; IBM Corp., Armonk, New York, United States) for descriptive analysis. RESULTS: In the present study, 76.3% (238/312) of households in the urban and rural areas had access to safe drinking water (here, the meaning of the word "safe" is based on its operational definition). A total of 130 (83.3%) households in rural areas and only 21 (13.5%) in urban areas had private supply as the primary water source. The physical and chemical qualities of water were within the requirement (acceptable limit) and permissible limit in all the study areas, so the water is considered safe for drinking. CONCLUSIONS: This study reported that 76.3% (238) households had access to safe drinking water according to the operational definition. The major public source of drinking water was public-supplied tap water, and in private sources, submersible or boreholes were the most common.

Barriers of household toilet utilization among toilet owners in a rural area of Northern India: An analytical cross-sectional study.

Background: Open defecation continues to prevail among toilet owners despite effective implementation of the Swachh Bharat Mission (Gramin). We conducted this study to determine toilet utilization rates and learn about the barriers to toilet use in the rural areas. By understanding the barriers, physicians can provide targeted education and become better equipped to manage their patients' conditions and advocate for their demands. Materials and Methods: We conducted a cross-sectional study on the households of the rural field practice areas of the department in central Uttar Pradesh by the census method. House listing was procured from the departmental records. The questionnaire was directed at both the household level and individual level. Results: The proportion of households with access to a toilet was found to be 91.1% of which 504 households were included in the study. Among the toilet owners, 115 (22.8%) households were not using toilets exclusively by all the members. At the individual level, age groups (of 20-59 years, and ≥60 years) and female gender were found to be significantly associated with open defecation. At the household level, government assistance for toilet construction and livestock keeping was found to be associated with open defecation. Major barriers to toilet use were childhood habits, dearth of toilets in the farming grounds/workplace, women during menstruation and having a non-functional toilet. Conclusion: This study indicates that merely installing a household toilet does not ensure exclusive utilization of toilet and the practice of open defecation might continue to be prevalent if corrective measures are not undertaken.

Protocolised Management of Cardiogenic Shock and Shock Teams: A Narrative Review.

Despite advances in therapy, the incidence of cardiogenic shock continues to increase, with significant mortality that has improved minimally over time. Treatment options for cardiogenic shock are complex and time-, resource-, and case volume-dependent, and involve multiple medical specialties. To provide early, more equitable, and standardised access to cardiogenic shock expertise with advanced therapies, cardiogenic shock teams with a protocolised treatment approach have been proposed. These processes have been applied across hospitals into integrated cardiogenic shock networks. This narrative review evaluates the role of cardiogenic shock teams, protocolised and regionalised shock networks, and the main individual components of protocolised shock management approaches.

Antimicrobial peptides modulate lung injury by altering the intestinal microbiota.

BACKGROUND: Mammalian mucosal barriers secrete antimicrobial peptides (AMPs) as critical, host-derived regulators of the microbiota. However, mechanisms that support microbiota homeostasis in response to inflammatory stimuli, such as supraphysiologic oxygen, remain unclear. RESULTS: We show that supraphysiologic oxygen exposure to neonatal mice, or direct exposure of intestinal organoids to supraphysiologic oxygen, suppresses the intestinal expression of AMPs and alters intestinal microbiota composition. Oral supplementation of the prototypical AMP lysozyme to hyperoxia-exposed neonatal mice reduced hyperoxia-induced alterations in their microbiota and was associated with decreased lung injury. CONCLUSIONS: Our results identify a gut-lung axis driven by intestinal AMP expression and mediated by the intestinal microbiota that is linked to lung injury in newborns. Together, these data support that intestinal AMPs modulate lung injury and repair. Video Abstract.

Effect of Saccharolactone on CYP-mediated Metabolism of Xenobiotics.

BACKGROUND: Saccharolactone is used as a ß-glucuronidase inhibitor in in vitro microsomal and recombinant uridine diphosphoglucuronosyl transferases (rUGTs) incubations to enhance glucuronide pathway and, thereby, formation of glucuronide metabolites. We investigated its effect on CYP mediated metabolism of drugs (compound-174, phenacetin and quinidine) using human liver microsomes (HLM) supplemented with Phase-1 and Phase-2 co-factors. METHODS: Compounds were incubated in HLM supplemented with co-factors to assess Phase-1 (NADPH) and Phase-2 (NADPH, alamethicin, saccharolactone and UDPGA) metabolism. CYP phenotype assay for compound-174 was conducted in HLM (± 1-ABT) and human recombinant CYP isoforms. CYP inhibition profile of saccharolactone was also generated in HLM. RESULTS: The metabolism of compound-174, phenacetin and quinidine in HLM significantly decreased in reactions containing additional components like alamethicin, saccharolactone and UDPGA and indicated that the addition of saccharolactone inhibited the metabolism. Phenacetin and quinidine are known substrates of CYP1A2 and CYP3A4 isoforms. The metabolism of compound- 174 was significantly inhibited in the presence of 1-ABT in HLM, and CYP3A4 and CYP2C8 isoforms were found to be the predominant isoforms responsible for its metabolism. Further evaluation of CYP inhibition in HLM indicated saccharolactone to be a strong inhibitor of CYP1A2, 2D6, 3A4 and 2C8 isoforms with IC50 values of less than 4 mM. CONCLUSION: The findings indicated that saccharolactone being a strong inhibitor of CYP1A2, 2D6, 3A4 and 2C8 isoforms (IC50 < 4 mM), resulted in significant inhibition of the metabolism of compound-174, phenacetin and quinidine in HLM and caution should be exercised in using it with proper titration of the concentrations.

Multi-exposure Laser Speckle Contrast Imaging (MECI)-Based Prediction of Blood Flow Using Random Forest (RF) With K-Means (KM).

Blood flow prediction is very important for medical diagnosis, drug development, tissue engineering, and continuous monitoring. One commonly used method for studying blood flow is called multi-exposure laser speckle contrast imaging (MECI). It provides valuable insights into how blood flows through tissues and helps in diagnosing circulatory diseases. In our study, we used MECI to measure blood flow in real-time by taking multiple measurements with different exposure times and contrasts. To predict different blood flow rates ranging from 0.1 to 1 mm/s, we employed machine learning (ML) techniques like clustering and random forest (RF) or support vector machine (SVM) algorithms. The study showed that RF with K-means performance is found to be the most accurate technique for flow classification, with an accuracy of 98.5%, a precision of 92%, a specificity of 98.9%, and a classification error of 1.5%. Our study demonstrates that employing clustering and RF algorithms in MECI provides a robust and effective approach to predicting blood flow. This technique holds great potential for a wide range of applications in the medical and healthcare fields.

Development of novel bosentan analogues as endothelin receptor antagonists for pulmonary arterial hypertension.

Since decades, bosentan has been in use for the treatment of pulmonary arterial hypertension (PAH). However, chronic exposure to bosentan leads to the development of resistance, tolerance, and serious adverse effects that have restricted its usage in clinical practices. To surmount these limitations, some new bosentan derivatives have been synthesized and evaluated for their therapeutic efficacy in PAH. Molecular docking analyses of all the synthesized derivatives were carried out using the endothelin (ET) receptor. In addition, the inhibitory ability of synthesized derivatives was determined in in vitro assay employing an ET-1 human ELISA kit. Among the synthesized derivatives, three derivatives namely 17d, 16j, and 16h with higher docking scores and lower IC50 values were selected for determination of the magnitude of the binding force between the derivative and ET receptor using molecular dynamics (MD) simulations study. Further, these derivatives were subjected to in vivo studies using monocrotaline (MCT) induced PAH in rat model. Results of in vivo studies inferred that the derivatives exhibit impressive ability to reduce PAH. Besides, its protective role was also evidenced in hemodynamic and right ventricular hypertrophy analyses, histological analysis, cardiac biomarkers, hypoxia-inducible factor 1 alpha (HIF1α) levels, and biochemical studies. Furthermore, gene quantification by quantitative RT-PCR and Western blot analysis was also performed to examine its effect on the expression of key proteins in PAH. Notably, amongst three, derivative 16h exhibited the most encouraging results in molecular docking analysis, in vitro, in vivo, histopathological, biochemical, protein expression, and MD studies. Besides, derivative 16h also showed impressive pharmacokinetic features in ADMET analysis. In conclusion, derivative 16 h could act as a reliable ET receptor antagonist and requires further exploration to attain its therapeutic utility in PAH management.

Blood Flow Prediction in Multi-Exposure Speckle Contrast Imaging Using Conditional Generative Adversarial Network.

Purpose Blood perfusion is an important physiological parameter that can be quantitatively assessed using various imaging techniques. Blood flow prediction in laser speckle contrast imaging is important for medical diagnosis, drug development, tissue engineering, biomedical research, and continuous monitoring. Deep learning is a new and promising approach for predicting blood flow whenever the condition varies, but it comes with a high learning cost for real-world scenarios with a variable flow value derived from multi-exposure laser speckle contrast imaging (MECI) data. A generative adversarial network (GAN) is presented in this research for the reliable prediction of blood flows in diverse scenarios in MECI. Method We suggested a time-efficient approach using a low frame rate camera that can be used to predict blood flow in MECI data by using conditional GAN architecture. Our approach is implemented by extending our work to the entire flow as well as the specific region of interest (ROI) in the flow. Results Results show that conditional GAN exhibits improved generalization ability to predict blood flow in MECI when compared to classifications-based deep learning approaches with an accuracy of 98.5% with a relative mean error of 1.57% for the whole field and 7.53% for a specific ROI. Conclusion The conditional GAN is very effective in predicting blood flows in MECI, entirely or within ROI, compared with other deep learning approaches.

A Review on Performance Improvement of Anaerobic Digestion Using Co-Digestion of Food Waste and Sewage Sludge.

Anaerobic co-digestion (AcoD) is a vital technology in the decarburization of the economy because of its ability to process organic waste, recover nutrients, and create biogas as a sustainable biofuel all at the same time. This attribute also makes this technology a viable partner in pursuing a circular economic model. However, the poor biogas output of typical substrates like sewage sludge and animal manure and the hefty installation costs limit its viability. This review paper with literature analysis provides a good grasp of the anaerobic co-digesting process with diverse food digestion methods. In this survey, we have analyzed the Anaerobic Digestion of water waste, food waste, and animal manure and the anaerobic co-digestion of animal waste with water waste and food waste with water waste. This analysis demonstrates that anaerobic co-digestion produces more methane biogas than anaerobic digestion. Also, it has been shown that by adjusting the ratio of food and animal waste to water waste, we can produce more methane. In the future, we would like to supplement anaerobic co-digestion by altering the proportion of different wastes that are mixed with water waste in order to increase methane production.