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This study aimed to develop a simple and easy to construct fruits size sorting machine. The sorting machine was designed to sort oranges, apples, and yellow plums in small, medium, large, and extra-large size groups based on physical and mechanical properties including axial dimensions, arithmetic mean diameter, sphericity, mass, volume, projected area, and frictional characteristics (coefficient of static friction) against two structural surfaces of the sorting machine (galvanized iron and rubber). The maximum sorting efficiency of the machine was 98% at 20 rpm for plums. Whereas the minimum fruit sorting efficiency of the machine at 25 rpm was 76% for apple fruits. The sorting efficiency of the machine increased with increasing sphericity ratio of fruits. The sorting machine productivity was 280, 250, and 212 kg h-1 for sorting oranges, apples, and plums, respectively. It is recommended that the machine should be operated at three slope angles of the sorting unit 20º, 15º, and 10º for oranges, apples, and plums, respectively. These angles correspond to the coefficient of static friction of the tested fruit.

Purpose: Our aim was to assess the different voice prostheses (VPs) to identify the most efficient, safest, patient-tailored, longest lifetime, and inexpensive VPs and assess the different factors affecting their quality.Method: In September 2017, 15 databases were searched to include all randomized controlled trials. A new search was done in May 2019 to include all other study design articles, which include all the new-era VPs subtypes. Network meta-analysis (NMA) was applied to all 27 outcomes, besides NMA overall and partial order setting was done by using Hasse scatter plots. p values were used in NMA, where the best VPs are approaching one and the least approaches zero. Meta-analysis was done for the rest of the outcomes.Results: Two hundred one articles were eligible for inclusion in our study (N = 11,918). Provox-2 was significantly the most efficient and safest device concerning the most patient preference (odds ratio [OR] = 33.88 [0.65, 1762.24]; p = .92), the least dislodgement (risk ratio [RR] = 0.27 [0.13, 0.57]; p = .79), the least airflow resistance (RR = 0.42 [0.08, 2.11]; p = .84), the least granulation formation (RR = 0.73 [0.02, 26.32]; p = .60), and the least VPs’ inaccurate size (RR = 0.77 (0.23, 2.61); p = .66). Heat and moisture exchanger addition showed a significant increase in maximum phonation time and breathing experience, with p values (1 and .59), respectively. While heat and moisture exchanger addition showed a significant decline in stoma cleaning frequency, coughing frequency, forced expectoration, sputum production, sleeping problems, and loosening of adhesive, with p values (.99, .72, .69, .96, 1, and .96), respectively, Groningen low resistance and Nijdam were considered the worst devices with both overall mean p value of .44.Conclusions: Provox-2 is considered the best choice as being the most preferable for patients, with the least airflow resistance, dislodgment, granulation formation, and prosthesis inaccurate size. Groningen low resistance and Nijdam were considered the worst devices according to our analysis.Supplemental FiguresS1. Risk of bias assessment summary.S2. Risk of bias assessment graph of included randomized controlled trials.S3. Network meta-analysis for Replacements frequency of each device.S4. Network meta-analysis for Duration lifetime of each device.S5. Network meta-analysis for Air flow resistance of each device.S6. Network meta-analysis for Maximum phonation time of each device.S7. Network meta-analysis for Leakage rate of each device.S8. Network meta-analysis for Speech rate of each device. S9. Network meta-analysis for Patient device preference of each device. S10. Network meta-analysis for Stoma cleaning of each device. S11. Network meta-analysis for Breathing problems of each device. S12. Network meta-analysis for Coughing Frequency of each device. S13. Network meta-analysis for Forced expectorations of each device. S14. Network meta-analysis for Sputum production of each device. S15. Network meta-analysis for Sleeping problems of each device. S16. Network meta-analysis for Loosening of adhesive of each device. S17. Network meta-analysis for Increase phonatory effort of each device.S18. Network meta-analysis for Voice speech quality of each device. S19. Network meta-analysis for Fundamental Frequency of each device. S20. Network meta-analysis for Voice Loudness of each device.S21. Network meta-analysis for Speech Intelligibility of each device.S22. Network meta-analysis for Stoma stenosis of each device.S23. Network meta-analysis for Dislodgement of each device.S24. Network meta-analysis for Fistula problems of each device.S25. Network meta-analysis for Granulation of each device.S26. Network meta-analysis for Breathing Experience of each device.S27. Network meta-analysis for Prosthesis inaccurate size of each device.S28. Network meta-analysis for Prosthesis deterioration of each device.S29. Network meta-analysis for Follow-up survival rate of each device. S30A. Meta-analysis for Aspiration pneumonia rate of each device. S30B. Meta-analysis for Fungal colonization rate of each device. S31A. Meta-analysis for Experience with speaking rate of each device. S31B. Meta-analysis for Skin irritation rate of each device. Supplemental TablesS1. PRISMA 2009 Checklist.S2. Detailed search strategy for each database search.S3. Detailed definitions of each outcome in the study.S4. All equations used in data extraction.S5. Baseline characteristics of the patients in the included studies. Tawfik, G. M., Makram, O. M., Zayan, A. H., Ghozy, S., Eid, P. S., Mahmoud, M. H., Abdelaal, A., Abdelghany, S. M., Sayed, A. M., Sang, T. K., Kassem, M., Ho, Q. L. M., Eltanany, H. H., Ali, A. F., Sweiny, O. G., Elsherbiny, K. E., Shafik, A. G., Hirayama, K., & Huy, N. T. (2021). Voice rehabilitation by voice prostheses after total laryngectomy: A systematic review and network meta-analysis for 11,918 patients. Journal of Speech, Language, and Hearing Research. Advance online publication. https://doi.org/10.1044/2021_JSLHR-20-00597

The aim of this study was to determine the effect of feeding dried powder ofMoringa oleiferaleaves as a supplemented food on total cholesterol level and antibody titer against parvo virus in dogs.Moringa oleiferaleaves were collected from Fayoum Province of Egypt. A total 12 weaned (45 days) German shepherd dogs divided into 4 groups in each group 3 Animals: 1stas control, 2nd200 mg/kg, 3rd300 mg/kg and 4th400mg/kg ofMoringa oleiferaleaves powder. The blood samples were collected from dogs before, half and after experiment (0, 15, 30 days) for analysis of total cholesterol and anti-body titer against parvo virus. The results revealed that: (1) There is a significant decrease (PMoringa oleiferaleaves may have a promising effect for cholesterol-lowering (2) Administration ofthe Moringa oleiferaleaves lead to increase (P Moringa oleiferaas an immune boosting agent.

Brooke Benner,1,* Logan Good,1,* Dionisia Quiroga,2 Thomas E Schultz,3 Mahmoud Kassem,2 William E Carson,1 Mathew A Cherian,2 Sagar Sardesai,2 Robert Wesolowski2 1Department of Surgery, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA; 2Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA; 3Department of Pharmacy, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA*These authors contributed equally to this workCorrespondence: Robert WesolowskiDivision of Medical Oncology, The Ohio State University Comprehensive Cancer Center, 1800 Cannon Drive, 1250 Lincoln Tower, Columbus, OH 43210 Tel +1 614 366 5125Fax +1 614 293 7264Email Robert.Wesolowski@osumc.eduAbstract: Tenosynovial giant cell tumor (TGCT) is a rare benign tumor that involves the synovium, bursa, and tendon sheath, resulting in reduced mobility of the affected joint or limb. The current standard of care for TGCT is surgical resection. However, some patients have tumor recurrence, present with unresectable tumors, or have tumors that are in locations where resection could result in amputations or significant debility. Therefore, the development of systemic agents with activity against TGCT to expand treatment options is a highly unmet medical need. Pathologically, TGCT is characterized by the overexpression of colony-stimulating factor 1 (CSF-1), which leads to the recruitment of colony-stimulating factor-1 receptor (CSF-1R) expressing macrophages that make up the primary cell type within these giant cell tumors. The binding of CSF-1 and CSF-1R controls cell survival and proliferation of monocytes and the switch from a monocytic to macrophage phenotype contributing to the growth and inflammation within these tumors. Therefore, molecules that target CSF-1/CSF-1R have emerged as potential systemic agents for the treatment of TGCT. Given the role of macrophages in regulating tumorigenesis, CSF1/CSF1R-targeting agents have emerged as attractive therapeutic targets for solid tumors. Pexidartinib is an orally bioavailable and potent inhibitor of CSF-1R which is one of the most clinically used agents. In this review, we discuss the biology of TGCT and review the pre-clinical and clinical development of pexidartinib which ultimately led to the FDA approval of this agent for the treatment of TGCT as well as ongoing clinical studies utilizing pexidartinib in the setting of cancer.Keywords: pexidartinib, colony-stimulating factor 1 receptor, tenosynovial giant cell tumors, pigmented villonodular synovitis

Additional file 2. Surgical management. Table of the various surgical procedures received by the patients in this study. N denotes the number of patients in each group.

Additional file 1. Neo-adjuvant chemotherapy regimens. Table of the various neo-adjuvant chemotherapy regimens received by the patients in this study. N denotes the number of patients in each group. pCR represents the number (and percentage) of patients in each group with a pathologic complete response. RCB represents the median residual cancer burden score (and ranges) in each group.

Additional file 1: Supplementary Table. Baseline characteristics of patients who received trastuzumab, categorized by completion vs interruption of therapy.

Additional file 6. Percentage of TILs, CD8+ T cells, and PD-L1+/PD-1+ cells in TNBC samples before and after NAC. Table of changes in TILs, CD8+ T cells, PD-L1 expression and PD-1 expression following NAC in samples from triple-negative breast cancer patients. There were three pre-NAC samples available and nine post-NAC samples available for analysis. Values are listed as means (and ranges) or the number of samples (and percentage of total group these represented). If samples stained