Utafiti huu unachunguza kwa utaratibu uwepo wa dawa za antifungal na fungicides katika maji taka, maji ya juu ya ardhi, maji ya chini ya ardhi, sludge na mazingira mengine ya ikolojia, na unalenga kuendeleza thamani za Predicted No-Effect Concentration (PNEC) zinazoweza kutumiwa ili kuhakikisha kwamba environmental exposure haichochei selection ya antifungal resistance. Watafiti walichukua tafiti 122 kutoka records 13.527 za awali kwa final synthesis; waliripoti antifungals 54 tofauti katika environmental samples na, kwa sababu hakukuwa na data za kutosha za PNEC mahsusi kwa environmental fungi, walitumia minimum inhibitory concentration (MIC) distributions za Candida albicans kukokotoa PNEC-MIC values kwa antifungals 17. Thamani zilizokokotolewa zinatofautiana kati ya 30 ng/L na 6300 ng/L. Hata hivyo, hizi si experimental environmental safety limits wala binding legal discharge standards zinazotumika sasa; ni starting values zinazohitaji kuthibitishwa baadaye kwa lengo la kupunguza antifungal resistance selection.

Katika environmental screening ya utafiti, compounds za azole class zinajitokeza hasa. Kati ya tafiti 122, fluconazole ilikuwa compound iliyoripotiwa mara nyingi zaidi kwa %44, huku clotrimazole ikiwa %33, miconazole %28 na ketoconazole %27. Hata hivyo, watafiti wanatoa onyo muhimu kwamba asilimia hizi hazionyeshi moja kwa moja true environmental prevalence: high detection frequency ya compound inaweza pia kusababishwa na substance hiyo kuwa imefanyiwa utafiti zaidi au kulengwa mara nyingi zaidi katika analytical methods.

Fluconazole ni mojawapo ya mifano iliyo wazi zaidi ya utafiti kwa upande wa environmental fate. Katika Table 1, Log(K_ow) ya fluconazole imetolewa kuwa 0,50 na water solubility 1390 mg/L. Kwa sababu ya low lipophilicity yake, compound ina tendency kubwa zaidi ya kubaki katika aqueous phase kuliko solid phase. Review inaeleza kwamba fluconazole inaweza kubaki kwa kiasi kikubwa katika final effluent katika wastewater treatment processes na kugunduliwa mara chache zaidi katika sludge. Kwa upande mwingine, compounds kama clotrimazole, ketoconazole, miconazole, itraconazole na terbinafine zenye Log(K_ow) values za juu zaidi zinaweza kujifunga kwa nguvu zaidi kwenye solids na sludge.

Tofauti hii inaonyesha matokeo muhimu kwa wastewater management: kupungua kwa concentration ya antifungal katika treated water hakumaanishi kila mara kwamba chemical imeondolewa kabisa kutoka kwenye system. Lipophilic compounds zinaweza kuondoka katika aqueous phase na kujikusanya katika sludge, na ikiwa treatment sludge itatumika katika agricultural soil, environmental exposure inaweza kuhamia kwenye pathway nyingine. Kwa hiyo, utafiti unapendekeza kwamba water effluent na sludge management zisitathminiwe kama vitu tofauti, bali kama sehemu za One Health risk chain moja.

Mapendekezo makuu ya regulatory ya watafiti ni kwamba, ili kupunguza antifungal resistance selection katika mazingira, si current ecotoxicological PNECs pekee zinazopaswa kutathminiwa, bali pia resistance-selection-focused thresholds zinazohusiana moja kwa moja na antifungal susceptibility ya fungi. Kwa kusudi hili, utafiti unakokotoa MIC_1% value iliyo katika lower end ya MIC distribution na kugawanya value hii kwa 10 kwa assumption kwamba resistance selection inaweza kutokea pia katika concentrations za chini zaidi, hivyo kuzalisha PNEC-MIC.

Kutokana na calculation hii, lowest PNEC-MIC value imekokotolewa kuwa 30 ng/L kwa anidulafungin, 50 ng/L kwa micafungin; na 100 ng/L kwa terbinafine, rezafungin na isavuconazole. Kwa voriconazole, itraconazole, miconazole, econazole, clotrimazole na ketoconazole value ni 200 ng/L; kwa posaconazole 400 ng/L; kwa amphotericin B 1600 ng/L; kwa flucytosine na fluconazole 3200 ng/L; na kwa caspofungin na fenticonazole 6300 ng/L.

Mpangilio huu si toxicity ranking wala clinical hazard ranking. PNEC-MIC values zinategemea MIC distribution iliyotumika na selected C. albicans model. Compound kuwa na PNEC-MIC ya 30 ng/L haimaanishi kwa ujumla kuwa ni “more toxic” kuliko antifungal nyingine yenye value ya 200 au 3200 ng/L.

Utafiti pia unaonyesha kwamba baadhi ya environmental concentrations zilizoripotiwa zimezidi calculated PNEC-MIC values. Kulingana na synthesis ya waandishi, kuna tafiti zilizoripoti environmental measurements zilizo juu ya PNEC-MIC ya 3200 ng/L kwa fluconazole, 200 ng/L kwa voriconazole na itraconazole, 200 ng/L kwa miconazole, clotrimazole na ketoconazole, na 100 ng/L kwa terbinafine. Comparison hii si direct evidence kwamba resistance imeendelea; inaonyesha kwamba concentrations hizo ni exposures zinazoweza kuhitaji detailed experimental investigation zaidi kutoka upande wa resistance selection.

Kwa mtazamo wa Türkiye, utafiti hauundi new environmental concentration dataset au legal PNEC limit kwa Türkiye. Main text iliyopakiwa pia haina Türkiye-specific regulatory assessment. Kwa hiyo, si scientifically appropriate kuhamisha PNEC-MIC values katika Table 2 moja kwa moja kuwa thresholds katika wastewater discharge legislation ya Türkiye. Kwa upande mwingine, utafiti unatoa starting framework kuhusu antifungal classes zipi na concentration scales zipi zinaweza kuwa research priorities ikiwa hospital wastewaters, municipal facilities, loads zinazotokana na matumizi ya dawa, agricultural fungicides na matumizi ya sludge kwenye soil zitafuatiliwa pamoja.

Tatizo kuu la utafiti ni nini?

Starting point ya utafiti ni kwamba antifungal resistance si tatizo linalotokea katika hospital au clinical setting pekee. Antifungal medicines na baadhi ya azole fungicides zinazotumika katika agriculture zinaweza kufika kwenye mazingira kupitia sewerage, hospital discharges, industrial wastewaters, surface runoff na njia nyingine. Environmental fungi zinapokabiliwa mara kwa mara na substances hizi katika concentrations ambazo si lethal au hazisimamishi growth kabisa, ecological pressure ya kuchagua resistant organisms inaweza kutokea.

Utafiti unachunguza uhusiano huu chini ya One Health approach. Human health, animal health na environmental processes si systems tofauti; resistant fungi zinazotokea katika mazingira zinaweza kuwa na consequences kwa effectiveness ya clinical antifungal treatments.

PNEC ni nini?

Predicted No-Effect Concentration (PNEC), katika context ya utafiti, ni protective reference value kwa concentration ambayo haitegemewi kwamba environmental exposure italeta unacceptable effect. Katika utafiti huu, pamoja na classic ecotoxicity effect, antifungal resistance selection inashughulikiwa mahsusi.

Tatizo kuu la waandishi ni kwamba PNECs nyingi zilizopo katika literature kwa antifungals zinategemea toxicity outcomes kutoka organisms kama fish, algae, crustaceans au bacteria. Environmental PNEC data zinazolenga moja kwa moja resistance selection katika fungi ni chache sana.

MIC ni nini na kwa nini ilitumika?

Minimum Inhibitory Concentration (Minimum/Minimal Inhibitory Concentration, MIC), kulingana na definition ya utafiti, ni lowest concentration ya antifungal substance inayokandamiza fungal growth kwa kiwango kinachoonekana, takribani zaidi ya %50. Katika yeast species, assessment kawaida hufanywa baada ya saa 24, na katika molds baada ya growth ya saa 48–72.

MIC ni clinical microbiology metric inayotumika hasa katika antifungal susceptibility testing. Kwa kuwa hakukuwa na direct sufficient PNEC data kwa environmental resistance, watafiti walitumia MIC distribution kama starting point.

PNEC-MIC ilikokotolewaje?

Kwanza utafiti ulikadiria MIC_1% value inayowakilisha lower end ya MIC distribution kwa antifungal fulani. Kisha, kwa kukubali kwamba resistance selection inaweza kutokea chini ya classical MIC, additional safety factor ya 10 ilitumika:

\[ \mathrm{PNEC\!-\!MIC}=\frac{\mathrm{MIC}_{1\%}}{10} \]

Hapa MIC_1% ni concentration inayolingana na takribani lower %1 portion ya modeled MIC distribution. Division factor ya 10 ilitumika kuzingatia difference kati ya MIC na lower concentrations zinazoweza kutoa competitive advantage kwa resistant organisms.

Method hii haitokani moja kwa moja na new environmental field experiment iliyoundwa specifically kwa antifungals. Utafiti unaadapt approach iliyotumiwa awali na Bengtsson-Palme na Larsson kwa antibiotics kwenda kwenye antifungal resistance problem.

Kwa nini Candida albicans ilichaguliwa?

Watafiti walichagua Candida albicans kama main model katika PNEC-MIC calculation. Sababu mbili kuu zilitolewa: C. albicans ni sensitive model kati ya species zilizochunguzwa na ina extensive MIC distribution data katika EUCAST database.

Waandishi wanakubali wazi kwamba ecology na resistance dynamics za environmental fungi ni tofauti na C. albicans. Available data kwamba environmental fungi kwa ujumla zina equal au higher MIC values zilitumika kama justification katika utafiti.

Hata hivyo, C. albicans-based PNEC-MIC si experimentally validated boundary ya resistance selection katika environmental fungal communities zote. Waandishi wanawasilisha values hizi kama starting point kwa development ya environmental PNECs.

Ni publications ngapi zilichunguzwa?

Katika systematic search, awali 13.527 records zilitambuliwa. Kati ya hizi, 13.458 zilitoka PubMed, ScienceDirect na Web of Science databases, na 69 zilitoka Portuguese national open scientific repository RCAAP.

Baada ya kuondoa records 312 za kabla ya 2000 na duplicate records 3378, 9837 unique records zilibaki kwa screening. Manual refinement iliondoa records nyingine 197 na full-text candidates 9640 zilitambuliwa.

Kati ya records hizi, 8955 hazikufikia full-text evaluation katika verification stage na 685 studies ziliingizwa katika eligibility assessment. Kati ya hizo, 70 hazikuweza kupatikana, studies tano ziliondolewa kwa sababu ya language, na studies 488 zisizo na environmental antifungal concentration au suitable quantitative data ziliondolewa. Final systematic synthesis ilifanywa kwa 122 studies.

Kwa nini PRISMA diagram ni muhimu?

Kielelezo 1 cha utafiti kinaonyesha kwa uwazi jinsi records zilivyopunguzwa kutoka 13.527 hadi studies 122. Hivyo, inaweza kufuatiliwa records ngapi zilipotea katika kila stage na sababu kuu za full-text selection.

Hata hivyo, diagram hii pia inaonyesha limitation muhimu: 70 kati ya 685 potential full texts hazikuweza kufikiwa. Waandishi wanakubali wazi kwamba hali hii inaweza kuleta selection bias katika evidence synthesis.

Search ilifanywaje?

Database search ilifanywa tarehe 7 Februari 2024. PubMed, ScienceDirect, Web of Science na RCAAP zilitumika.

Katika PubMed na Web of Science searches, “wastewater” iliunganishwa na terms kama antifungal agents, fungal drug resistance, fluconazole, itraconazole, posaconazole, voriconazole, clotrimazole, terbinafine, anidulafungin, caspofungin, micafungin na risk assessment.

Katika ScienceDirect, shorter search structure ilitumika; katika RCAAP, kutokana na platform na language limitations, Portuguese queries “águas residuais E antifúngicos” na “águas residuais E avaliação de risco” zilitumika.

Kabla ya search strategy, pilot tests tano zilifanywa katika main databases, na pilot searches 20 kwa RCAAP kutokana na platform restrictions.

Ni environmental compartments zipi zilichunguzwa?

Review haikulenga wastewater treatment plant effluent pekee. Kutoka studies:

• wastewater treatment plant influents na effluents,
• hospital wastewaters,
• surface waters,
• rivers na river basins,
• groundwaters,
• treatment sludge na biosolids,
• sediments

antifungal concentrations zinazohusiana nazo zilikusanywa.

Ni antifungals tofauti ngapi zilipatikana katika mazingira?

Katika synthesis ya final studies 122, antifungals 54 tofauti, hasa substances za azole class, ziliripotiwa katika different environmental matrices. Watafiti walitambua jumla ya 371 antifungal detection records/reference points.

Nambari hii haimaanishi environmental samples 371 tofauti; ni jumla ya antifungal reports katika studies za systematic review.

Ni substances zipi ziliripotiwa mara nyingi zaidi?

Katika Kielelezo 2, fluconazole ina highest detection frequency:

Asilimia hizi si direct measurement ya true occurrence probability katika mazingira. Waandishi wanasisitiza kwamba compound kulengwa mara nyingi zaidi au kujumuishwa zaidi katika analytical methods kunaweza kuongeza detection frequency.

Kwa nini classification ya Kielelezo 2 inapaswa kusomwa kwa tahadhari?

Ingawa Kielelezo 2 kinasema kinaonyesha detection frequency ya “antifungal compounds”, graphic pia ina metronidazole na sulfamethoxazole. Maandishi baadaye yanafafanua metronidazole wazi kama antibiotic.

Kwa hiyo, si sahihi kuhitimisha kwamba bars zote katika graphic ni za pharmacological “antifungal” class moja. Kwa Verianla, graphic inatathminiwa kama presentation ya environmental antimicrobial dataset iliyochunguzwa na review; non-antifungal compounds hazija-reclassify kimya kimya.

Kwa nini Fluconazole ni mfano maalum?

Fluconazole ina tendency ya kubaki katika aqueous phase kwa sababu ya high water solubility na low Log(K_ow) value. Katika chanzo, Log(K_ow) ni 0,50 na water solubility ni 1390 mg/L.

Katika systematic review, fluconazole ilionekana katika reports 54 na ikawa antifungal iliyosomwa/kuripotiwa zaidi kwa detection frequency ya takribani %44.

Moja ya highest values iliripotiwa kuwa 236.950 µg/L katika sewerage ya industrial area nchini India. Watafiti wanajadili kwamba hii inaweza kuhusishwa na low flow, high temperature na conditions maalum za pharmaceutical manufacturing area. Extreme value hii haipaswi kutafsiriwa kama general municipal wastewater concentration.

Katika study nyingine, maximum fluconazole concentration katika effluent ya treatment plant katika Henares River basin nchini Spain iliripotiwa kuwa 109.480 ng/L.

Lipophilic antifungals zinaenda wapi?

Utafiti unatumia general classification kwamba substances zenye Log(K_ow) zaidi ya 4 zina tendency kubwa zaidi ya ku-bind kwenye organic solid phases, huku substances chini ya 2 zikiwa more likely kubaki katika aqueous phase.

Katika Table 1:

Uhusiano huu si absolute treatment law. pH, ionization, dissolved organic matter, sludge properties na process design pia zinaweza kuathiri real distribution. Chanzo kinatumia Log(K_ow) kama moja ya indicators kuu zinazosaidia kuelezea compound behavior.

Je, antifungal iliyoondoka kwenye maji imeondolewa kweli?

Hapana. Huu ni mmoja wa environmental messages muhimu za utafiti. Lipophilic antifungal inapoadsorb kutoka aqueous phase kwenda sludge, concentration katika wastewater effluent inaweza kupungua; lakini ikiwa molecule haijadegrade, environmental load imehamishwa kwenda phase nyingine.

Matumizi ya treatment sludge au biosolid kama agricultural fertilizer/soil conditioner yanaweza kuunda direct exposure pathway ya antifungals zilizojikusanya kwenda kwenye soil.

Waandishi wanaeleza kwamba wakati wa study hakukuwa na acceptable limits mahsusi kwa antifungal concentrations katika land application ya sludge. Kauli hii ni regulatory assessment ya utafiti katika 2026 publication context.

Sludge concentration inconsistency ndani ya chanzo

Review inaripoti maximum ya 2547 ng/g katika sludge kwa clotrimazole, 10.000 ng/g kwa ketoconazole na 2069 ng/g kwa miconazole kutoka studies tofauti.

Hata hivyo, katika sehemu ya baadaye ya discussion hiyo hiyo, values 2547 ng/L, 1800 ng/L na 2069 ng/L zinatumika kwa substances hizi kwa mtiririko huo. Katika sludge concentration, units za ng/g na ng/L si equivalent na number ya ketoconazole pia inabadilika.

Kwa kuwa chanzo hakielezi difference hii, Verianla haitumii values hizi kama common definitive maximum values.

Je, high concentration ilionekana tu katika substances zilizofanyiwa utafiti mara nyingi?

Hapana. Moja ya points zinazosisitizwa na waandishi ni kwamba baadhi ya substances zilizofanyiwa utafiti kidogo pia zilifikia high environmental concentrations.

Kwa mfano, ingawa climbazole iliripotiwa katika studies 11 tu, iliripotiwa katika municipal wastewater nchini Germany kwa kiwango cha 1350 ng/L. Terbinafine ilionekana katika records chache, lakini ilipimwa kuwa 15.000 ng/L katika surface water nchini India.

Hii inaonyesha kwamba detection frequency pekee haitoshi kwa environmental prioritization. Concentration, exposure frequency na level inayoweza kuwa effective kwa resistance selection vinapaswa kutathminiwa pamoja.

Agricultural fungicides zinafikiaje wastewater?

Utafiti unajadili agricultural azoles kama source muhimu ya environmental load. Baadhi ya fungicides, hasa tebuconazole, zimeripotiwa katika surface water, wastewater iliyochanganyika na rainwater na treatment plants karibu na rural areas.

Moja ya highest wastewater concentrations ya tebuconazole katika studies ilikuwa 1893 ng/L. Waandishi pia wanajadili urban source pathway ambapo fungicides zinazotumika katika building paints na coatings zinaweza kuoshwa kutoka surfaces na rainfall na kufika kwenye sewer system.

Kwa nini food industry ni muhimu?

Review inaonyesha kwamba post-harvest fruit processing na food industry zinaweza kuunda high point sources kwa baadhi ya fungicides.

Kwa imazalil, 19.802 ng/L iliripotiwa katika food-industry wastewater effluent, na kwa thiabendazole 926 ng/L katika context hiyo hiyo, huku imazalil katika municipal effluent ikiwa 496 ng/L.

Kwa thiabendazole, extremely high value ya 1.900.000 ng/L pia iliripotiwa katika influent ya treatment plant nyingine nchini Spain. Kwa kuwa values hizi zinatoka sites na sources tofauti, hazipaswi kulinganishwa kama standardized process performance.

Kwa nini conventional wastewater treatment inaweza kutotosha?

Primary na secondary wastewater treatment processes hazikuundwa specifically kuondoa antifungal medicines. Primary treatment inategemea zaidi physical settling na solids separation, huku secondary treatment ikitegemea biological organic-matter transformation.

Kwa hiyo, baadhi ya antifungals zinaweza kubaki katika effluent bila biodegradation ya kutosha; nyingine zinaweza kuadsorb kwenye sludge. Chanzo kinawasilisha literature kwamba substances kama fluconazole, bifonazole, naftifine, posaconazole na ciclopirox zinaweza kubaki baada ya conventional treatment.

Membrane bioreactors zinaweza kutoa nini?

Utafiti unajadili membrane bioreactors (MBR) kama moja ya advanced options zinazoweza kuboresha antifungal removal.

Katika South African study iliyowasilishwa katika review, metronidazole na ketoconazole pamoja na baadhi ya metabolites zao zilipimwa katika treatment line yenye MBR. Chanzo kinawasilisha:

• removal kutoka takribani %60 hadi karibu %100 kwa metronidazole,
• %40–75 removal kwa metronidazole metabolite,
• removal kutoka takribani %60 hadi karibu %100 kwa ketoconazole,
• ketoconazole N-deacetyl metabolite kutogunduliwa katika effluent

kama matokeo.

Kuna terminology boundary muhimu hapa: makala yenyewe inafafanua metronidazole kama antibiotic. Kwa hiyo, mfano huu haupaswi kutathminiwa kama controlled comparison ya MBR specific kwa antifungals pekee.

Kwa nini MBR inaweza kusaidia hasa kwa hydrophobic substances?

Katika MBR example inayojadiliwa katika chanzo, pore size ya ultrafiltration membranes imepewa kuwa takribani 0,2–0,5 µm. Antifungal molecule yenyewe si lazima ishikiliwe mechanically kwa sieve katika scale hii; interpretation ya utafiti ni kwamba compounds zilizo-bind kwenye particulate phase zinaweza kushikiliwa vizuri zaidi katika system pamoja na biomass na particles zinazozuiliwa na membrane.

Kwa hiyo, simplistic mechanism ya “0,2 µm pore physically stops antifungal molecule” haipaswi kuhitimishwa.

Ni advanced treatment methods gani nyingine zinazojadiliwa?

Katika utafiti, potential advanced processes kwa antifungals ni pamoja na:

• new sorbents kama hydrogels,
• graphene-modified adsorbent materials,
• electrochemical advanced oxidation,
• photo-oxidation,
• photocatalysis,
• UV-based advanced oxidation

.

Methods hizi zimetolewa kutoka studies tofauti katika review. Kwa kuwa utafiti haukufanya experiment inayolinganisha antifungal mixture ileile katika influent ileile kwa technologies zote, hauhitimishi ni ipi universally best option.

Verianla Live: PNEC-MIC values kwa antifungals 17

Values zote hapa chini zimetolewa kutoka Table 2 ya utafiti. Graphic inaonyesha tu scale difference kati ya PNEC-MIC values zilizokokotolewa kwa method ileile. Low PNEC-MIC value haimaanishi moja kwa moja higher toxicity, higher clinical risk au more dangerous drug.

Je, model fit ni sawa kwa antifungals zote?

Hapana. MIC distributions zilifit kwa normal distribution model na \(R^2\) values zimetolewa katika Table 2.

Kwa compounds nyingi, fit ni high sana. Kwa mfano, \(R^2=0{,}998\) iliripotiwa kwa anidulafungin, \(R^2=0{,}999\) kwa fluconazole, na \(R^2=0{,}999\) kwa rezafungin na isavuconazole.

Kwa terbinafine, \(R^2=0{,}724\) inaonyesha model fit dhaifu zaidi kuliko compounds nyingi nyingine. Kwa hiyo, terbinafine PNEC-MIC ya 100 ng/L haipaswi kutathminiwa kana kwamba ina model uncertainty sawa na drugs nyingine kwa kuangalia final number pekee.

Je, PNEC ya literature na PNEC-MIC ni kitu kimoja?

Hapana. Table 3 ya utafiti inalinganisha approaches mbili tofauti. Classical PNECs kutoka systematic literature zinategemea zaidi toxicity effects katika organisms kama algae, fish, crustaceans, bacteria au organisms nyingine, huku PNEC-MIC values zikilenga C. albicans antifungal susceptibility na resistance selection.

Kuwa higher kwa PNEC-MIC values katika examples hizi tatu hakumaanishi kwamba classical PNECs ni “wrong”. Methods hizi mbili zinalenga kulinda different biological effects na different organisms.

Je, environmental concentrations zinazidi PNEC-MIC values?

Ndiyo, systematic review inaeleza kwamba baadhi ya studies ziliripoti measurements zilizo juu ya calculated PNEC-MIC values.

Kulingana na comparison ya utafiti wenyewe:

• 3200 ng/L kwa fluconazole,
• 200 ng/L kwa voriconazole,
• 200 ng/L kwa itraconazole,
• 200 ng/L kwa miconazole,
• 200 ng/L kwa clotrimazole,
• 200 ng/L kwa ketoconazole,
• 100 ng/L kwa terbinafine

kuna environmental records zinazozidi PNEC-MIC values.

Kwa econazole na fenticonazole, concentrations zilizolinganishwa katika review zilibaki chini ya PNEC-MIC values. Kwa antifungals nyingine zilizokokotolewa, imeelezwa kwamba hakuna suitable environmental occurrence result iliyopatikana katika systematic search.

Environmental sample kuwa juu ya PNEC-MIC si direct evidence kwamba resistant fungi zimeendelea katika site hiyo. Value inaonyesha tu exposure level inayoweza kuhitaji detailed resistance-selection research zaidi chini ya model iliyopendekezwa na source authors.

Kwa nini Imazalil ilishughulikiwa kando?

Kwa kuwa routine C. albicans MIC distribution haikupatikana kwa imazalil, utafiti haukutoa standard PNEC-MIC value katika Table 2. Badala yake, approximate approaches mbili zilijadiliwa.

C. albicans CYP51 enzyme inhibition estimate ilitumia effectiveness value ya takribani 24 µg/L ilitumika na PNEC proposal ya takribani 0,024 µg/L ikapatikana. Vinginevyo, kwa kutumia similar imidazole na dermatophyte MIC values, PNEC ilikadiriwa kuwa katika range ya takribani 0,03–1 µg/L.

Values hizi si validated PNEC-MIC zilizopatikana kwa standard method katika Table 2; chanzo kinaziwasilisha kama example estimates za kushughulikia data gap ya imazalil.

Kwa nini sub-MIC exposure ni muhimu kwa antifungal resistance?

Fungus kuendelea kuishi chini ya antifungal concentration haimaanishi kwamba hakuna biological effect. Utafiti unajadili previous studies zilizoripoti metabolic, tolerance au resistance-selection-related effects kwa caspofungin, voriconazole na fluconazole katika doses chini ya MIC.

Literature hii ndiyo main justification ya kutotumia MIC_1% moja kwa moja kama threshold katika PNEC-MIC calculation, bali kuigawa tena kwa 10.

Kwa nini information kuhusu echinocandins ni dhaifu zaidi?

Moja ya gaps muhimu zaidi za utafiti kwa future ni echinocandin class. Waandishi wanaeleza kwamba environmental fate ya echinocandins katika wastewater haijaripotiwa vya kutosha katika scientific literature.

Ingawa PNEC-MIC values zimekokotolewa kwa caspofungin, anidulafungin, micafungin na rezafungin, environmental data kuhusu real concentrations zao katika wastewater environments na relationship yao na resistance selection ni limited sana.

Chanzo kinatoa expectations kwamba zinaweza kubaki katika maji au sludge kulingana na hydrophilic/lipophilic properties. Statements hizi si measured environmental fate results, bali future research projections za waandishi kulingana na physicochemical properties.

Utafiti unapendekeza nini kwa regulation?

Waandishi wanapendekeza kwamba PNEC-MIC values zinaweza kutumika ku-prioritize antifungals, kuchagua target substances katika monitoring programs na kutoa starting data kwa future environmental standards.

Utafiti pia unajadili kwamba katika European Union monitoring list ya 2025, antifungal azoles kama clotrimazole, fluconazole na miconazole pamoja na agricultural azole fungicides nyingi ziliingizwa katika monitoring.

Hata hivyo, “kuwa kwenye monitoring list” na “kuwa na binding discharge limit” si kitu kimoja. Main claim ya makala ni kwamba regulatory thresholds zitakazounganisha environmental antifungal concentrations na resistance selection bado zinahitaji kuendelezwa.

Matokeo yanayoungwa mkono na utafiti

• Antifungals, hasa azoles, zimeripotiwa katika different environmental matrices kama wastewater, surface water, groundwater na treatment sludge.
• Conventional wastewater treatment haiondoi antifungals zote kikamilifu.
• Hydrophilic antifungals zinaweza kubaki katika aqueous phase, huku transfer ya more lipophilic compounds kwenda sludge na biosolid phase ikiwa important environmental pathway.
• Fluconazole ni moja ya antifungals zilizoripotiwa mara nyingi zaidi katika literature iliyochunguzwa.
• Baadhi ya antifungal concentrations katika mazingira zimeripotiwa juu ya PNEC-MIC references zilizokokotolewa katika utafiti.
• Current environmental PNEC database haitoshi kwa fungal resistance selection.
• Candida albicans MIC distributions kutoa PNEC-MIC ni starting approach inayoweza kutumiwa kwa experimental environmental threshold development.
• Wastewater effluent na treatment sludge zinapaswa kutathminiwa pamoja; pollutant kuondoka katika water phase hakuthibitishi full degradation.
• Antifungal pollution na antifungal resistance zinapaswa kuchunguzwa pamoja katika One Health perspective.

Matokeo ambayo utafiti hauungi mkono au haujathibitisha

• PNEC-MIC values si current legal wastewater discharge limits.
• Haijathibitishwa kwamba kila concentration chini ya PNEC-MIC ni absolutely safe kwa environmental fungi zote.
• Candida albicans haiwakilishi resistance dynamics za environmental fungal species zote.
• Kuzidi PNEC-MIC pekee hakuthibitishi kwamba antifungal resistance imeendelea katika field.
• Compound kuripotiwa mara nyingi zaidi haimaanishi lazima iwe more prevalent katika mazingira.
• Adsorption kwenye sludge haimaanishi kwamba antifungal imeondolewa environmentally.
• Haijaonyeshwa kwamba MBR, advanced oxidation au adsorption technique yoyote ni universal solution kwa antifungals zote.
• PNEC-MIC values 17 hazitegemei kiasi sawa cha experimental environmental data.
• Utafiti hauweki legal discharge standard au national environmental-risk threshold kwa Türkiye.
• Chanzo hakina long-term field experiment inayothibitisha PNEC-MIC values zote 17 katika environmental fungal communities.

Mbinu na Matokeo ya Utafiti

Research design

Utafiti unaunganisha scientific components mbili kuu:

1. Systematic literature search kutambua environmental occurrence ya antifungals na existing PNEC values.
2. PNEC-MIC calculation kwa antifungals 17 kutoka Candida albicans MIC distributions ili kupunguza data gap kuhusu environmental fungal resistance.

Kwa hiyo, utafiti si narrative review pekee; unaongeza new secondary calculation layer juu ya systematically selected environmental data. Hata hivyo, hakuna new environmental samples zilizokusanywa, antifungal concentrations hazikupimwa laboratory na PNEC-MIC values hazikuthibitishwa kupitia environmental microcosm au field experiment.

Systematic review standard

Waandishi wanaeleza kwamba waliendesha method kulingana na Joanna Briggs Institute approach na kuripoti kulingana na PRISMA 2020.

Katika abstract, method inaitwa “Preferred Reporting Items for Systematic literature reviews and Meta Analyses extension for Scoping Reviews (PRISMA-SLR)”. Expression katika main methods section ni PRISMA 2020. Terminological difference hii haijaelezwa katika chanzo.

Search sources

Inclusion na exclusion approach

Publication period iliwekwa 2000–2024. Waandishi wanataja kwamba 13.215 kati ya initial records 13.527, yaani %97,7, zilichapishwa katika kipindi hiki kama moja ya justifications za date range.

Kulingana na PCC framework, studies zisizohusu antifungal agents au environmental occurrence zao, studies zinazotaja antifungal lakini hazitoi quantitative environmental concentration au PNEC, na publications zilizo katika clinical/laboratory context pekee bila environmental relationship ziliondolewa.

Screening bias ilipunguzwaje?

Initial screening ilifanywa na independent reviewers wawili. Wakati kulikuwa na disagreement kati ya researchers wawili, third reviewer alihusishwa katika decision process.

Method hii inalenga kupunguza individual screener error. Hata hivyo, makala haitoi standardized study-quality score kama ROBINS-I, QUADAS au equivalent kwa kila one of included studies 122.

Access na language bias

Studies 70 kati ya 685 eligibility candidates hazikuweza kufikiwa kutokana na institutional paywalls na kutokuwepo kwa open-access version. Kati ya records 615 zilizobaki, English na Portuguese tu zilitathminiwa, na publications tano zaidi ziliondolewa kutokana na language.

Waandishi wanakubali hasa kwamba access problem inaweza kuleta selection bias katika systematic evidence synthesis.

Geographic representation imesambazwa vipi?

Literature iliyokusanywa imejikita zaidi Europe na Asia. Main text inaeleza studies 22 kutoka China, 16 kutoka Spain, 8 kutoka Sweden, 8 kutoka India na 6 kutoka Germany.

Underrepresentation ya Africa na Latin America, kulingana na watafiti, haithibitishi kwamba real antifungal pollution ni lower katika regions hizi. Monitoring infrastructure, research funding, language na international bibliographic visibility vinaweza kuathiri data distribution.

Temporal representation

Publication range ya studies katika final dataset iliyotajwa katika main text ni 2005–2023, na idadi ya publications iliongezeka baada ya 2012. Highest number of publications iliripotiwa mwaka 2015 ikiwa studies 15.

Data hii inawakilisha systematic search ya 7 Februari 2024. Makala kuchapishwa 2026 haimaanishi kwamba environmental occurrence synthesis inajumuisha literature ya 2025–2026.

PNEC-MIC modeling

Katika EUCAST, C. albicans MIC distributions zilichambuliwa kwa nonlinear regression kwa kutumia normal distribution model. Baada ya kukadiria MIC_1% inayowakilisha takribani lower %1 portion ya distribution, value iligawanywa kwa 10.

Table inaonyesha kwamba takribani 210-fold range katika PNEC-MIC values haitokani na drug name pekee bali pia position ya MIC distribution. Hata hivyo, kiwango ambacho PNEC-MIC inalingana na real environmental safety threshold kinahitaji direct field validation.

Data source katika Table 2 si sawa kwa compounds zote

Caspofungin row imehusishwa na unpublished data katika source footnote. Terbinafine imehusishwa na publication ya Arendrup na wenzake ya 2020; miconazole, econazole, clotrimazole, ketoconazole na fenticonazole zimehusishwa na study ya Kroustali na wenzake ya 2025.

Kwa hiyo, ingawa table imeprocess kwa mathematical formula moja, evidence origin ya starting MIC data si sawa katika rows zote.

Classification problem katika Table 3

Table 3 inalinganisha PNEC values zilizopatikana katika systematic review na PNEC-MIC values. Hata hivyo, pamoja na substances zinazohusiana na target topic kama azoxystrobin, carbendazim, climbazole, clotrimazole, fluconazole na ketoconazole, table pia ina non-antifungal chemicals kama benzotriazole, ethylparaben, methylparaben, metronidazole, sulfamethoxazole na triclocarban.

Kwa hiyo, kutumia Table 3 yote kama “antifungal drug PNEC table” kunapanua scientific classification kupita kiasi. Katika Verianla text, antifungal PNEC-MIC comparison imetumika tu kwa substances ambazo clearly zinafaa topic.

Supplementary Table S1 boundary

Detailed country, matrix na source list ya environmental concentrations katika review ipo katika Supplementary Table S1. Main PDF ina synthesis na selected maxima pekee zilizotolewa kutoka table hiyo.

Kwa kuwa Supplementary Table S1 haipo katika uploaded file, Verianla haichukulii rows zote za supplementary table hii kama independently verified. Values zilizotolewa moja kwa moja katika main text zinaweza kutumika; hakuna new comparison iliyofanywa kutoka invisible supplementary-table rows.

Strongest aspects za utafiti

Moja ya strengths za utafiti ni kuleta environmental antifungal occurrence na clinical antifungal susceptibility data chini ya One Health problem moja. Hivyo, si swali tu la “chemical ilipatikana katika mazingira?” linaloulizwa, bali pia “concentration iliyopatikana inaweza kuendana na scale gani kwa upande wa resistance selection?”

Clear PRISMA flow, independent screeners wawili, reporting ya idadi ya inaccessible studies na explicit PNEC-MIC formula huongeza reassessability ya method.

Main limitations za utafiti

Limitation ya kwanza ni kwamba PNEC-MIC si directly measured selection concentration katika environmental fungal communities, bali protective proxy derived from C. albicans MIC data.

Limitation ya pili ni clear imbalance katika geographic distribution ya studies. Dominance ya Europe na Asia si equivalent na real map ya global antifungal pollution.

Limitation ya tatu ni kwamba full texts 70 hazikuweza kufikiwa na kutumia English/Portuguese studies pekee kunaweza kuleta selection bias.

Limitation ya nne ni kwamba systematic search ilifanywa 7 Februari 2024. New environmental occurrence studies za remaining 2024 na kipindi cha 2025–2026 hazijaingia automatically katika main systematic dataset.

Limitation ya tano ni kwamba baadhi ya tables na figures katika utafiti zinaonyesha non-antifungal antimicrobials chini ya antifungal headings na kuna unit/value inconsistencies katika sludge concentrations.

Limitation ya sita ni kwamba PNEC-MIC calculations kwa baadhi ya substances zinategemea unpublished MIC data au MIC data kutoka sources tofauti.

Main scientific interpretation

Hitimisho linaloweza kutetewa zaidi la utafiti ni kwamba antifungal pollution inapaswa kujumuishwa katika water na sludge management si kwa classic environmental toxicity pekee, bali pia kwa upande wa resistance selection.

PNEC-MIC values 17 si final regulatory limits zilizotatua problem hii. Main contribution ya utafiti ni kupendekeza testable quantitative bridge kati ya environmental antifungal concentration na fungal susceptibility data. Critical next step ni experimental validation ya thresholds hizi katika real wastewater matrices, environmental fungal communities na chini ya long-term exposure.

Dokezo la Chanzo na Mbinu

Jina kamili la utafiti asilia: Predicted no effect concentrations of antifungals for wastewater management and agricultural use

Waandishi na mpangilio: D. Gil; S. José; A. Ascenso; M. Novak Babič; E. Segal; J. Meletiadis; J. P. Gangneux; C. J. Weiskerger; H. M. Solo-Gabriele; E. Valério; J. Brandão.

Co-first authors: D. Gil na S. José. Chanzo kinaeleza kwamba authors wawili walichangia kwa kiwango sawa na kushiriki first authorship.

Corresponding authors: E. Valério na J. Brandão.

Taasisi: Department of Environmental Health, National Institute of Health Doutor Ricardo Jorge, Lisboa, Portugal; Department of Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia; Department of Clinical Microbiology and Immunology, School of Medicine, Tel Aviv University, Tel Aviv, Israel; Clinical Microbiology Laboratory, Attikon University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece; Centre National de Référence des Mycoses et Antifongiques LA-AspC Aspergilloses chroniques, European Excellence Center for Medical Mycology, Centre hospitalier Universitaire de Rennes, Rennes, France; University Rennes, CHU Rennes, Inserm, EHESP, Irset UMR_S 1085, Rennes, France; United States Environmental Protection Agency, Atlanta, GA, United States; Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, United States; cE3c – Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências da Universidade de Lisboa, Lisboa, Portugal.

DOI: 10.3389/ftox.2026.1767925

Jarida: Frontiers in Toxicology.

Section: Environmental Toxicology.

Publisher / platform: Frontiers.

Volume / article number: Volume 8, Article 1767925.

Source type na peer-review status: Ni study iliyochapishwa na Frontiers kama “Review” article na kupita peer review. Scientific method inaunganisha JBI/PRISMA-based systematic literature search na PNEC-MIC calculation kutoka Candida albicans MIC distributions.

Article dates: Received 15 December 2025; Revised 16 January 2026; Accepted 26 January 2026; Published 24 March 2026.

Editor: Martin Ezechias.

Reviewers: Sandra Bakare na Yago Guida.

Official DOI link:https://doi.org/10.3389/ftox.2026.1767925

Official publication link:Frontiers — official article page

License: Creative Commons Attribution License (CC BY).

Funding: Study iliungwa mkono na Fundação para a Ciência e Tecnologia chini ya CE3C unit funding UIDB/00329/2025 na CHANGE LA/P/0121/2020. Kwa Monika Novak Babič, support kutoka Slovenian Research and Innovation Agency kupitia MRIC UL I0-0022 na P1-0198 pamoja na European Union Horizon Europe Grant No. 101185862 iliripotiwa. Study pia inaripoti co-funding support chini ya EU4Health program Grant Agreement No. 101140460 EU-WISH.

Data na supplementary material: Makala inaeleza kwamba Supplementary Table S1 na completed PRISMA 2020 checklist zipo katika supplementary material. Uploaded main source ni main article ya kurasa 18 pekee; Supplementary Material files husika hazijachunguzwa independently katika tathmini hii ya Verianla.

Conflict of interest: Waandishi waliripoti kwamba hakuna relationship inayoweza kuleta commercial au financial conflict of interest. Pia ilifichuliwa kwamba E. Valério alikuwa member wa Frontiers editorial board wakati wa submission, na imeelezwa kwamba hii haikuathiri peer-review process au final decision.

Generative AI statement: Waandishi waliripoti kwamba hawakutumia generative AI katika kuunda makala. Frontiers pia inatoa standard platform note kwamba baadhi ya alternative texts za figures zinaweza kuwa zimeundwa kwa AI support ya platform yenyewe.

U.S. EPA disclaimer: Makala inaeleza wazi kwamba study si product ya U.S. Government au U.S. Environmental Protection Agency na kwamba author husika hakufanya kazi hiyo kama sehemu ya government duty.

Author contributions: D. Gil na S. José formal analysis, investigation, original draft na review/editing; A. Ascenso formal analysis na writing; M. Novak Babič na E. Segal writing; J. Meletiadis na J. P. Gangneux investigation na writing; C. J. Weiskerger na H. M. Solo-Gabriele writing; E. Valério data curation, formal analysis, investigation, methodology, project administration, supervision, validation, visualization na writing; J. Brandão conceptualization, formal analysis, funding acquisition, investigation, project administration, resources, supervision, validation, visualization na writing.

Systematic-search date boundary: Database search ilifanywa 7 Februari 2024. Makala kuchapishwa 2026 haimaanishi kwamba systematic environmental concentration dataset inajumuisha literature ya 2025–2026.

Access na language boundary: Publications 70 kati ya 685 katika eligibility stage hazikuweza kufikiwa; English na Portuguese studies pekee zilitathminiwa. Waandishi wanakubali kwamba hali hii inaweza kuleta selection bias.

Risk-of-bias boundary: Independent screeners wawili na third reviewer katika disagreements walitumika. Hata hivyo, standardized quantitative study-level risk-of-bias scoring haijaripotiwa kwa included studies.

PNEC-MIC boundary: PNEC-MIC values si definitive thresholds zilizopimwa experimentally katika environmental fungal communities. Ni model values derived from lower part ya Candida albicans MIC distribution na additional safety factor ya 10.

Model-organism boundary:Candida albicans ni clinically important species yenye extensive MIC data; hata hivyo, haiwakilishi ecology na resistance dynamics zote za environmental fungi.

Data-origin boundary: Starting MIC data za PNEC-MIC calculations hazitoki source ileile kwa antifungals zote. Kwa caspofungin, Table 2 inaeleza kwamba unpublished data zilitumika; terbinafine na baadhi ya imidazoles zinategemea published studies tofauti.

Model-fit boundary: Kwa terbinafine, normal-distribution fit ni \(R^2=0{,}724\), lower kuliko compounds nyingi nyingine katika table. PNEC-MIC values hazipaswi kutathminiwa kana kwamba zina same model certainty kwa kuangalia final number pekee.

Classification inconsistency: Katika baadhi ya structures kama Kielelezo 2 na Table 3, non-antifungal substances kama metronidazole, sulfamethoxazole, benzotriazole, parabens na triclocarban zipo chini ya antifungal headings au katika comparison ileile. Substances hizi hazija-reclassify kimya kimya kama antifungals na Verianla.

Sludge unit/value inconsistency: Katika chanzo, sludge concentrations za clotrimazole, ketoconazole na miconazole zimeripotiwa kama ng/g katika sehemu moja na ng/L katika sentence nyingine; number ya ketoconazole pia inabadilika. Inconsistency hii haijasahihishwa kimya kimya.

Regulatory-interpretation boundary: PNEC-MIC values katika Table 2 zimependekezwa na waandishi kama starting references kwa future regulation na monitoring studies. Utafiti hauonyeshi kwamba values hizi ni current binding legal discharge limits.

Scientific-source boundary: Environmental concentrations, detection frequencies, PNEC/PNEC-MIC values, treatment mechanisms na resistance assessments katika makala hii ya Verianla zinategemea study iliyochunguzwa pekee. External sources zilitumika tu kuthibitisha bibliographic identity, publication record, peer review na license information; hakuna new experimental result kutoka nje iliyoongezwa kwenye main scientific narrative.